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Every personal detail is a tell. From your choice of college major, to the industry you work in, to the company within that industry—each decision is part of a sorting phenomenon populating certain workplaces with Democrats and others with Republicans.

We’re socialized to not talk politics at the office to avoid polarizing issues that could break norms of professional behavior. But according to a new study from two Harvard researchers, that norm may have obscured a startling partisan divide at the workplace: Republicans and Democrats are sorting into different fields of study, industries, and companies.

Workers aren’t just pawns in this partisan sorting; they’re actively choosing it, although perhaps subconsciously. As the study authors Sahil Chinoy and Martin Koenen found, “The median Democrat or Republican would trade off 3% in annual wages for an ideologically congruent version of a similar job.”

“Is [3 percent] big or small?” Chinoy asks. “It’s less than something like health care. It’s sort of actually comparable in magnitude to some of these softer amenities, things like having a relaxed versus a fast pace of work, for example, or having training opportunities at work. People seem to care similarly about the ideological nature of the job.”

The following is a transcript of the episode:

Jerusalem Demsas: I have a bit of a weird job for several reasons, but for one: Many of my colleagues’ varied ideological commitments are pretty clear due to the nature of our work.

But I was curious about what workplaces look like in less overtly political places. Do people often know the political opinions of their colleagues and bosses? Could work be a place for the healthy mixing of people with different partisan identities?

Probably not. At least, that’s what I take away from a new paper called “Political Sorting in the U.S. Labor Market,” which argues that political segregation is extremely common in the workplace. According to the authors, “a Democrat or Republican’s co-worker is 10 percent more likely to share their party” than what you might expect based on where their workplace is located.

Why? Well, it’s largely because workers are opting into college majors, jobs, industries, and companies that correspond with their partisan identities. Republicans are more likely to have studied business, finance, engineering, and technology, while Democrats are more likely to have studied the arts, social sciences, and the humanities.

Industries themselves are therefore more likely to have employees of one party rather than the other, but even within industries, companies are attracting one party’s adherents over the other.

My name’s Jerusalem Demsas. I’m a staff writer at The Atlantic, and this is Good on Paper, a policy show that questions what we really know about popular narratives. My guest today is Sahil Chinoy, who co-authored this paper while finishing up his economics Ph.D. at Harvard. Sahil himself is on the job market, I’m sure headed to one of those ideologically diverse workplaces so common in academia.

Sahil, welcome to the show.

Sahil Chinoy: Thank you. Thanks so much for having me.

Demsas: So before you conducted your research project, did you think that workplaces were more or less segregated than other areas of life, like neighborhoods, schools, etcetera?

Chinoy: I think somewhat less. We’ve all heard this idea that there should be, quote, “no politics at work.” And I think I took that to heart and thought the workplace might be a uniquely important site where there’s less partisan or political segregation than some of the other environments that we inhabit, like schools and certainly neighborhoods. There’s a lot of attention paid to partisan segregation, particularly across space, across neighborhoods.

And I do think that I thought that the workplace would exhibit less sorting than that. How much less? I don’t know. I certainly thought that it can’t be the case that it’s perfectly even.

Demsas: Yeah, I mean, it’s like when you’re young, and you’re in, like, K-12 or something, it’s the time of your life when you’re repeatedly kind of interacting with people you didn’t choose to be interacting with. It’s your teachers, other kids at school.

And when you grow up, work is basically one of the only times when you’re being forced to go anywhere that you are not actively choosing who you’re going to be interacting with. Obviously, there’s a ton of segregation that comes from where people are in school.

But I think the fact that, like, this is arguably the only place that adults are interacting with people that they’re not opting into on a regular basis—that leads people to kind of feel like, Oh this is probably, like, the most generative space for reaching people across the partisan aisle.

But you do not find this. So walk me through your paper. What did you do to investigate whether workplaces were segregated by party?

Chinoy: Yeah. So just one point on that. I think that’s exactly right. I think the idea here is, like, people have less ability to choose who their co-workers are compared to other people that they interact with, and that’s what generates segregation.

I will note, though, that—it’s kind of funny. When I bring this point up to academics and to professors, there’s sort of the one group, I think, that doesn’t really see this. They’re like, What do you mean? We can perfectly choose who our colleagues are.

Demsas: (Laughs.) That’s, in fact, the whole point.

Chinoy: That’s what hiring is. That’s the whole point. But I think generally, yes. I think that’s the idea.

So we’re sort of starting with this basic premise that, you know, maybe the workplace is less politically segregated than some of these other environments—not such a hard question to pose or to ask. I think it’s just a hard question to answer.

And it’s a hard question to answer, I think, primarily because of a data constraint. We have very high-quality and large-labor-market surveys in the U.S., but they don’t ask questions about politics or partisan affiliation. And we have large and high-quality political surveys, but they usually don’t ask questions about where exactly people work. And even if they did, they’re large, but they’re not large enough to really capture who is working with whom.

And so the starting point of this paper is really to say we have this pretty, to some extent, obvious question: To what extent do Democrats work with Democrats and Republicans work with Republicans? And how are we going to answer it? And the way we answer it is by combining two sources of information: On the one hand, public LinkedIn profiles—so scraped LinkedIn profiles that list where everyone works and some other characteristics about them, often where they went to college or their educational background. And we combine that with administrative voter records.

And so in the U.S., who you vote for is not public. But in 30 states and the District of Columbia, which party you register with is public. And so we combine those two sources of information, and that lets us see who is working with whom and everyone’s party affiliation. And that’s how we can quantify the magnitude of this partisan segregation at work.

Demsas: So you find that “a Democrat or [a] Republican’s co-worker is 10 percent more likely to share their party than expected based on local partisan shares.” Can you just unpack that finding? What does that mean?

Chinoy: Yeah. So the idea is: We want to benchmark the share of your co-workers who share your party affiliation against what we might expect. And so, you know, to give you a concrete example, say you are a Democrat, and you work at Google in Mountain View, then a high share of your co-workers are fellow Democrats. I think it’s something like 55 percent in our data. So that’s, you know, a relatively high share of Democrats. But what should we actually expect? Should we benchmark that against the share of Democrats in the U.S. as a whole?

And so our baseline measure takes that sort of realized share of co-partisans—so the 55 percent of Democrats that share your workplace—and divides it by the share of Democrats in your local labor market, which we operationalize as a commuting zone. Commuting zones are sort of aggregations of counties that are precisely designed to capture these kinds of commuting patterns, who could reasonably share your workplace.

And it turns out—I’m going to forget the exact number, but you know, it turns out—that share is quite high for Google in Mountain View. So you’re a Democrat at Google Mountain View—your co-workers are 6 percent more likely to share your party affiliation than you would expect based on the local shares of Democrats and Republicans. And then we generalize that for everyone. We do that for every person in our sample, tens of millions of people, and that’s how we arrive at that 10 percent number.

Demsas: This is, I think, a really great way of putting it, because, obviously, someone’s going to say, you know, Okay, Google—you’re in California. You’re in Silicon Valley. This is just a high-Democrat place, so are you just, like, looking at, basically, that there is geolocation sorting that’s already happening? And you’re saying it’s not just the fact that, like, there are locational differences in partisanship. It’s that even taking that into account, workplaces are even more segregated based on party than you would expect just by, like, walking around and taking a random sampling of people who live in the commuting zone that Google is in.

Chinoy: Yeah, that’s exactly right. And, you know, I can compare against the national shares, and if I do that, that number is 20 percent. It’s twice as high as the baseline statistic that I quoted for you earlier. And that’s a meaningful number, too, but what sort of intuitively accords with people’s sense of how to measure partisan segregation? It’s probably comparing against the local environment. And that’s why that 10 percent number is kind of our preferred estimate.

Demsas: How does this compare to the level of partisan segregation that we observe in other places? We know, for instance, that there’s partisan segregation happening in schools or in dating markets and churches and stuff like that. Is the workplace the most segregated based on party in America, or is this in line with other places?

Chinoy: Yeah, so it’s hard to answer this directly for every other social environment or every other group of people. I can tell you a couple things. So one is: I think a natural comparison is residential partisan segregation. This is something that people study a lot, right—the extent to which Democrats live on the same block as Democrats, and Republicans live next to other Republicans. And so we can sort of compare what I told you—that 10 percent number, that overexposure ratio—against partisan segregation across neighborhoods.

And you can define neighborhoods in different ways. One way to do it is a zip code. And when we do that, we find that partisan segregation at work is pretty similar. So, like, a little bit less than but overall pretty similar to partisan segregation across zip codes. We can go one step further and say, you know, maybe the zip code is a little bit bigger than what you have in mind when you think of neighborhood-level sorting. And so we have individual addresses in our data, and so we can say, you know, You have 15 co-workers. Let me figure out how many of them share your party affiliation, and let me look at our sample of the 15 people who live closest to you and figure out how many of those people share your party affiliation.

And when we do that, we find that workplace-level segregation, workplace-level overexposure ratio is a little bit less pronounced than that sort of nearest neighbor level of segregation, but still pretty similar, not so different. It’s not orders of magnitude different. So that’s kind of why we say that it’s a little less pronounced than residential segregation as a whole but still pretty sizable.

This isn’t in the paper, but we can also look at colleges. That’s the other thing that we can really observe well in our sample, and when we do that, we find that colleges are less segregated along party lines than our workplaces.

Demsas: Wow.

Chinoy: And sorry—that’s college cohorts.

Demsas: Wait. Sorry. Can you break that down? College cohort—you mean, the people who went to your college and then are in the class of 2017 as well?

Chinoy: Exactly. Yes.

Demsas: Okay, so that group, the people who went to my college and are in the same class as me, are less segregated than my workplace? Well, maybe not me, in particular, but on average.

Chinoy: Yeah. And I think a lot of that is just the size of these groups. College cohorts are quite big compared to workplaces, which tend to be relatively smaller. And so there’s a little bit more room for that kind of political diversity in college cohorts. And so the extent to which you think that’s an apples-to-apples comparison, I think it is up for debate because of that size issue.

Demsas: So you’re not going to take the hard position that colleges are more open than workplaces in America? (Laughs.)

Chinoy: I wouldn’t say they’re more open, but certainly you’re in this group of people that, for many people, is quite large and might include people from diverse geographic backgrounds. That’s also something that happens at colleges.

Demsas: So is this a function of income or racial or gender segregation? Like, how much of this can be explained by the fact that our workplaces are segregated by factors that are correlating with partisanship but are not partisanship, in particular?

Chinoy: Yeah, that’s a great question, I think a natural question. I think it is important to note, though, that overall, like, what is the phenomenon of interest? It’s partisan segregation without differencing out all of those other background characteristics, right?

And I think that there’s an analogy to gender segregation at work. You know, to what extent is gender segregation at work driven by different occupational choices? The different occupations that men and women sort into or are sorted into—that’s sort of an interesting question. At the end of the day, that’s part of the phenomenon of interest. That’s part of what creates segregation at work. And so I think a similar thing applies here.

That said, we can do, I think, the kinds of exercises you have in mind, where, instead of benchmarking just against the share of Democrats and Republicans in your local labor-market area, in your commuting zone, we can additionally incorporate information about those co-workers in predicting their partisanship.

And so what I mean is: If we knew not just where your co-workers lived, in terms of which commuting zone they live in, but also their exact year of birth and their gender and their race—things which are, as you know, very correlated with partisanship and politics in the U.S.—would we still be surprised that Democrats disproportionately work with Democrats, and Republicans disproportionately work with Republicans? So these are pretty fine predictors, right? We actually interact [based on] year of birth and gender and race. So for me, you know, an Asian male born in 1995 tends to be registered with the Democratic Party at a particular rate. We can incorporate that information and say, Is it still the case that we see this partisan sorting?

And we find that, indeed, that explains some segregation but certainly not all of it. And we can add even more predictors, so not just the education level of everyone, whether they went to high school or college or have a postgraduate degree—again, something that’s highly correlated with partisanship—but also the exact college that they went to. And we can show there are partisan differences across schools.

And we can incorporate that information as well. We can incorporate not just the exact college that you went to but what you studied when you were there. And there, again, we see large gaps in the college major choices of Democrats and Republicans, which I think actually is independently quite interesting also. So college and major and then industry and occupation—we can incorporate all of these predictors, and we still find that a Democrat or Republican’s co-worker is about 4.3 percent more likely to share their partisanship than we would expect. So we bring that ratio down from 10 percent to 4.3 percent. All of these things clearly matter, but they don’t explain all the segregation that we see.

Demsas: I think that’s really significant. I think when I first saw your abstract, I was like, Okay, well, is this just like, Black people are Democrats, and women are Democrats, and men are Republicans, when we’re looking at averages?

And seeing that significant difference even without that—and I mean, I take your point well that looking at partisanship is relevant, even if it is the case that race and gender are playing into that. Like, that overall partisanship still tells you something about workplaces in America.

But I also want to ask, because I think in your paper that you’re seeing more heterogeneity for different income bands and educational attainment, that there’s a different level of partisan segregation for people who make more money or for people who have, you know, graduate degrees or college degrees.

Can you tell me about that? What’s going on there?

Chinoy: Yeah, so that’s exactly right. You know, the 10 percent number that I was quoting for you before is an average across everyone in our sample. We can see what that looks like among subgroups and, in particular, we can see what that looks like among subgroups defined by education and by income.

When we do that for education, we see something pop there, which is that people with postgraduate degrees, people who are more highly educated, tend to be in workplaces that are more segregated. And there’s a little bit of something going on for high-school graduates versus people with bachelor’s degrees, but really where it tends to stand out the most is people with a postgraduate education.

Demsas: It’s you, Sahil. You’re causing all our problems.

Chinoy: (Laughs.) I mean, yeah, like, kind of, though, right? And you can think of stories why this might make sense. Maybe these people have more of an ability to choose an employer that really aligns with their ideological interests in a way that isn’t true for other groups of workers. I can’t say for sure why.

Demsas: Or they’re more motivated, right? Like, you might be more ideological or partisan.

Chinoy: Totally. Also true. And, actually, on that point, when we subset to people who have made campaign contributions and might be more politically motivated or politically interested kind of in the way you were describing, we also see that those people are experiencing more segregation at work, particularly the people who donate to very liberal or very conservative candidates.

And then you also asked about income. And here we see a little bit less of a clear pattern, actually. So the gradient seems more pronounced for education than for income. There’s a bit of a technical point here, which is that we don’t know someone’s exact income in the LinkedIn data. You don’t put them on your LinkedIn profile, mostly. So we infer it from where people live, based on the block group that they live on, and so you might worry that’s sort of an inexact measure of income, but the education measure we have is more specific. We try to do some things to alleviate that concern.

Overall, we stand by the idea that the gradient is stronger for education than for income.

Demsas: But for income, higher-income people are more likely to have a more-segregated workplace?

Chinoy: Barely, among our sample. And our sample is people who have LinkedIn profiles, and so that’s a higher-income slice of the population than the overall workforce. And among that sample, we don’t see too much in terms of the highest-income people among them experiencing more segregation than the lowest-income people.

Demsas: This is a bit afield from your specific paper, but I remember there being a lot of talk about how diverse workplaces were more creative, and I think that literature is actually kind of more mixed, so I don’t know how good that literature actually stands up. But there’s a lot of talk about how having kind of ideological diversity, background diversity, etcetera can make for more creative teams. Does your research look at whether these sorts of workplaces, you know, have any impact on productivity? Do you have thoughts on whether that would play out, given other research you’ve looked at?

Chinoy: Yeah, it’s a great question. I think that’s the next paper I want to write.

Certainly, there are countervailing forces here. It’s probably bad for, you know, workplaces to have 100 percent people who think a certain way. That seems not optimal. It also seems like you probably want to be able to get along with your co-workers to some extent. And, you know, if partisanship and political affiliation is a measure of that, then, probably, a little bit of homophily might actually be productive. So my speculation is that there would be a bit of a U shape there. I don’t know for sure. I think that would be super interesting to study.

I think that where people do study this question, specifically, is among corporate leaders. It’s been, like, historically, a little bit easier to get information about the political affiliation and donation behavior of executives and board members, and so people have focused on that. There is one paper that basically claims that increasing political polarization of corporate America is not in the financial interest of shareholders. I’d have to remember exactly what they study in that paper, but I think they’re looking at the alignment between corporate executives and their boards, the political alignment, and looking at what happens when they leave.

Demsas: Yeah, we can put that paper in show notes for people to take a look at if they want.

There’s another paper—also, we’ll put that in the show notes—from Christopher Rosen last January [2024], and they found that employees experience negative affect after overhearing political conversations at work. Essentially, the effects are amplified when employees think their co-workers are less similar to them. So you’re more negative when you overhear someone who’s a Democrat, and you’re a Republican having kind of a conversation. And they’re attenuated when you overhear someone who has your viewpoints or you feel like it’s aligned with your ideological or partisan goals.

And so that seems pretty straightforward there, and I agree, these countervailing forces here feel difficult to sort out, particularly because an individual firm’s goal might be to increase the amount of good feelings that people within their company feel, but an industry or our goal as a society to try to create the most productive companies might be to have a lot more frictions happening in the workplace for the societal benefits that might bring.

It’s also like, the incentives are also countervailing here. There’s not really an incentive from workplace leadership, maybe, to try and make their workplaces more diverse in ideology, which I feel like is why there was such a push to try to find productivity benefits from ideological diversity—to try to incentivize this kind of corporate shift. But it seems rough.

Chinoy: I think that’s a good point. And I think the other thing I would add is that the conversation we just had is kind of focused on the interests and the efficiency and productivity of companies and workers. We also might have a social interest in partisan mixing and people who don’t think the same way politically interacting with each other.

Again, this is the kind of thing that, on its face, seems right. Like, we probably want people to interact with people who don’t think like them. Actually saying why that is good, politically, is not terribly obvious. Is it going to reduce support for, like, political violence or things like that? Probably not.

I think people have shown that people don’t generally believe in that kind of thing anyways. But you know, the extent to which I think mixing between Democrats and Republicans is good for our politics, I think that’s sort of another reason to be interested in this issue.

Demsas: Yeah, I want to emphasize for listeners, we’re not saying that, like, all these workplaces—and you’re not finding that all these workplaces—are 100 percent Democrat or 100 percent Republican. It’s just more likely to be. And so people might look around and say, I know the conservative at my job, and it’s like, Yeah, you know the conservative at your job.

So I think what you just said kind of segues into another finding in your paper, which is that there’s a persuasive aspect to this too. Just to tell you my prior, I feel like if I was constantly surrounded by very right-wing people at my job, I would probably only become more left-wing. But I do think that maybe your paper indicates that that effect is not the same for everyone—or maybe I’m just wrong about myself. Maybe I would be persuaded. But tell me about that finding. What did you see?

Chinoy: Yeah, so the story there is mixed. I don’t think what you’re saying is wrong about yourself. So the idea here is: What could explain political segregation? Well, one channel that could explain political segregation is sort of this conformity effect. People become like their co-workers, like their workplace over time. If I end up in a workplace with a lot of Democrats, I might be more likely to affiliate with the Democratic Party, and sort of vice versa with Republicans.

This has been shown, actually, with neighborhoods, and so people tend to adopt, to some extent, the partisanship of their neighbors or the people that they live around. And so we were interested in whether something similar could be happening at work. I’ll spare you the details of exactly how we estimate this, unless you want me to get into it, but the basic finding is that we find that the workplace can causally affect people’s partisan affiliation but only for people who don’t start out as committed Democrats or Republicans.

And so you’re not really getting people to change their mind. I think that’s kind of consistent with, perhaps, the story that you were telling about yourself. But people who start out as either independents or who start out as not registered with a particular political party, we find that moving to a workplace where the co-workers are more Democratic or more Republican tends to make those individuals more Democratic or more Republican, on average.

So there is some evidence of a little bit of an effect of the workplace on an individuals’ partisan politics or party affiliation. It’s not as big as in the case of neighborhoods, and so it seems like this channel has less power to explain the segregation that we see.

And in particular, the timing of this is kind of interesting. It looks less like the case that people switch to a new workplace and then adopt the politics of that workplace, and rather the case that people update their own party registration and then move to a compatible workplace, a co-partisan workplace. And that’s what kind of leads us to think, like, maybe it’s less the case that people are picking up the politics of their workplace and more the case that people are selecting jobs or workplaces, in part, based on politics or things correlated with their own party affiliation. And that’s the direction that we go in the paper.

[Music]

Demsas: After the break: how firms use partisan language to appeal to Democratic versus Republican job seekers.

[Break]

Demsas: What is driving this, I think, is a very useful thing to spend some time on now. I could theorize a bunch of different streams by which partisan sorting shows up, like word of mouth and recommendations, or it might be driven through partisan networks, or Democrats are more likely to be academics, and Republicans are more likely to be petroleum engineers or business owners or whatever. And when you’re able to drill down into how people are sorting, what part of the employment timeline is this actually coming up in?

Chinoy: Yeah, that’s right. So it’s not a straightforward answer, in the sense that certainly it’s the case that we can see in our data that Democrats and Republicans are choosing different schools and majors and occupations and industries. And so, clearly, all of that matters. It sort of limits the available workplaces and the kinds of people that you could even possibly interact with at work. That is something we can account for statistically when we measure segregation. I kind of described how we did that earlier, and we still find that there’s residual segregation.

So what is explaining that residual? There are a couple of different ideas. And I think the two probably main ones are workers selecting partisan or compatible workplaces, or it’s some kind of employer-discrimination channel, where employers are hiring people of a particular party or want things correlated with a particular partisanship, partisan identity.

And we focus on worker selection in this paper, kind of for the reason that I mentioned, that suggestive timing of when people are moving to co-partisan workplaces after sort of updating their party registration. And we focus on the worker-selection channel. And we try to say, you know, Is it the case that workers are actually selecting jobs based on something related to their political identity and something related to how they perceive the politics of the company?

We do this in a survey, and sort of the key question, I think, to begin studying this is, you know, What do workers actually know about a company when they choose whether or not to apply for a job there? It could be the case that segregation is driven because Democrats, you know, want to work at companies with more Democrats, but, like, is that something you really know when you apply for a job? You don’t know that it’s 60 percent Democrats versus 40 percent or something like that.

And so to study this, we look at our big data set that we’ve assembled of all these companies and shares of Democrats and Republicans who actually work there. And we look at how these companies are signaling. We look at the language that they used to describe themselves, and we see how that correlates with partisanship, with the shares of Democrats and Republicans who are actually at that company. And we actually find that there’s quite a bit of signal here, that the Democratic companies are advertising themselves in a way that’s quite different from the Republican companies, even within the same industry.

And a lot of the actual signaling language probably won’t surprise you. It’s words related to the environment and diversity and community for the Democratic companies, and sort of the absence of those for the Republican companies. But the fact that these signals kind of come through so clearly in our data kind of leads us to study the extent to which this can drive sorting. And I’ll pause there for a second, but I can tell you more about that.

Demsas: I would like to talk more about that because I saw the ideological signals and company descriptions, and this is on LinkedIn, right? So how are Democratic firms versus Republican firms describing themselves?

Chinoy: Yes, exactly. So, again, I want to emphasize this is all within industries. So we’re not just comparing, you know, nonprofits, which tend to have more Democratic employees, to, say, energy companies or oil-and-gas firms, which tend to have more Republican employees. This is saying, Take two firms within the same industry. Look at the text that they use, the words that they use on LinkedIn to describe themselves. And we find empirically that there are these words that are quite correlated with the partisanship of the employees.

And again, it’s a lot of the kind of bundle of things related to ESG practices and things related to diversity initiatives and things that are related to more subtle, perhaps, things, like, We’re a company that really emphasizes community and teamwork among our co-workers—that tends to be empirically more Democratic—versus, We’re a company that really emphasizes customer service and efficiency and excellence. That tends to actually be more correlated with companies that have more Republicans, which maybe wasn’t necessarily obvious to me.

Demsas: Yeah. I saw this other paper come out recently by Erika Kirgios and her co-authors that looks at whether communicating measurable diversity goals attracts or repels historically marginalized job applicants. It’s a bit orthogonal to the broader conversation, but I think it plays into this part of your paper quite well.

They look at whether “adding a measurable goal to a public diversity commitment,” like, instead of, quote, “We care about diversity.” You might say, like, We care about diversity and plan to hire at least one woman or racial minority for every white man we hire. And they look at whether that impacts application rates from women and racial minorities. They find that it increases application likelihood among those groups by 6.5 percent, without sacrificing candidate quality. Interestingly, it’s mostly driven by white women. I’m not even sure that the racial-minority finding is statistically significant, though they do find that it’s positive.

I think about this in relation here to whether there are different subgroups that are more motivated to find a job with more of their co-partisans at work and how that changes with racial and gender—different subgroups. I don’t know if you have thoughts on that.

Chinoy: Yeah, that’s interesting. There’s a lot of interesting work studying how these kinds of job ads affect who applies. The other big one I alluded to before is about ESG practices. And there’s another case, I think, where you can think of ways to make that, like, verifiable. You could say that this company actually has some particular ESG designation.

And I think what is maybe interesting about our survey and our paper is that we actually aren’t signaling anything that is explicitly verifiable. There’s no stamp associated with, you know, a company that is more pro-Democratic or more pro-Republican. And yet, this sort of matters. And yet, job seekers clearly seem to pick up on these things and care about them.

Demsas: I think someone listening to this might feel like, Okay, is this just a function of this current moment right now? Like, overt partisan politics in the workplace is much more commonplace in recent years. And this prevailing narrative about, like, Politics shouldn’t be discussed at work. You know, Politics, religion—you know, leave that outside the workplace. That’s kind of an older view of the workplace.

When exactly were you conducting this? And do you have any sense of whether or not this is just, like, a 2017–2022 moment?

Chinoy: Yeah, it’s a great question. So to answer the question, our LinkedIn data is a snapshot from 2022, and our voter-file data, which we’re kind of using to track how people’s party affiliation changes as they move from workplace to workplace, starts in 2012. And so it’s covering, you know, a more recent time period, for sure.

The question of, Can we measure how this is changing over time? I think it is super interesting and a little bit hard, in the sense that you can see in our LinkedIn data, where everyone was working in 2010, but then you worry, Who are the kinds of people who have gone through and listed where they worked in 2010? And so you worry about selection, and so I find that kind of a hard question to answer.

I think that there’s suggestive stuff. So, you know, if you ask people in surveys if they’re willing to leave a job over political differences, you’ll find that it’s the case that young people are much more likely to say that. Now, was that true in 1962? I’m not quite sure. But that sort of points in that direction. You find that in other countries—in Brazil, for example—that this kind of political assortative matching has been increasing over time. You find that among corporate boards, again, this kind of thing has been increasing over time.

And so I think there are a lot of sort of suggestive indications that this might be something that is more pronounced today than it was a couple of decades ago. It’s really hard to say for sure, though.

Demsas: Yeah. It’s funny, too, because part of what’s happened over this time period, at least in the United States, is that our parties have become much more sorted on ideology. And so in the 1950s or whatever, there were a lot more conservative Democrats and liberal Republicans, and that has changed significantly over time. And now most people who are ideologically liberal have sorted into the Democratic Party, so it becomes kind of difficult to measure this if you’re looking at just partisan measurements. Like, maybe there was more partisan diversity at workplaces in 1962, but ideological diversity was still really low, and people were still sorting. So I think there’s quite a difficulty with measurement there.

Chinoy: That’s a good point. It makes me sort of think of one other point, which is that for a smaller set of our sample, about 10 percent of our sample, we can measure their donation behavior. And so there, we can actually look at sort of a within-party measure of sorting. We can say, Is it the case that the more liberal Democrats, as measured by who they’re actually donating to, are sorting into workplaces with more Democrats, and vice versa for Republicans? And there, we also find pretty strong patterns. So there is an extent to which this exists even within party.

Demsas: Another question I have is about, like, obviously 2022—pretty tight labor market. So workers had tons of choice and ability to sort based on a bunch of different amenities. And I wonder if you think that this kind of sorting happens less in a high-unemployment environment. So, you know, God forbid, when there’s a recession at some point, or there’s a period of high unemployment, do you expect this kind of ideological sorting to go down?

Chinoy: Yeah, so I think the answer is yes. And I think that, again, that would be a pretty cool follow-up paper. I think that’s something that we can probably study directly in the data that we have.

I think that one piece of evidence here is, you know, how important are these kinds of what we call “ideological amenities” or “partisan amenities”? How much are these characteristics about a job—how much do workers value them, relative to other things that they might care about in a job? Our survey is designed to precisely measure the quantitative trade-offs people would make for these kinds of ideological amenities, you know, trading off against wages. It turns out to be about 3 percent of their salary.

Demsas: (Laughs.) That’s wild.

Chinoy: Is that big or small? I think it depends on your priors. But, you know, it’s certainly way smaller than what people would pay for health care or, you know, some of these sort of more—

Demsas: How do you measure that? How do you know someone’s willing to trade 3 percent of their salary?

Chinoy: Yeah. So this is kind of what I was getting at before. We pick up these ideological signals in the way these companies describe themselves. We use them to generate synthetic job ads. We want to ask workers in a wide range of occupations and industries about these different kinds of jobs. How do we do that without me sitting down and writing, you know, 10,000 job ads?

This turns out to be exactly the kind of thing that ChatGPT is good at, a large language model is good at. We can give it these kinds of ideological signals that we find, in our data, are correlated with companies with more Democrats and Republicans. We can give it a particular occupation and industry, and it’ll come back with a job ad that does emphasize these signals or doesn’t emphasize these signals, and then we ask workers about them in an online survey.

We ask them to explicitly make choices between these companies that are framed in different ways, and we vary the wages associated with these job ads, and that’s how we can sort of capture the strength of this trade-off. And so that’s where we get this 3 percent number. Is it big or small? It’s less than something like health care. It’s sort of actually comparable in magnitude to some of these softer amenities, things like having a relaxed versus a fast pace of work, for example, or having training opportunities at work.

People seem to care similarly about the ideological nature of the job. Of course, the difference is that our ideological amenities are precisely designed to split Democrats and Republicans. You know, Democrats care about the liberal one, and Republicans care about the other one. Whereas, Democrats and Republicans care similarly about, say, a relaxed pace of work. And so those other amenities can’t generate segregation, but the stuff that we study and design actually can generate segregation.

Demsas: I’m not surprised that people would trade off a little bit on wages in order to feel more comfortable at work with their ideological co-partisans. But I wonder if you were to tell people, Hey—your revealed preference is that you would sacrifice, like, X thousand dollars a year. Do you actually want to take that trade? With remote work, for instance, they’re doing these experiments now where people are like, Yeah, I will take a pay cut in order to be able to be fully remote. I wonder if people would explicitly say, Yes, in order to be at a more Republican firm, I will give you $3,000. I wonder if that’s a self-conception problem that we might run into if you made that explicit.

Chinoy: Yeah. So certainly we’re asking people in the survey to kind of make these trade-offs explicitly. You know, it’s job A or job B, and it’s $3,000 or not. I will say, also, that in the observational data, we don’t know individuals’ wages directly.

Again, that’s the problem I mentioned. People don’t list their salary in their LinkedIn profile, but we do know something about where they live and their occupation and their industry. We know what college they went to. And so we can take similar Democrats and Republicans—similar in terms of their demographics and where they live, and in terms of what exact college they went to, which is a pretty good measure of education or perhaps labor-market skills—and find that the Democrats are consistently choosing occupations and industries that pay less than the Republicans. And so there’s certainly some evidence, or some suggestive evidence, that there’s some trade-off that people are making between fit with the workplace, or their job more generally, and the actual salary associated with that job.

Demsas: There’s Gallup polling from February of last year that asked about U.S. employees’ experience with political conversations at work. And conservatives were much more likely to say that they had a discussion with co-workers about politics: 60 percent of conservatives versus 48 percent of liberals. That is contrary to, at least, my expectations. I’d expect parity, or maybe liberals would be doing it more. I don’t know why I had that expectation, but I was surprised.

It makes me think that maybe there’s some sort of mobilization aspect happening here, if conservatives are saying, in 2024, that they’re having conversations with co-workers about politics, and then, all of a sudden, conservatives win a trifecta. I don’t know if that’s playing into it.

Chinoy: That’s interesting. That probably goes against my priors a little bit too. I think I would have expected liberals or Democrats to be having more of these conversations at work. That’s interesting.

I think that, certainly, studying mobilization—it’s actually not clear to me, right? If you’re part of the majority group at your workplace, and then everyone’s like, Hey, let’s go vote for our guy, for our candidate. Is that actually going to make you more likely to turn out? Or is there some sort of backlash effect if you’re a minority and you say, you know, I really hate all these conversations I’m having with my co-workers. I’m going to go try to vote them out of office, or something like that? It’s not super clear to me what direction that goes in. I think that it is a great question.

Demsas: I’m revealing a lot about my psychology in this episode, going, like, Well, if I had 60 percent people who disagreed with me, then I’m definitely gonna go vote, you know? So maybe that’s not the average experience for people. (Laughs.)

Chinoy: Well, to tie this back, again, I think we find these, like, pretty heterogeneous effects on partisanship for people who start out as committed, versus not. And so I think there’s some sense in which maybe people who are younger and who are susceptible to political influence might adopt the politics of their workplace and perhaps turn out, and then people who already have a particular ideological stance or particular partisan attachment might be motivated to turn out as a backlash against the prevailing politics of the workplace. I’m not sure. I think that’s an interesting question.

Demsas: So we mentioned a couple times—I mean, you’re on the job market right now. You’ve mentioned academia a bit. I mean, have you seen any of this playing out in your own field? Like, this kind of sorting?

Chinoy: Yes. And I think that one fascinating thing, I think, is the sorting across college majors, which is something that we can see—sorting across colleges but also across college majors. And we can see this explicitly in our data. It turns out that economics is pretty much in the middle, which, when I tell economists, makes them very happy that it’s a discipline that doesn’t necessarily lean so far one way or another.

But certainly, higher education leans to the left in our data. Certainly, elite colleges lean to the left in our data. Certainly, many academic disciplines lean to the left in our data. And so I guess for lack of a more sophisticated answer, if you’re looking for a place with a good deal of partisan segregation, looking at universities is not a bad place to look.

Demsas: The mechanisms are interesting because you have this self-sorting. You lean a lot on people choosing these sorts of majors that are kind of correlated with their partisan identities or may help shape their partisan identities. And then they choose workplaces and things like that, and colleges, and down the line, etcetera.

But is there any impact that you can find on the employer side of selection? Like, I don’t know if you’re experiencing this at all, too, but there’s some level to which, when you’re in a job interview, they’re trying to suss out if you’re a good fit for the company. And part of that fit, I assume, might be ideological or partisan.

Chinoy: I think that’s absolutely right. And so I think that just isn’t the main mechanism or the main channel that we study in this paper, honestly, because we have to choose something. And so we focus on the worker side. Again, there’s evidence—from Brazil, in particular, there’s a paper looking at employer, you could call it, discrimination. There are audit studies in the U.S. looking at callback rates for résumés that signal whether you’re a Democrat or Republican, and there’s some evidence for that as well. So yes, I do think that kind of employer-selection story is certainly part of what’s going on.

Demsas: I think your focus on the employee side is actually really interesting, because I think it raises questions about allowing this kind of free choice, how that can lead to, maybe, societally suboptimal ends. There’s a new paper in the American Political Science Review from Jon Green and several of his co-authors that looks at demand for echo chambers.

And we think about echo chambers, and we’re like, Oh man, social media. It’s such an echo chamber. We’re talking about it as if it’s kind of imposed on us. And their intro of that paper has something interesting. They argue that “networked curation processes lead information consumption on social media in particular to be more politically homogeneous than [this] empirical literature has thus far suggested. However, this is more a reflection of democracy than a threat to democracy—a product of individuals engaging with information, and each other, on their own terms.”

Essentially, people are choosing to follow certain people. They follow creators. They follow influencers. They follow their friends. They follow people that make them feel good about themselves. There was this big outrage recently. I don’t know if you noticed—people were following the VP account on Instagram and then were shocked to realize that they were now following J. D. Vance, and now a mass unfollowing happened. And it’s like, you had curated your Instagram feed to be people you wanted to follow, and all of a sudden you see, like, J. D. Vance being inaugurated on your feed, and you’re like, How did I get on here? What’s going on?

And it’s an interesting question about—in previous generations, people went and they bought a newspaper, and you couldn’t just choose to take the parts of the newspaper that you wanted. You had to take it all. And you don’t do that anymore. So I don’t know if you have thoughts on that. Or should you want to change this, are there even ways to change this?

Chinoy: Yeah. I think that’s a really good point and interesting question: Is partisan segregation bad? Should we be worried about it? I think it is a very important, interesting question.

I will note that when labor economists study racial and gender segregation at work, they have a different set of motivations in mind. They have equity motivations in mind. These are protected categories. We really are worried, in particular, about differences in pay between groups doing the same work, whereas I don’t think we have the same equity motivations for being worried about Democrats and Republicans at different workplaces.

Demsas: DEI for conservatives in the academy is a very controversial conversation. (Laughs.)

Chinoy: Exactly. Yeah. So without going there, I think that we have different motivations to study partisan segregation at work versus these other forms of segregation.

I think that—and this is kind of getting to a conversation that we had a little bit earlier—it’s probably good that people get to do what they want and put themselves in workplaces where they feel happy and where the organization kind of aligns with their goals. It’s probably good that people work with co-workers who they get along with. It probably makes them, to some extent, more productive. Does it make the actual firms more or less productive? I think that is an open question, and certainly one that factors into this calculus about whether we think this is ultimately helpful or harmful.

And then, of course, I think the other really hard question to answer, which we talked about before, is: What does this do for democracy generally? Should we think that it’s bad that this place where we thought that partisans might be mixing more than other environments actually isn’t going to provide that kind of kind of mixing? What are, exactly, the consequences of that lack of contact between people who don’t think the same way? I think it is a hard question to nail down. I think we have this intuitive sense that probably it’s not so good if we really segregate ourselves politically. But actually quantifying or measuring and thinking about, What are the effects of that? I think is still an open question.

Demsas: One note of hope I might relay here is that—I thought about this in the context of my job, which is, obviously, not the average job in the United States, but I come into contact, in the context of my work, with people who don’t work here, all the time.

So for instance, I might come into contact with people who I’m interviewing, who are different from me, when I’m walking down the street, doing man-on-the-street interviews. But if I also conceptualize other jobs—if you’re in the service industry and you’re a restaurant worker, maybe all your co-workers behind the bar are on the same team as you, but you’re serving customers and talking to them and interacting with them, and that may also lead to a lot of that cross-partisan contact.

I think it’s both difficult—impossible, maybe even—and undesirable from a business perspective to be able to even do that sorting. Obviously, at some level, businesses do this, right? Like, if you have a rainbow flag in the window or something, you’re signaling to people. But, you know, in general, most jobs force you to interact with people outside of your workplace. And that sorting may happen much less in that context. So you could think of, like, your workplace as your home, versus, you know, when you go outside, and then you’re like, Okay, well, I’m interacting with people who are different than me, but I have a place to go back and, you know, dish with my co-workers about how rude they were.

Chinoy: Yeah, so I think that studying the extent to which different occupations interact with customers or with the public and whether that sort of has some bearing on these effects on political views, I think would also be interesting. When they say the workplace is a context for this kind of cross-cutting discourse, I think what they usually have in mind is, like, with fellow co-workers. But certainly, you’re right that those aren’t the only people that you interact with in the context of work. And so that would be super cool to study.

Demsas: Well, that’s a great place for, I think, our final question, which is: What is an idea that you once thought was a great one but ended up only being good on paper?

Chinoy: So I thought about this a bit, and if you’ll forgive me, I think I’m going to mention another academic paper, which is related but not exactly the same. So one thing that I’m super interested in, as someone who’s interested in politics and demographics and data, is the extent to which these demographic characteristics, some of which we’ve been talking about, are really predictive of politics and party affiliation and things like race and gender and age.

And I think what is tempting, then, is to say, There are these strong correlations that exist between politics and demographics. We know something usually about demographic trends in the U.S., whether a particular racial group is growing, whether people are becoming more educated, on average, or not. And so using that to make predictions about what’s going to happen to politics and to elections, I think, is really tempting.

This is the idea that, you know, people are becoming more educated, on average, and more-educated people tend to vote for Democrats, and so the Democrats are going to do better in the future. There are various versions of this argument, and it’s quite tempting to make, but it turns out it doesn’t really work.

There’s a paper by one of my advisors, Vincent Pons, as well as Jesse Shapiro and Richard Calvo where they test this. So they look at the correlation between politics and demographics in a particular election. They say, If these correlations were the same in the next election and we sort of just tracked the evolution of demographics from election to election, how good would that prediction be? And it turns out that it’s quite bad. It’s sort of worse than just guessing that it’s gonna be 50–50, Democrat or Republican.

And I think that sort of goes to show that—it’s kind of interesting that these demographic correlations are so strong in the moment. But also, these trends are kind of slow moving, and politics responds kind of quickly, and parties respond to where they see their electoral advantages.

Demsas: Demographics are not destiny.

Chinoy: Yeah, I could have just said that, and I think I probably would have gotten the same point across. But this is a longer way of saying that.

Demsas: No, it’s great. We’ll put the papers in the show notes as well. But thank you so much, Sahil. This was fantastic.

Chinoy: Thanks for your time.

[Music]

Demsas: Good on Paper is produced by Rosie Hughes. It was edited by Dave Shaw, fact-checked by Ena Alvarado, and engineered by Erica Huang. Our theme music is composed by Rob Smierciak. Claudine Ebeid is the executive producer of Atlantic audio. Andrea Valdez is our managing editor.

And hey, if you like what you’re hearing, please leave us a rating and review on Apple Podcasts.

I’m Jerusalem Demsas, and we’ll see you next week.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

Sometime on Tuesday evening, the USAID website was taken down and replaced with what looked like a beta page from the internet of the 1990s. There were no affecting photos of American government officials distributing food and medicine overseas. Instead, a box of text explained that nearly all USAID personnel would be placed on administrative leave, globally. With administrative assistance from Elon Musk, President Donald Trump seems to have wiped out the world’s largest donor agency in just a few days. It was a radical act, but maybe not as politically risky, in the domestic sense, as other plans in the grand project of dismantling the federal government. USAID has important beneficiaries, but most of them are not Americans and live overseas.

In this episode of Radio Atlantic, we discuss where Trump and Musk seem to be headed and the obstacles they are likely to encounter in the future. What happens when Trump starts to face challenges from courts? What happens when Musk goes after programs that Americans depend on, particularly those who voted for Trump? What new political alliances might emerge from the wreckage? We talk with staff writer Jonathan Chait, who covers politics. And we also talk with Shane Harris, who covers national security, about Trump’s campaign to purge the FBI of agents who worked on cases related to the insurrection at the Capitol.

“I think that will send a clear message to FBI personnel that there are whole categories of people and therefore potential criminal activity that they should not touch, because it gets into the president, his influence, his circle of friends,” Harris says. “I think that is just a potentially ruinous development for the rule of law in the United States.”

The following is a transcript of the episode:

Hanna Rosin: Today is the deadline for some two million federal employees to decide if they want to type resign in response to the now infamous “Fork in the Road” email. The email, of course, is one in a list of things that Elon Musk, empowered by President Trump, has been doing in order to “disrupt” the federal government.

Donald Trump: We’re trying to shrink government. And he can probably shrink it as well as anybody else, if not better.

Rosin: For example: gain access to the U.S. Treasury’s payment system—

News anchor: Treasury Secretary Scott Bessent reportedly granting Elon Musk’s DOGE team access to the federal government’s payment system, which handles trillions of dollars in payments.

Rosin: —dismantle USAID, of which Trump is not a fan—

Trump: And we’re getting them out. USAID—run by radical lunatics.

Rosin: —and neither is Musk.

Elon Musk: If you’ve got an apple, and it’s got a worm in it, maybe you can take the worm out. But if you’ve got actually just a ball of worms, it’s hopeless. And USAID is a ball of worms. There is no apple. And when there is no apple, you’ve just got to basically get rid of the whole thing.

Rosin: All of these efforts are unusual, maybe even unprecedented, norm-breaking—even for Trump. But are they unconstitutional? And could they fundamentally change the character of the country?

This is Radio Atlantic. I’m Hanna Rosin.

[Music]

News anchor: At the FBI, some agents have started to pack up their desks as fears of mass firings grow.

Rosin: In the second half of the show, we’re going to focus on a special case inside the government, which presents a different set of potentially history-changing problems—the FBI—with staff writer Shane Harris.

But first, we are going to discuss what’s at stake, more broadly in this overhaul, with staff writer Jonathan Chait, who covers politics for The Atlantic.

[Music]

Rosin: Jon, welcome to the show.

Jonathan Chait: Thank you, Hanna. I’m delighted to be here.

Rosin: So, Jon, of all the unorthodox things that Trump has authorized Elon Musk to do with the federal government, which one strikes you as pushing constitutional limits the most?

Chait: Attempting to eliminate or cut spending for agencies that have been authorized by Congress. This is just a totally revolutionary step in terms of the structure of our government. And it’s kind of shocking, to me, how far he’s been able to go, and how much permission he’s received from the Republican Party.

Rosin: And is there another time in history when a president tested this limit between what Congress authorizes and what the president can do with that? And how has it worked out in the past?

Chait: That’s a great question. You had a struggle with Andrew Jackson over the Bank of the United States. That was a real constitutional struggle between him and his enemies as to how much power the president had vis-à-vis Congress and whether the president had just total authority to do what he wished. And Andrew Jackson was sort of known for pushing the boundaries of the office to or past their limits, and saying if the Supreme Court ruled against him, he would just do what he wanted, anyway. He did the same thing with his attempts to ethnically cleanse Native Americans to take their land. He just fundamentally didn’t care if he had authority from Congress.

That’s the kind of struggle we’re, I think, heading into right now. And Richard Nixon tried a smaller version, I think, of what Trump is doing now. He basically said, Congress has authorized certain kinds of spending, and I’m just going to impound it. But the Supreme Court ruled against him, and Congress passed the Impoundment [Control] Act that formalized the fact that Congress has this authority, and the president doesn’t, and if Congress authorizes spending, with very limited exceptions, the president has to carry it out. And if the president objects to certain forms of spending that Congress enacted, he has to persuade Congress to pass a law to change it.

Rosin: Got it. Okay. So that’s the line we’re working with. So it’s the Impoundment Act. It’s been defined by the Supreme Court. Can we talk about examples of, say, how far an administration can go in resisting a previous administration’s policies, but not pushing against this constitutional line? What would be something we’ve seen before? And what would prompt what people would refer to as, say, a legal or constitutional crisis?

Chait: Just in the big picture, the executive branch has been asserting more and more authority, over decades, as Congress has gotten more and more dysfunctional. The use of the filibuster has risen. Congress has gotten less and less able to fulfill its constitutional obligation to really direct national policy the way the Constitution imagined it. And so the executive branch has really kind of filled in this gap in a lot of ways. So you’ve seen presidents of both parties creatively exerting their authority.

You had Trump doing this with immigration, where he, you could say, couldn’t or just barely even tried to get Congress to fund the wall that he wanted. So he just basically redirected funding from the Pentagon to the border by calling it an emergency. And Trump is doing the same thing with tariffs.

Now, Congress basically ceded the president emergency authority to declare tariffs for various national-security emergencies, thinking that this would just be used in the case of something like a war or an international conflict, but it let the president decide what an emergency is. And so Trump can just say, well, an emergency is whatever he wants, and that’s on Congress.

And Biden has kind of pushed the limit in a lot of ways, I think most controversially with student loan forgiveness, where the executive branch has control over student loans, and so Biden just kind of forgave those loans on a kind of sweeping basis. Now, he was challenged legally. But when you’re in power, your party has a pretty strong incentive to interpret executive power in the most sweeping way.

So there’s a way in which both parties have really been engaged in this, but I really think what Trump and Musk are doing now has totally breached the walls of normal and is just turning the Constitution into a farce.

Rosin: Okay. So the reason that’s true is mostly because of appropriations? Because from what you’ve said, presidents are pushing this line constantly. So what are they doing that doesn’t just break norms or traditions, but actually is pushing into constitutional crisis?

Chait: Article I of the Constitution, which is really just, like, the guts of the Constitution, says that Congress has authority over spending.

So Congress establishes an agency. Congress sets its spending levels. And throughout our history, with the exception we’ve described for Nixon, which was slapped down, the presidents have to follow that because that’s the law, right? Now, the president has a role in that. The president can veto some of these laws. If Congress proposes spending that the president doesn’t want, the president can veto it, and then Congress can override it, or Congress can make a deal with him. But whatever emerges from that is the law, and the president has to follow the law.

Rosin: Okay. And does the Trump team have any creative arguments for how to get around this Impoundment Act?

Chait: So far, Elon Musk is just operating in this totally chaotic legal gray zone. So his first target has been the United States Agency for International Development. And one thing they’ve made this argument is that, Well, that was just established by an executive order by the president, John F. Kennedy, 1961, so it can be ended by an executive order. The problem is: After it was established by executive rule, it was later established by Congress. Congress voted to make the United States Agency for International Development an agency.

So after Congress established the United States Agency for International Development, it had the force of law. And so saying, We’re going to eliminate this agency, is just a violation of the law. It’s pretty simple.

Rosin: Okay. I can see the argument. So can we play out both scenarios? The first scenario is: The courts push back on Trump. You know, they enforce the Impoundment Act. They say, You cannot do this. You can’t end USAID. Elon Musk has to stop roaming around the federal government and making these decisions that violate this constitutional balance of power. What happens then? Does it call Trump’s bluff?

Chait: It might, but I wouldn’t count on it, for a couple reasons. Number one: Musk is moving much faster than the legal system can move. And it’s a lot easier to destroy something than it is to build something. So once you’ve basically told everyone they’re fired, and they can’t come to work, they can sit and wait for the courts to countermand that while they’re losing their income and their mortgage is going under, or they could just go find another job somewhere.

Rosin: I see. So it’s just, like, facts on the ground change, so that even if the legal reality doesn’t budge, you’ve already disintegrated the actual infrastructure.

Chait: You lose the institutional culture. You lose the accumulated expertise. And by the time the courts have stepped in, rebuilding it is difficult to do, even if the president wanted to. And obviously, they’re not going to want to anyway. Second of all, it’s not totally clear that they’re going to follow the law, that the law has any power over them.

I mean, remember: Donald Trump established on the first day of his administration that he believes that people who break the law on his behalf can get away with it when he pardoned the entire—or commuted the sentences of the entire—insurrectionists, right?

Rosin: Yeah.

Chait: So Elon Musk knows full well that if he violates the law, Trump is going to have his back. So I think that’s also shaping the behavior of everyone involved in this episode.

Rosin: Right. So it sounds like you pretty strongly believe there is no brake to this. b-r-a-k-e. There is no stop to this. I was thinking that maybe the courts or something to, you know, put some hope in to stop this. But it sounds like no.

Chait: Well, in the long run, the courts can have an effect by saying, You don’t have the authority to eliminate this agency. It still exists, meaning that when the Democrats win back the presidency, if that ever happens, it’ll still be there, and then they can actually rebuild it.

Rosin: So in other words, in that scenario, there’s temporary dismantling, but the balance of powers remains in place, is affirmed by the courts, and things get slowly rebuilt.

Chait: Right. Although, you know, you’ve lost all your talent, you’ve lost your institutional memory, and then you’re probably rebuilding this agency from scratch.

And keep in mind, USAID is just the test case. I think they’re just picking on the most politically vulnerable agency. It deals with foreign aid, right? So most of the people affected by this right now are mostly living in other countries, who won’t get, you know, drinking water and food. And people are going to starve and die of diseases, but they’re not going to be Americans. They can’t vote, so they’re politically weak and vulnerable.

So that’s the target that they’ve picked to establish this principle that the presidency can pick and choose what spending is real and what isn’t. So then they’re going to start to go on to do domestic targets. But then, I think, once they’ve started attacking domestic targets, then they’re going to start dealing with political blowback in a way they’re not facing when they’re going after foreign aid.

Rosin: I see. So that’s a different political—so if that starts to happen, if we enter a period where you have people who have stake in this in the U.S., can you see any interesting alliances that could come out of that moment?

Chait: It’s really hard to see where they’re going, because Elon Musk is not proceeding from an accurate map of reality.

So to just explain what I mean by that, he said that he wants to cut—first he said—$2 trillion from the fiscal-year budget, from one year. Then he revised it down to $1 trillion. So right away, you know, when you’re just picking these random round numbers, you obviously don’t know what you’re talking about. But he said, like, basically, there’s a trillion dollars in just, you know, waste and improper payments—and there just isn’t. There’s nothing close to that by even the most expansive possible definition. So Musk thinks he’s going to just go through the budget and find waste, and just kill it and add up to a trillion dollars. And he’s obviously not.

So the question is: What happens when his fantasy starts to run into reality? Does he start to just attack social-welfare programs and end payments of food stamps and Medicaid reimbursements and programs like that to people? Does he realize that he didn’t know what he was talking about and he’s in way over his head? We don’t know how it’s going to go, but I think that is the question you’ve got to answer before you start to figure out what the politics look like.

Rosin: Right. And there’s also military budgets. Like, if you think where the giant spending is, you’re running up against budgets that will face a huge amount of resistance if you slash them in the way that he’s slashed other things.

Chait: Right. Yeah. If they start going after the Pentagon, I think you, obviously, cut pretty deeply into the Republican coalition pretty fast. I even think they’re probably starting to accumulate small amounts of domestic political targets with USAID, right? They cut off funding to a Lutheran charity, but, you know, those are midwestern religious conservatives who are operating those programs who are being targeted. Now, most of the money is going overseas, but you’re still hurting people in the United States of America. And I think that pain is going to start to spread more widely if they keep going.

Rosin: Right. Okay, so you’re describing a realistic scenario in which this whole operation does encounter resistance. There are many policy researchers—on the left, even—who have argued that the government does, in fact, need an overhaul and, more specifically, isn’t equipped for a digital age. Is there a chance that in all of this, you know, Elon Musk could usher in a more efficient, tech-friendly kind of government?

Chait: Yeah, well, that was the initial hope that some people who specialize in government reform were hoping for. Jennifer Pahlka is an expert in what’s called “state capacity,” which is just the ability of government to function and to bridge the gap between its ambitions and its actual ability to meet those ambitions.

And part of that is fixing the way government hires and fires people.

But the problem is: Elon Musk doesn’t seem to be interested in that in any way whatsoever. He’s just holed up with a bunch of engineers who don’t seem to have any expertise in government or state capacity whatsoever. And they’re just finding programs that people within this kind of right-wing bubble in which he resides think sound radical and just, you know, saying, Delete it! Delete it! and getting cheers on social media for it.

It’s just so completely haphazard. There doesn’t seem to be any interest in actually making the government, you know, operate better.

Rosin: Yeah. And I suppose Twitter did not become a better, more profitable, you know, smoother-functioning company after Elon Musk took it over. It just became a kind of tool of the culture war—like, an effective tool of the culture war.

Chait: Right. It became smaller, less profitable—jankier, but more conservative.

Rosin: Right, okay. All right. One final thing. So project far into the future. Let’s say that your blowback scenario is real. What political alliances can you see reforming? Like, if you had to predict a political realignment some years down the road that includes a reaction to everything that’s going on now, what does it look like?

Chait: Well, the Trump coalition has really been built on winning multiracial, working-class voters back from the Democrats—and those voters are disproportionately to the right on social policy—and they’ve exploited some of those progressive stances on social policy that the Democratic Party has adopted over the last decade, but they’re still relatively to the left on economics. Maybe they don’t believe in government, in the abstract, but in the specific, they really rely on programs, like nutritional aid and Medicaid, Obamacare.

And every time the Republicans have gone after those programs, their coalition has splintered. That was really a major element in killing George W. Bush during his second term. He decided to privatize social security, and that was a major cause of the decline of his popularity that made him politically toxic, along with the Iraq War and Katrina, social security privatization.

You know, you could see a version of that happening with Trump, but I wouldn’t take for granted that it’ll play out that way because we live in a different world in a lot of ways.

[Music]

Rosin: Thanks again to Jonathan Chait.

After the break: Donald Trump also has his eyes set on the FBI. We hear from The Atlantic’s Shane Harris about what that might mean.

[Break]

Rosin: Shane, welcome to the show.

Shane Harris: Hi. Thanks for having me.

Rosin: Sure. So the president asked the FBI to turn over the names of every agent who worked on the Capitol riots. What do you read into that request?

Harris: Well, I think you don’t even have to read that closely between the lines. You can just read the lines as they were sent in the order that we now have seen publicly, that went from the acting deputy attorney general, Emil Bove, of course, who had been one of Donald Trump’s lawyers as a private citizen, telling the acting director for the FBI, Look—we want the names of these people because they believe in the words that he has put, that they can no longer have trust that these FBI employees will implement the president’s agenda faithfully.

So what they are saying is that these are individuals who they don’t think are on board with Trump administration policies. And then of course, you know, we can do a little bit of inference, which is, you know, why would he go after the people who investigated January 6 and his role in it? Which was, by the way, the biggest FBI investigation in the country’s history. You know, these are the agents who interviewed and ultimately gave evidence that created the charges for the Capitol rioters—who were sent to prison, who Trump then later pardoned and who are now free—who investigated his own activity around January 6 and efforts to impede the transition from the Trump to the Biden administration.

So these are the FBI agents who did that case. And you know, what Trump is making very clear here is that, you know, he wants to identify them. He doesn’t trust them. He doesn’t trust the leadership that oversees them, and either wants them removed or moved, or we’ll see what the disciplinary action is. But some of them, he’s actually said he wants them fired immediately. He’s made pretty clear how he feels about these people and why he’s going after them, I think.

Rosin: Now, that must have landed in a very particular way at the FBI. You know the agency better than I do. As far as I understand it, I mean, you are assigned a case; you work on that case. So how have leaders in the agency responded to that request?

Harris: I think it’s been really interesting. I mean, there’s been this mixture from people I’ve talked to of: On one level, people are not surprised that Donald Trump went after FBI personnel, because it was expected that he would go after senior-leadership-level type people. I mean, he had essentially pushed out the FBI director, Christopher Wray, who—remember—became the FBI director when Donald Trump fired the previous FBI director, James Comey, in his first term.

But people were genuinely stunned by the scope of this demand to know the names of all of these agents who worked J6—and then there’s one other related case—because it’s, you know, potentially 4,000 to maybe even 6,000 personnel if you’re taking in FBI agents, analysts, people who play a support role.

But then something really fascinating has happened: There has been this—I hesitate to say the word defiant—but there are senior leaders at the FBI, including the person who is serving as the acting director right now, who essentially are saying, No, you cannot just fire agents for this reason, for no real cause. These people have protections under civil-service rules. They have due-process rights. And what’s more, some of the advocates for these folks are saying, Look—you can just read the plain language of the order that I just read to you and see that this is a retaliatory response, that what the president is doing is going after people because he doesn’t like their opinions or what they did.

As you pointed out, these thousands of agents didn’t pick to be on the case. I mean, it’s not like they raised their hand and said, Yes, please. I would like to investigate and prosecute Donald Trump. They were assigned these cases. So the leadership has actually really kind of dug in here, some of them, and essentially is saying, There’s a process for this. This isn’t fair.

Now, we’ll see how long they can resist the White House on this, but we’re seeing some real institutional pushback from the FBI, which personally, I think, is encouraging.

Rosin: I want to get more into the pushback, but I’m curious what we know about this group of agents. There’s a few thousand. Because, yes, I followed the January 6 cases. I know that it was the biggest investigation in history, but who are they? Like, if you think about losing these 4,000, is why I’m asking, what’s their expertise, and what do they generally do?

Harris: If we take that group of the J6 investigators, the agents themselves, these could be people who were pulled in from all over the country. So this could include agents that were investigating national-security-related matters, counterterrorism matters, transnational crime, narcotics. The universe of these agents, as you know, was so big because the case was so big and demanding.

Trump, though, has zeroed in, more particularly, on some individuals, including some very senior-level officials that have the title of executive assistant director, and he actually named some of these in this order. And those people were involved in things like, for instance, the Mar-a-Lago investigation, when Donald Trump took classified documents from the White House and stored them at his estate in Florida—offenses for which he was later charged under the Espionage Act.

Some of these people—one of them was the special agent in charge of the Miami Field Office, which participated in the raid on Mar-a-Lago. Others had supervisory and leadership positions on intelligence and counterintelligence matters. It was a counterintelligence squad at the Washington Field Office in D.C. that handled the Mar-a-Lago case. So, you know, he understands that there are people who, individually, separate from J6, worked on the Mar-a-Lago case, as well, and those people are being singled out too.

Rosin: Right. I mean, there are two things here. One is, we’ve talked about this in terms of other agencies, like USAID, which is: What vast institutional knowledge would you lose? So these people worked on individual cases, but also, they have a lot of expertise in counterterrorism. They just must have a large, you know, body of knowledge and experience that you could lose.

Harris: Absolutely. So let’s just take, for instance, the squad at the Washington Field Office that did the Mar-a-Lago investigation. They work in the counterintelligence division of the FBI. So when those folks are not investigating, you know, Donald Trump’s removal of classified documents, they’re looking at things like spies operating inside the United States trying to maybe steal government secrets or recruit agents in the United States. They’re looking at people who might be mishandling classified information. They look at people who might be leaking to journalists as well.

These are folks who work on highly specialized counterintelligence cases. This isn’t just something that you, you know, kind of step into, and on day one, you know how to do it. These are different kinds of tradecraft. They’re very sensitive. These people all will have high-level security clearances. They will have been vetted for these jobs. So folks who are in positions like that, when you eliminate them, you know, it’s not entirely clear to me that there is just then, like, a backup bench of people who can come in to do these really important national-security cases.

And the same would go for anyone who’s working actively on counterterrorism, you know. I mean, Donald Trump has talked a lot about his concern that there are, you know, terrorists making their way inside the United States, taking advantage of, you know, weak border security or other ways of getting into the U.S. Well, it’s FBI agents who do counterterrorism cases that investigate things like that.

So if you’re suddenly moving people with this level of expertise off their jobs, or you are creating a real disruption and distraction while they’re trying to do their jobs, I think that arguably weakens national security, it creates vulnerabilities, and it distracts the FBI from doing its job, which is to go out and not just investigate crimes but to try and stop violent crimes and bad things from happening to Americans and to the U.S. government.

Rosin: Right. So you can see the future crisis. Like, you can project a future crisis where we are vulnerable to terrorism or something like that because we’ve lost a huge amount of this expertise.

Harris: I think that’s right. Yes. It doesn’t seem to me like he is thinking through the consequences of hobbling the FBI at this moment. What he is interested in is retribution. He’s interested in payback. And he is putting, you know, not only the country, but he’s putting his administration at grave political risk by doing that.

Rosin: Okay, Shane. Here’s something else that I was wondering about. Since when did the FBI come under so much suspicion from the right? I’ve always thought of the FBI as an agency conservatives can get behind, and Trump’s attacks feel like they upend all that. It’s confusing.

Harris: Oh definitely. And this has long been one of the more baffling aspects of Donald Trump’s critique of the FBI, as he’s painting them as this kind of leftist deep state.

I mean, the FBI—I’m speaking in general terms, of course, I mean—it is a generally conservative institution, both because I think that the people who work in it are often politically conservative or just sort of dispositionally conservative. It’s a law-enforcement agency. I mean, it does everything by the book. There are jokes in the FBI about how it takes, you know, five forms that you have to fill out before you can make a move on anything. It is a very hidebound, bureaucratic, small-C conservative organization. I mean, these are cops.

Rosin: Right. Right.

Harris: Okay? It’s a bunch of cops, right? This is like, if you want to think in generalities, like, you know, USAID is like, Oh, yeah, it’s people who want to get to charities, and they worked in the Peace Corps, and they’re all about humanitarian causes. And that, too, is kind of a broad brush.

But, you know, when I talk to people who have worked in the bureau, if you knew these people, these are not people who you would associate with progressive causes. That doesn’t mean that they are sort of reactionary right-wingers. I don’t want to make that impression either. They’re very much following the rule of law. It’s a conservative institution. It is very hidebound and steeped in tradition and in regulation.

And, you know, Trump just has this image of it as this out-of-control left organization. And he has persuaded large numbers of his followers and Americans that this is true. And I have to tell you, in the 20-plus years that I’ve covered national security, one of the most fascinating and bewildering trends that I have seen is this change in political positioning, where now, people who tend to be on the left, sort of—I don’t want to say revere the FBI and the intelligence agencies but—hold them up as models of institutions of government that we need to have faith and trust in, and they’re there to try and protect people. When it was a generation ago, people on the left who were deeply skeptical of the CIA and the FBI because these agencies were involved in flagrant abuses of civil rights and of the law in the 1950s and ’60s.

And now it’s people on the right who, particularly after 9/11, used to be so reflexively defensive of the CIA and the FBI and counterterrorism and Homeland Security, who now have sort of swapped political positions with the critique on the left that see these institutions as, you know, run through with dangerous, rogue bureaucrats who want to prosecute their political enemies. I mean, it’s just like the people have switched bodies.

Rosin: Let me ask you a broader question about this. As someone who’s been tracking Trump’s attempts to rewrite the history of January 6 for a while, I could say I was a little surprised by the blanket pardon of insurrectionists, maybe a little more surprised by this effort to go after the agents who investigated them. Because—and tell me if this is an exaggeration—to me, that could send a message to supporters: If you commit violence on my behalf, not only will you not get punished, but anyone who tries to go after you will be in trouble. Which, if I continue that logic, seems like, potentially, a blank check to commit violence on the president’s behalf. Is that paranoid?

Harris: No. It’s not. It’s not. That is, I think, one of the clear risks that we face with the president behaving in the way that he has. And I would take it one step further, which is to say: The message is that if you are an FBI agent, or maybe more to the point, an FBI leader, someone in a management position, there are certain things that you should just not look into and investigate.

And not to say, like, now that the president enjoys, you know, presumptive immunity for all official acts. I mean, who knows what the FBI is even going to investigate when it comes to Donald Trump. But how good would you feel being assigned a case to look into Elon Musk or, you know, Trump campaign donors who may have engaged in illegal activity or influence peddling, the whole universe of people connected to Trump?

What he is saying by pardoning these J6 rioters is that If you are on my side, I will come protect you. And I think that will send a clear message to FBI personnel that there are whole categories of people and therefore potential criminal activity that they should not touch, because it gets into the president, his influence, his circle of friends. I think that is just a potentially ruinous development for the rule of law in the United States.

The FBI is there to investigate crimes objectively, regardless of who may have committed them. And what the president is doing now is essentially saying there’s a whole category of people who, if not outright exempt, are people that are going to fall under his protection, and for the people who might dare to investigate them, there will be consequences.

Rosin: Well, Shane, thank you, but no thank you, for laying that out in such a clear and chilling way. I appreciate it.

Harris: My pleasure, Hanna. Thanks for having me.

[Music]

Rosin: This episode of Radio Atlantic was produced by Jinae West. It was edited by Claudine Ebeid and engineered by Rob Smierciak. Claudine Ebeid is the executive producer of Atlantic audio, and Andrea Valdez is our managing editor.

I’m Hanna Rosin. Thank you for listening.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

There are two Chicago neighborhoods that are, on the surface, quite similar. They are both more than 90 percent Black; the median age of both is roughly 38. About the same share of people have college degrees, and the median income of both is roughly $39,000.

But one experiences about twice as many shootings per capita as the other.

The University of Chicago economist Jens Ludwig opens his forthcoming book, Unforgiving Places, by describing the neighboring places of Greater Grand Crossing and South Shore, both minutes away from the elite university where he teaches. Ludwig’s argument begins by reframing the problem of gun violence away from the demoralizing story of American exceptionalism and toward the more granular variation that differs state by state, city by city, and yes, block by block.

“Whatever you believe about the causes of gun violence in America, those beliefs almost surely fail to explain why Greater Grand Crossing would be so much more of a violent place than South Shore,” Ludwig writes. “How, in a city and a country where guns are everywhere, does gun violence occur so unevenly—even across such short distances, in this case literally right across the street?”

Talking about gun crime almost always turns into talking about gun-control legislation, a debate that has been happening my entire life and I’m sure will continue past my death. But on today’s episode of Good on Paper, Ludwig and I spend little time on that topic, focusing instead on policy levers that could reduce gun violence but don’t require national gun-control legislation.

The following is a transcript of the episode:

Jerusalem Demsas: In 2022, Louisiana had the second-highest rate of gun deaths in the country. I’m just back from a reporting trip to the Lake Charles area, and I had a few people remark rather pointedly to me that my home of Washington, D.C., is a violent place, seemingly unaware that D.C. has had a significantly lower rate of gun deaths than Louisiana for many years now.

Why do some places see higher rates of gun violence than others? It’s an incredibly important question to answer rigorously. Homicide is a leading cause of death for young adults, and the vast majority of those homicides happen with guns. But this is a topic where the politics rarely line up with actionable solutions.

After the COVID-19 crime wave, politicians have scrambled as they place crime at the top of the agenda again and are searching for public-policy tools to address violence in their communities.

My name’s Jerusalem Demsas. I’m a staff writer at the Atlantic, and this is Good on Paper, a policy show that questions what we really know about popular narratives. My guest today is the economist Jens Ludwig, from the University of Chicago, who has spent his career studying the economics of crime. He has a book coming out in a few months called Unforgiving Places: The Unexpected Origins of Gun Violence.

Jens and I talk about the classic explanations for why gun violence happens in some places and not others. He pushes back against the classic right-wing explanation that the problem is bad people and the classic left-wing argument that solving the problem of gun violence requires ending mass social inequalities first.

One note about the show: We’re going to begin adding the studies and articles and books we reference in the show notes, so you can easily access them for further reading. A link to Jens’ book will be there, too, if you’d like to investigate his argument further.

Okay. Jens, welcome to the show.

[Music]

Jens Ludwig: Thanks so much for having me. It’s such an honor to be here.

Demsas: Jens, you have a book coming out in April called Unforgiving Places. What’s it about? What are you arguing?

Ludwig: The book basically makes two arguments. One argument is that we’re despairing about the problem of gun violence because we’ve thought about it as just all being about gun control, and I think that’s not true. I think the problem of gun violence in America is partly about guns, and it’s partly about violent behavior. And if we can’t do anything about the guns, we can at least try and do something about the violent behavior. And the experiences of L.A. and New York over the last 30 years show us that there’s real progress that you can make there.

And then I think the other core argument of the book is that violent behavior is not what we’ve thought. I think most people have thought of violent behavior in America as being about thoughtful, deliberate action that leads you to focus on incentives, like bigger sticks or more enticing carrots. And in fact, I think most shootings in America are instead fast-thinking, reactive—it stems from arguments. And that leads us away from relying exclusively on incentives and towards a very different type of policy that we just haven’t been talking about or thinking about.

Demsas: When I was reading your book, there was a stat that just has been rattling around in my brain since I read it. You write that shootings account for fewer than 1 percent of all crimes but nearly 70 percent of the total social harm of crime. What does that mean? And how is that even measured?

Ludwig: Yeah. So the way that economists think about that sort of thing is very analogous to how environmental economists think about environmental harm. If you go back to the Exxon Valdez oil spill in Alaska a million years ago, there’s the tangible cost of cleaning up the bay or whatever it is, and then there’s the sort of social costs that don’t show up on any sort of budget spreadsheet anywhere. That’s the “harm to this pristine place now being ruined forever” kind of thing.

And so environmental economists have come up with ways of quantifying those sorts of intangible costs. And we can use the same sort of approach to measure the harm for crime as well. It basically comes down to what people are willing to pay to avoid exposure to different types of crime.

And so what you can see is people really don’t like disorder. They really don’t like having their bicycle stolen, their car stolen. I lived in cities for the last 30 years. I’ve had almost every sort of property crime that you can imagine happen to me. But the thing that people really, really are petrified about is staring down the barrel of a gun. And I can tell you that from firsthand experience. I was held up at gunpoint myself on the South Side of Chicago, going to pick up my older daughter from her piano lesson about five years ago.

My University of Chicago colleague Steve Levitt did a study where he showed that every serious crime that happens in a city reduces the city’s population on net by one person—so fewer people moving in, more people moving out. Every murder that happens in a city—the overwhelming majority of murders in the United States, unfortunately, are committed with guns—every murder that happens in a city reduces the city’s population by 70 people. And I think that’s another way to sort of see exactly how much the gun-violence problem in America is driving the crime problem.

Demsas: I also think it’s just remarkable to really think about this in perspective of how much effort we spend in trying to eliminate certain types of crime. I mean, if 70 percent of total social harm is shootings, then the vast majority of our efforts should just be focused on guns. And property crime should take a backseat, all this sort of thing. Intuitively, we understand that, obviously, murder is worse than other forms of crime, but I think the degree to which that is driving America’s violence problem and crime problem and the harms that ricochet out into communities is, I think, not well understood.

Ludwig: Yeah, I one million percent agree. And I think it also sort of helps you see a path to a criminal-justice system, a law-enforcement system that kind of sidesteps a lot of the current political fights that we’re having. I think everybody agrees that gun violence is a hugely serious problem, that we should be holding people accountable for this.

Even the mayor of Chicago, who I think within the political distribution is one of the more progressive elected leaders in the United States—he’s going around talking about the need to improve the odds that shooters get arrested and wind up behind bars. And so I think this much stronger focus on gun violence would be a way to concentrate everything on the thing that the American public really cares the most about. It sidesteps a lot of the fraught political debates about how we do enforcement over lots of other things that the public doesn’t like, but it’s not the first-order thing that they’re worried about.

Demsas: So there’s familiar pattern that I think most people are aware of when it comes to the gun-policy conversation in the United States, and it’s: There is a tragic mass shooting—maybe at a school, maybe at a nightclub—and then there’s this intense rallying to pass gun legislation.

And economists have quantified this. There’s a study that showed that a mass shooting leads to a 15 percent increase in the number of firearm bills introduced within a state the year following that shooting. Interestingly, in states with Republican-controlled legislatures, those are often laws that loosen gun restrictions. But even when looking at Democrat-controlled legislatures and laws that tighten gun restrictions, studies often struggle to find significant impact of these laws on reducing gun violence, reducing deaths, reducing mass shootings.

In your book, you also seem kind of pessimistic about the potential for gun legislation to have a large impact on reducing gun deaths. Why is that?

Ludwig: Yeah. Let me respond in two ways. The first is: Federal gun laws set a floor, not a ceiling, on what cities and states can do. And so lots of cities and states around the country, including my home city of Chicago, have enacted gun laws that are more restrictive than what you have under the national law. And the problem with that is that we live in a country with open city and state borders. So what Gary, Indiana, is doing about air quality affects the South Side of Chicago, and vice versa, right?

And in the same way, like, my family for the last 18 years has lived in Hyde Park, on the South Side of Chicago. Our favorite ice-cream place in the area is Dairy Belle in Hammond, Indiana. So we spend 20 minutes driving down there every summer, like, way too often. And when we come back from Indiana into Chicago, nobody stops us at the city border to check what we have in our trunk.

And when you look at where the crime guns are coming from in Chicago, almost none of them come from a gun store in Chicago. They come from places like, you know—there are gun stores quite close to Dairy Belle in Indiana that are big sources of crime guns in the city. So I think the way that you want to be thinking about gun regulation, I think, is very analogous to how you would do something like regulate air quality. And that’s to think about regulation at the national level in a world in which you’ve got what an economist would call lots of externalities across jurisdictions in their own laws.

Demsas: But even federal gun-control legislation has often felt, at least from my overview of the economics literature, like it hasn’t had a massive impact, whether it’s assault-weapons legislation or other forms of gun-control legislation that’s passed over the past few decades. Is that just a reflection of the fact that these laws are pretty modest in what they’re attempting to do? Or does that indicate that we can’t really attack this problem legislatively?

Ludwig: What I would say is: Most of the national gun laws that we’ve enacted in the United States are very modest, as you said. I think the biggest problem with the gun laws that we have in the United States is: Most of the laws regulating gun acquisition—you know, gun sales—only apply to gun sales that are, basically, carried out by a licensed gun dealer.

And that’s something like 50 or 60 percent of all gun sales in the U.S. And the other 40 percent are almost completely unregulated under federal law. Some states try and regulate that, but that’s not a loophole—that’s like a chasm that you can drive a truck through. And you know, when you look at where the guns used in crime come from, you wouldn’t be surprised to see that’s the most important source of crime guns that you see in Chicago and other cities around the country.

But you know, I think the difficulty of cities and states regulating their way out of the gun-violence problem, and the difficulty of substantially changing national gun laws, has led a lot of people to conclude that gun violence in America is a hopeless problem, because we can see that the gun-control politics are stuck.

So one way that I’ve come to think about this is that that’s too pessimistic a view. And the reason for that is that gun violence is not just about guns; it’s about guns plus violence. So it’s having lots of guns around, but also having people who use them to hurt other people. And if we can’t make much progress on the gun-access part of things, the good news is that there’s a second path to progress, which is to try and change the willingness of people to use guns to hurt other people.

We have something like 400 million guns in the United States, in a country of about 330 million people. And I think the existence proof that shows us that you really can make a huge difference on the gun-violence problem by figuring out how to control violence comes from the Los Angeles and New York City experience over the last 30 years.

So in 1991, the murder rate per 100,000 people in L.A. and New York was very similar to Chicago, actually, at that time. It was something like 30 per 100,000. So to give you a sense of what that means: In London, the murder rate is something like one or two per 100,000. So the United States is just totally off the charts. Almost all of those extra murders here are committed with firearms.

And in the 30-year period following that—so 1991 (the peak of the crack-cocaine epidemic), 30 years after that, up through 2019 (the last year before the pandemic)—the murder rate in Los Angeles declined by 80 percent; the murder rate in New York City declined by 90 percent. And those are cities that are swimming in the ocean of, you know, hundreds of millions of guns in America. And I think that speaks to a more optimistic take, that it is not a hopeless problem—not just that something can be done but that something substantial can be done.

Demsas: The other variation you point to in your book that is what really intrigued me is that Canada and Switzerland also have above-average rates of gun ownership, but they don’t have particularly high rates of murder in line with what we would expect if you just took America’s experience. And I think I had this kind of model in my head that it’s just like, If you have this many guns, there’s nothing you can do. Like, that’s the situation. There will be variations based on other things, like whether the economy is doing well or whether we’re incarcerating people or not, or how many cops there are on the street and what they’re doing. You’d still see variations in crime, but you would always have some kind of baseline level of criminality.

But I want to get to the core argument of your book, which I think is maybe encapsulated by a pretty provocative question on the back cover, which says, “What if everything we understood about gun violence was wrong?” This is a very bold claim, and I’m excited to explore it with you. But I think that the first part of that is unpacking what it is that you mean by “everything we understand about gun violence.” You lay out two competing theories that Americans hold about the causes of gun violence. One is the “root causes theory” and one is the “wickedness theory.” Can you just walk us through what those two are?

Ludwig: Yeah, the conventional wisdom in America right now says that violent behavior is thought through, right? So it’s either bad people who aren’t afraid of whatever the criminal-justice system is going to do to them, or it’s people in bad economic conditions who are desperate in doing whatever they need to do to survive. And both of those conventional wisdoms on the right and the left actually have something in common, which is: They think of gun violence as being sort of a deliberate behavior, and that leads us then to focus on incentives to solve the problem. You know, We need bigger sticks, if you’re on one side of the aisle, or if you’re on the other side of the aisle, We need more enticing carrots.

I think the thing that’s so striking is that it just doesn’t fit with what all of the data tell us gun violence in the United States is. Most shootings are not premeditated, and most shootings are not motivated by economic considerations. They’re not robbery. They’re not drug-selling turf. That’s all what psychologists would call “System 2” slow thinking.

Most shootings, instead, stem from arguments. They’re reactive, or what psychologists would call “System 1” thinking. And the fact that so many shootings stem from these sorts of in-the-moment conflicts that go sideways and end in a tragedy because someone’s got a gun, that helps explain why deterrence is imperfect. Someone acting very reactively is not thinking through a jail sentence. And it also helps explain why a social program that’s intended to reduce poverty—like give somebody a job, give somebody cash, whatever—that also isn’t solving the violence problem.

Demsas: I want to hold here a bit because I think this question, Are people making rational calculations? is both at the heart of a lot of economics and also the heart of what we’re going to talk about for the rest of this episode. And I accept that I do not think that I or anyone else is constantly doing a benefit-cost analysis about every action that I take, even if it is as important as whether you pull out a gun and shoot someone.

But I wonder whether that undersells the rationality that still exists, right? Because we know that deterrence is possible. We know that when we increase the certainty of capture—if you know you’re going to get caught for shoplifting, if you know that you’re going to go to jail if you shoot someone—that significantly decreases crime incidents. And what that indicates to me is that there is a level of benefit-cost analysis happening, even if people aren’t fully using that System 2 part of their brain.

Ludwig: Yeah, I one hundred percent agree that deterrence is really a thing. I’m a card-carrying economist. I work at the University of Chicago. I totally believe that incentives matter and that deterrence is a thing. But I think that this really connects very importantly to where we started, that gun violence is the part of the crime problem that is the thing that drives the total social cost of crime.

So in many ways, crime is an unhelpfully broad term. It’s almost like disease. What would you do about disease? I mean, I don’t even know how to think about answering that. Like What are we talking about? Like, pneumonia or cancer? And crime is a similarly unhelpful, super-broad umbrella.

And there was a study, for instance, done in Sweden a few years ago where they looked at what happened when you put cameras up in the subway system. And what you could see is that property crimes go down when you camera-up the trains, but violent crime doesn’t go down, right? And I think what that tells you, partly, is that different behaviors are shaped differently.

The key breakthrough of behavioral economics and behavioral science over the last couple of decades is to realize that our minds work in two different sorts of ways. There’s the deliberate, sort of rational benefit-cost calculation that psychologists call System 2, and a sort of very reactive, automatic, below-the-level-of-consciousness cognition that psychologists call System 1—or fast thinking and slow thinking.

And different behaviors are driven by different types of cognition. And so stealing a loaf of bread to feed your family is much more System 2 than what you do in an argument. Let me just point the finger at myself, first and foremost here. I’m not saying anything about other people’s behavior that is not true of my own behavior.

I’ve lived for 18 years in Hyde Park. It’s a little University of Chicago village in the middle of the South Side of Chicago. Every Wednesday morning, I take my dog, Aiko, out for a little walk. One day, I’m walking down the street, and about three or four doors down from me, there’s a neighbor whose dog is off leash, runs down the driveway, and attacks my dog.

Demas: Oh God. I hate that.

Ludwig: No, exactly. And this guy, the neighbor—his kids are literally in the same classroom as mine at the lab school. He lives four doors down from me. I have every incentive in the world to handle that gracefully and constructively. And that’s exactly what System 2 rational thinking would have done.

It turns out: That is exactly not what I did in that case. I assume this is a podcast where people don’t curse, but you can only imagine the stream of four-letter, seven-letter, and twelve-letter words that came out of my mouth at this guy who I’m going to be seeing for years into the future. I’m going to be seeing him at the parent potluck at school.

And so it really speaks to this idea of: In these super high-stakes moments, where people just don’t have very much bandwidth and they are relying on sort of very fast thinking to navigate, we are not always our best selves. We are not thinking about benefits and costs and things off into the future. We can make mistakes. All of us can make mistakes.

And in my case in Hyde Park, I was very lucky that neither one of us had a gun. But in a country with 400 million guns, you know, lots of people are in situations like that and behave the way I did and, unfortunately, they or the other person’s got a gun, and it ends in tragedy. And those tragedies, really, I would just point out, claim two lives. Somebody does something stupid in a moment and, you know, you spend the rest of your life in prison, and somebody else winds up dead. It’s multiple tragedies stemming from that.

Demsas: First, is your dog okay? Was everything fine?

Ludwig: Yeah, she’s a big chicken. She’s, like, a 70-pound shepherd mix who decided, rather than to try and defend herself or whatever, she would—I don’t want to throw my dog under the bus here. Everything turned out fine. She’s a lover, not a fighter. (Laughs.)

Demsas: (Laughs.) Your dog also is in System 1 thinking.

Ludwig: Yeah, exactly.

Demsas: Well, first, we’ll shout out the late Danny Kahneman here and his Thinking, Fast and Slow book, which provides much of the foundation of the System 1, System 2 model that you’re talking about here.

But I want to push here a bit because I think one of the common objections people have to this line of argument is that, yes, it is the case that, whether someone’s coming at you or you’re worried about your dog, and you don’t react the in the way that you might if you used your logical brain to react if you had time to think—but given that if you place every single American in the exact same conditions, you still see large variations in how people choose to respond, right? Like, all the people who are in conflicts in the South Side of Chicago do not shoot each other. A very small minority of people are choosing to shoot each other, even if they have access to a gun.

And so doesn’t that push against this idea that the problem is this System 1 thinking? Like, there is something particular about the choice to pull out a gun and kill someone in that moment. And it’s not just, Well, anyone can make that mistake, because even if you think about this demographically, we’re seeing mostly young men make this mistake and make this choice. There is something going on here that is not just, You’re not able to think under stress.

Ludwig: Let me take your question and sort of turn it on its head for a second. One of the things that I point out in the book is like a version of an observation that Jane Jacobs made 60 years ago in her book The Death and Life of Great American Cities, which is: When you look at similarly poor neighborhoods in American cities, you see huge variation in crime rates, especially violent crime.

And as I mentioned, I lived for a long time in Hyde Park, on the South Side of Chicago. There are two neighborhoods just south of Hyde Park. There’s Greater Grand Crossing and South Shore that are socio-demographically, historically almost identical in terms of their racial and ethnic composition, their socioeconomic composition. They’re adjacent neighborhoods, so they’ve got exactly the same gun laws; they’ve got exactly the same social policies. When people get caught, they get sent to exactly the same court system. So all the incentives that conventional wisdom would say would matter are identical. And yet the shooting rate per 100,000 is, in most years, about twice as high in Greater Grand Crossing than literally across Dorchester Avenue in South Shore.

Demsas: Wow.

Ludwig: So that’s sort of taking the premise of your question and noting that the incentive explanation certainly doesn’t explain all of the variation that you see in gun violence either.

So what could it be then? I one million percent agree with you that—at its core, the argument here is: People are people, and a lot of what determines the outcome of this interpersonal conflict is the situation that someone finds themselves in. But if it’s not socioeconomics, and it’s not the characteristics of the criminal-justice system, what else would it be?

And I think in many ways, Jane Jacobs was really onto something 60 years ago in thinking about what that thing would be. To sort of connect an experience that I had in Chicago a couple years ago to Jane Jacobs’ insight, I was in the juvenile-detention center on the West Side of Chicago, I’m talking to a staff leader there, and he says, I tell all the kids in here, “If I could give you back just 10 minutes of your lives, none of you would be here.”

And one of the insights that Jane Jacobs had 60 years ago is: If the problem here is people do things in these 10-minute windows that they later regret, you could almost sort of think of fraught social interactions as like a high-wire act. And one of the ways that you can help people is by—what do they do in the circus for high-wire performers? They have a safety net there.

And one of the safety nets that you have much more of in some neighborhoods than others is essentially what Jane Jacobs called “eyes on the street”—prosocial adults who are around and able to step in and deconflict things when it happens. And you could see exactly that when you look at South Shore versus Greater Grand Crossing.

So there is, for instance, much more commercial development in South Shore than in Greater Grand Crossing. And what that means, in practice, is that there’s just lots more foot traffic in the community in South Shore than Greater Grand Crossing. And so if a group of teenagers is getting into an argument, there’s more likely to be, like, a neighborhood adult around to step in.

It’s also the case—so my friends Sendhil Mullainathan and Eldar Shafir have a wonderful book that came out a couple of years ago, called Scarcity, where they point out that one of the many challenges of being poor in the United States is living in day-to-day circumstances that tax mental bandwidth. It’s just very stressful, right? And people with limited bandwidth wind up relying much more on System 1 than people who are less bandwidth taxed.

So when you look at the data, you can see all sorts of indicators that there’s much more stress and bandwidth tax for people living in Greater Grand Crossing than South Shore. And what that would lead you to conclude is that the people who are in Greater Grand Crossing are going to be more likely when they’re in these difficult, 10-minute, fraught interactions with somebody else to rely on System 1 to navigate that than their more deliberate, rational benefit-cost-calculating selves.

So I think the sort of left-of-center perspective that there are root causes that matter is definitely right. I think it’s totally right for property crime—you know, crimes shaped by economic considerations. I think it’s just a little bit incomplete with respect to the part of the crime problem that the public cares the most about, which is gun violence. And so I think we just need to expand our lens about what aspects of the social environment we want to be prioritizing for our public policies.

Demsas: I’m a housing person, so I’m a big fan of the Jane Jacobs book and the argument that she kind of draws out, and I think people can imagine this if they’ve been in streets and communities like this before, is when you have kind of mixed-use development—you have a coffee shop, and above that coffee shop, you have apartments, and across the street, there’s also a park, and there’s also a school nearby—is that that means that throughout the day, there are many different kinds of people watching the streets.

Versus if you had just a fully residential area, and then during the day, everyone’s basically gone because they’re either at school or work, so it really empties out of people to watch things. Or if you have a fully industrial area, where when people go home for the day, there’s nobody there. Or commercial area, same thing. And so when you have these kinds of mixed-use-development areas, it feels a lot safer because you can just always feel like there’s someone around doing normal business or taking their kids to school or whatever.

So I would love for housing policy to be the key. But is your argument, then, that the differences between neighborhoods that have similar socioeconomic problems, similar legal environments, etcetera but a large variation in gun violence is largely a function of their urban form?

Ludwig: I just—I absolutely adore that this is a sort of empirical, data-intensive, data-nerd podcast, and so in that spirit, I do think one of the big challenges for making progress on the sort of the crime and criminal-justice problem is: A lot of it is editorializing rather than guided by data. And so I think one of the key things that I tried to do in the book is really stick to the data and see what the data are telling us.

And so does the built environment matter? There was a wonderful study by Mireille Jacobson and Tom Chang that looks at what happens in Los Angeles when marijuana dispensaries open or close as a result of some regulatory change and when food places open and close.

That’s like the natural experiment of Jane Jacobs, like, let’s put in more mixed use—and what you can see is that when a retail establishment closes and foot traffic goes down, crime goes up.

There was a wonderful study by a great team at the University of Pennsylvania that worked with the City of Philadelphia to do a randomized experiment where they picked a bunch of rundown, vacant lots all over the city and picked half of them to redevelop and turn into little pocket parks. And what you can see is that the pocket parks then wind up bringing more people out of their homes and spending time there in public. And you can see that people feel safer, and they are safer. Gun violence goes down as a result of that.

My research center, the University of Chicago Crime Lab, we did a randomized trial with the City of New York a couple years ago where we helped put increased street lighting in some public-housing developments and not others. And one of the things that that would do is also potentially get more people out in public. We see violence decline there as well.

And then one other thing that I would just add—actually, two other quick things that I would add to this is: I think it gives you another way to understand all of the research and economics that suggests more police reduce crime. I know you had Jen Doleac on recently; you guys were talking about this.

I think most people would say, Oh that’s, like, deterrence or incapacitation. But when I look at the Chicago Police Department, for instance, the average Chicago cop makes about three arrests—not per week, not per month—per year. Three arrests per year.

Demsas: Wow.

Ludwig: So it’s, like, not a gigantic arrest machine that is generating all of this massive deterrence. What are police doing? Well, one of the things that they might be doing is helping interrupt these 10-minute windows. It’s something preventive, right? And I think that is a potentially important part of it.

And the thing that I would add to this, as well, is that sociologists believe that one of the most important determinants of a neighborhood’s violent-crime rate is what they call “collective efficacy”—this is research from the 1990s—the willingness of neighborhood residents to sort of step in and do something when there’s some sort of problem in the neighborhood. And I think that also is very consistent with this kind of behavioral-economics view of the gun-violence problem and what to do about it.

[Music]

Demsas: After the break: the problem with focusing on the “root causes” of gun violence.

[Break]

Demsas: Someone listening to this will say, How is this different from the root causes analysis that you kind of critiqued? Right?

Because there’s a really great quote that you have in your book, which is that we “treat gun violence as something that will get better once we fix everything else that’s wrong with society.” And I think that’s a frustration that a lot of people have, is that they are sympathetic to the idea that if we invested more in education, or if we invested more in social-welfare programs and UBI (universal basic income), expanded health care, that there would be reduced crime in 20 years, in 30 years.

But that doesn’t really respond to the specific concern of, Tomorrow when I walk to school, am I going to get shot? Can you help distinguish between your analysis and that root cause analysis?

Ludwig: What I hear in Chicago is something that you hear in lots of cities around the United States, is like, Gun violence is just a symptom of poverty, and we’re never going to solve the gun-violence problem until we solve the poverty problem.

And let us all hope that’s not true, because, as you know even better than I do, we’ve been working really hard for decades to try and solve the poverty problem in the United States, and it’s proven to be very difficult. I think the key optimistic observation or suggestion that we get from this behavioral-economics perspective on the gun-violence problem is: We can make massive changes in the gun-violence problem by changing parts of the social environment that are much easier to change than poverty and segregation and all of these other super big, super important social problems.

If I could wave a wand and I could end poverty and segregation in Chicago, believe me—I’d be the first person to wave that wand. And so I’m not arguing against any of the policies trying to do that. They’re super important. It’s more like, What else can we do on top of that to really start to make a meaningful difference on the gun-violence problem?

And I can’t wave a wand and end poverty in Chicago, but what I can do is: I can make it easier to have commercial development in Greater Grand Crossing than we currently have here on the South Side of Chicago. I can strategically deploy money to turn a bunch of vacant lots that are littered with empty broken beer and tequila bottles and turn that into a little pocket park that people are willing to be in. I can put money into things like block clubs. I can do some version of what the University of Chicago does, like put unarmed private security guards on some key corners to make sure that there’s an eye on the street because of that. So there’s a bunch of pragmatic things that you can do that can really make a difference that sort of complement these other efforts to address these really big root causes.

And maybe the one other thing I would just add: You might look at that sort of strategy and say, To some people, that’s going to feel unsatisfying that it is addressing a symptom, not the underlying cause. Like, we’re leaving the root causes there, and we’re just treating the symptom of the root causes. But I actually think what that concern or that perspective misses is that the causal arrow runs in both directions between gun violence and root causes, if that makes sense.

And you can sort of see a lot of these communities are in vicious cycles right now, where it’s like: You’ve got a lot of gun violence. People and businesses leave—fewer eyes on the street, fewer community resources to build the kind of public infrastructure that helps address this problem, even more gun violence, even more people leaving. There are lots and lots of neighborhoods, lots and lots of cities that are trapped in that sort of vicious cycle.

But if you can get the gun-violence problem under control. I think you can see that you can turn those vicious cycles into virtuous cycles. I think of gun violence, you know, not as a symptom of some deeper thing but in many ways as the social problem for cities that sits upstream of so many of the other social problems that cities are trying to wrestle with.

Demsas: To give your model in layman’s terms: Gun violence and shootings happen because there’s a large availability of guns and because people are not interrupted in pulling those guns out in the midst of a heated moment. So as you point out in your book, the vast majority of shootings are happening in the course of an argument—not in a premeditated sense but in [the sense] that someone bumps you on the sidewalk, or they insult you, or something like that—and that violence, that shooting happens because there’s no one to step in and say, Hey. Let’s calm things down. Is that kind of the overview that you’re giving us?

Ludwig: Yeah. The highest-level version of this is: All of our policies have conceived of gun violence as a problem of System 2 slow thinking, when I think it’s, actually, mostly a problem of System 1 fast thinking.

And so for starters, we just need a big reorientation to understand differently what the problem actually is to be solved. And once you have that reorientation—once you sort of think of gun violence as a problem of not bad people unafraid of the criminal-justice system, not people in bad economic circumstances stealing to feed their families, but normal people making bad decisions in fraught, difficult, 10-minute windows—one thing that you start to do then is start to think about, How do I change the social environment so there are more people, more eyes on the street to sort of step in and interrupt? And the other thing that you start to think more seriously about is, like, How do I focus my social policies more on helping people understand their own minds better and anticipate what they’re going to do in these difficult 10-minute windows?

And one of the ways that we can do that is through a very different type of social program than we’ve typically thought of in the U.S.—these behavioral-economics-informed programs like Youth Guidance’s Becoming a Man or Heartland Alliance’s READI program or YAP and Brightpoints’ Choose to Change program. These are all things that we’ve subjected to randomized controlled trials in Chicago.

And what they basically are doing is: They’re helping people understand that they’ve got fast thinking as well as slow thinking and recognize that their fast thinking can get themselves into trouble in these fraught moments, and helping them anticipate that and sort of better navigate those 10-minute windows. And you can see in randomized experiments that that reduces risk of violence involvement by, depending on the study and the time period, like, 30 to 50 to 60 percent. How you scale that, I think, is the frontier scientific and policy challenge, but at least now we can sort of see the direction that we’ve got to go.

And the other thing I would just add is: I think this behavioral-economics perspective also helps us understand why education is so important for solving the violence problem, but not in the way that people have historically thought. Most people would say, Yeah, of course, education is so central to solving the crime problem, because education improves people’s earnings’ prospects, and blah, blah, blah.

And it’s true that education is hugely important for people’s earnings prospects, and education is good for making better citizens. It is good for lots and lots of reasons. But the other thing that the data tell us education does is: It helps people learn to be more slow thinking and skeptical of their own minds in high-stakes moments. That turns out to be sort of a key byproduct of everything that schools ask people to do.

And I think of education as, like, in many ways, the most important sort of crime-prevention, gun-violence prevention tool that we have. I think things like rote learning are not what we want either for educational purposes or from the perspective of making schooling as sort of crime preventive as possible. And so I think there are other ways of reimagining what school does, which would be good for making school sort of more helpful for a world in which things like problem-solving are increasingly important for economic outcomes, but also super valuable for making education more helpful in addressing the gun-violence problem.

Demsas: You alluded to this a couple of times now, but it’s interesting that there’s one way to interpret your result as just, as like, We need to put a bunch more cops on the street, and those can be the eyes on the street. And that is kind of consistent with the literature we explored in the Jen Doleac episode around why increasing numbers of police officers can reduce crime, and violent crime, in particular. And the other avenue—I mean, these are complementary—is that there needs to be more attention on how to improve people’s System 1 thinking. And the Becoming a Man program, which I think is now really popular, is a great example of that.

But scaling these sorts of things is really, really difficult, as you mentioned. Are you indifferent between these two policy avenues, like an increased number of police officers, versus investing in programs that improve people’s ability to understand their own System 1, System 2 thinking? Or is it that you really want people to do one of those over the other? And in which case, it does seem very difficult to scale Becoming a Man and other programs. We have not been able to do that, despite years and years of positive coverage of that program.

Ludwig: For starters, I would say, we should be pushing on every possible front to solve this problem. It’s a huge humanitarian problem, one of the key drivers of Black-white life expectancy disparities in the United States, hugely important for the future of our cities that are the key economic engine for the whole country. So I wouldn’t say, like, Let’s do this or this. If we have multiple things that could be helpful, I’d say, Let’s push on every front.

On the eyes-on-the-street stuff, I would say, There’s tons of scalable stuff there, and it’s not just hiring more cops. So you can hire more cops in cities that like cops. You can put unarmed security guards on the street. You can fund community-violence-intervention nonprofit groups. You can clean up vacant lots and turn them into parks. You can improve street lighting. You can change zoning laws and permitting rules and whatever to make it easier to have stores interspersed with residential in a neighborhood. Tons of different things there that you could do, depending on the local political environment in your city, all of which are super scalable, all of which would be super helpful, all of which would increase the chances that there’s some sort of prosocial adult around who can sort of step in and de-escalate something.

On top of that, I think then there’d be huge value in trying to figure out how to scale the social programs that also help people better understand their own sort of thinking. And I think one of the most exciting visions for the future here comes from artificial intelligence, weirdly. My University of Chicago colleague Oeindrila Dube did a fascinating study with Sandy Jo MacArthur, who used to be at LAPD for many years, and my friend Anuj Shah, at Princeton.

They basically did Becoming a Man for cops. And what was so interesting about it is: Becoming a Man works with teenagers in middle school and high school. And it’s, like, an adult working with these kids, and that’s super hard to scale, because the program counselor is expensive, and they vary in skill, and How do you hire enough people? and everything that makes a social program hard to scale.

But the Becoming a Man for cops—what they did is they had this artificial-intelligence-driven force simulator thing, where they give cops feedback to see when their System 1, their fast thinking, is leading them to an unhelpful response, through a bunch of simulation exercises that the AI can do. And you look at the randomized control data, and it seems to have remarkably helpful impacts.

And I think the thing that’s so exciting about that is: Thinking about AI as a human-capital development tool lets you see, Oh I see. Once you’ve got the software, the marginal cost for rerunning software is super low. And the great thing about software is that it basically runs the same way over and over again. So we might be looking at a future where AI can be a super valuable way to enhance human capacity in ways that include addressing one of the most important social problems facing cities, which is gun violence.

Demsas: We’ve gotten a little bit into this, but trying to compare all three theories that are kind of existing out there: When we’re thinking about the root causes theory, that leads us to believe that we should invest a ton in antipoverty measures and expand healthcare, job-training opportunities, UBI, whatever. And then the wickedness theory kind of indicates that we should just try to root out and incarcerate bad people for as long as possible to prevent them from doing crime. Your theory, the “unforgiving places” theory—what do you want policy makers to take from that?

Ludwig: The first thing I want policy makers to take from this is to recognize that the gun-violence problem itself is different from what we think. Again, it’s not a problem of System 2 deliberate, slow thinking, people responding to incentives. Gun violence is mostly driven by System 1, reactive, fast thinking. That’s the most important thing.

From there, I would say we need to do two types of things. We need to change those aspects of the social environment that reduce the risk that conflict escalates. And related to that is, too, just in the safety net, is whatever your position on the Second Amendment, I think this is also why guns out in public are particularly worrisome. If people want to have 500 guns in their basement locked up, that’s one thing. But when people are taking guns out on the street, that’s the thing that makes interpersonal conflict on the South Side of Chicago so much more dangerous than interpersonal conflict in the south side of London or whatever. So people around to deconflict conflict when it happens, and anything that we can do to get guns off the street would be super helpful.

And then I think policies that help people, you know, both K–12 education and things like, you know, Becoming a Man to try and help people better anticipate and navigate those 10-minute windows. And that’s a policy agenda that really doesn’t make much sense under either the conventional wisdom of the left or right, right now. Those things aren’t about changing people’s incentives, so it’s like, Why in the world would they possibly work? But I think they’re really central to making huge progress on the problem. And I think if you look at the experiences of L.A. and New York over the last 30 years, they validate that view, or they’re certainly very consistent with that view, at least.

Demsas: Jens, always our last and final question: What is an idea that you once thought was great and ended up being only good on paper?

Ludwig: Great—so we launched a big research project with the superintendent of the Chicago Public Schools a couple of years ago. The huge priority of this superintendent was truancy. So Chicago used to have something like 150 truancy officers for its 600 schools in 1991, and with budget cuts, they got rid of all of them. And then you look at the data and, like, there are tons of kids who are missing three or four weeks of school a year.

And so you look at that, and the superintendent is like, This surely is a key reason that kids are not doing well in school. So Jon Guryan and I launched this big research project with CPS, and we worked really hard to try and figure out how to get kids to come to school more often, without the punitive whatever of truancy officers. With a bunch of partners, we managed to figure out a way to get kids to come back to school more often. And then we look at the data, and we see it does not boost their learning at all.

Demsas: Oh wow.

Ludwig: So weird, so counterintuitive. You would think, If you don’t go to school, you can’t learn. It’s super intuitive. And yet, you get kids to come to school more often, and they don’t learn.

Demsas: Wait. What’s going on? Doesn’t that kind of conflict with a lot of ed-policy research?

Ludwig: Yeah. So super weird, right? And so it was only very recently that Jon and I were looking at data right after the pandemic, and what you can see in the data is, for instance, if you look at eighth graders in Chicago, the average eighth grader in Chicago academically is like a sixth grader. And something like a third-ish of Chicago eighth graders academically are, like, closer to fourth graders.

Demsas: Wow.

Ludwig: And the eighth-grade teachers—their feet are being held to the fire to teach eighth-grade content. And so then you ask yourself, Why is it the case that sending a kid who, academically, is at the fourth-grade level to school to be taught eighth-grade content doesn’t improve their learning? Like, to ask the question is to answer it.

Demsas: So it’s like, basically, the kids who are missing a bunch of school are more likely to be the kids who are way behind in school. And so they’re going to benefit less from being in school.

Ludwig: Exactly.

Demsas: Oh wow. That’s a very depressing answer.

Ludwig: Yeah, we were confusing, you know, What is a cause, and what is effect? And so it seemed good on paper. Now we realize that there’s a very different underlying problem that we’re working hard to fix. But that’s my depressing answer to leave you with.

Demsas: Well, thank you so much for coming on the show. This was fantastic.

Ludwig: Thanks so much for having me on. It was great.

[Music]

Demsas: Good on Paper is produced by Rosie Hughes. It was edited by Dave Shaw, fact-checked by Ena Alvarado, and engineered by Erica Huang. Our theme music is composed by Rob Smierciak. Claudine Ebeid is the executive producer of Atlantic audio. Andrea Valdez is our managing editor.

And hey, if you like what you’re hearing, please leave us a rating and review on Apple Podcasts.

I’m Jerusalem Demsas, and we’ll see you next week.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

By now you’ve probably noticed your attention being stolen, daily, by your various devices. You’ve probably read somewhere that companies much more powerful than you are dedicated to refining and perfecting that theft. In this episode of Radio Atlantic, MSNBC host and author of The Sirens’ Call: How Attention Became the World’s Most Endangered Resource explains in painful detail what you’re really up against. “It’s absolutely endemic to modern life,” Hayes says. “Our entire lives now is the wail of that siren going down the street.”

Hayes talks about his own experience of becoming famous enough to be recognized and becoming a little addicted to that attention. He explains how companies have learned to manipulate natural biological impulses in ways that keep us trapped. And he invokes Marx, who argued that capitalism alienates workers from their labor, to explain how technology is now alienating all of humanity from attention, which is perhaps more insidious because it lives in our psyches. “I think it’s because there’s something holy or sublime in actual human connection that can’t be replicated.”

The following is a transcript of the episode:

[Music]

Child: When my parents are on the phone, it usually makes me feel, like, really bored and makes me want to do something, because I don’t really have anything to do. And I’m kind of just, like, sitting there and watching them on the phone.

Claudine Ebeid: And what do you think about the amount of time that Dad and I spend on the phone?

Child: Well, I think, like, when they had landlines and stuff, you wouldn’t spend too much more time on the phone, and you would spend it on other types of devices.

But now, since it’s all in the phone, you wouldn’t really be seeing your parents, like, on a computer. You’d only see them doing that for, like, work or something.

Hanna Rosin: That’s our executive producer, Claudine Ebeid, and her daughter. We’re hearing from them because when we talk about screen time or how phones are manipulating us, it’s often adults talking about kids. But of course, it goes the other way too.

Chris Hayes: Every kid is engaged in a kind of battle for their parent’s attention.

Rosin: This is Chris Hayes, my guest this week.

Hayes: I mean, I think every kid notices how distracted parents are by the phone.

Rosin: Who’s the meanest to you about it?

Hayes: My youngest.

Rosin: Really? (Laughs.)

Hayes: Yeah.

Rosin: Not the teenager?

Hayes: No, actually, I think the youngest, because youngest children have a real antenna for attention. They come into a family in which they recognize immediately that there is, at some level, a kind of Hobbesian war of all against all for parental attention.

Rosin: I’m Hanna Rosin, and this week on the Radio Atlantic: the war for your attention.

You probably know Chris Hayes best as a host on MSNBC. He’s the author of a new book: The Sirens’ Call: How Attention Became the World’s Most Endangered Resource. And he doesn’t just mean parental attention. He’s talking about attention in politics, commerce, social media—basically, how capitalism found a uniquely human weakness to exploit.

But of course, since the topic is so often seen only through the lens of parents and children, we started out sharing how we can feel like hypocrites when we police our kids’ devices.

[Music]

Hayes: The one that I’ve caught myself doing is: your child asking for screen time when they’re, you know, not allowed to or it’s not normally the time, and giving them, like, a sharp “no”—and then going back to looking at your phone. (Laughs.)

Rosin: Oh, Chris. One thousand percent. Even the fact that we get to use the term screen time, and guess who doesn’t get to use the term screen time. They can’t be like, Dad, you only have an hour of screen time a day.

Hayes: That’s right. And one of the things I write about in the book is that when we think about the state of boredom, or being bored, I think we associate it with being a child. I mean, I remember days in the summer, particularly, where I was a little underscheduled. I was just sort of sitting around—these periods where you feel like, I have nothing to do.

And the reason I’ve come to believe that we associate [boredom] with childhood is, as soon as we are old enough to control our lives, we do everything possible to make sure we never feel it. That’s why it’s associated with childhood: because children don’t have full agency. Once we develop full agency, we’re like, I’m not gonna be in that state. I’m gonna do whatever it takes not to be in that state.

Rosin: Chris writes about how there are two kinds of attention: voluntary attention and compelled attention.

Hayes: So compelled attention is part of our deepest biological, neurological wiring. It’s the involuntary reaction if you are at a cocktail party and a waiter drops a tray of glasses.

[Glass breaking]

Hayes: You can’t help it. You cannot control whether you’re going to pay attention to that. It’s often the case with, you know, an explosion—

[Loud boom]

Hayes: —or the siren that is on top of an ambulance or a cop car as it goes down the street.

[Siren wailing]

Hayes: That involuntary attention is the part of our neurological wiring in which our attention is compelled, independent of our volition and will, as a kind of almost biological fact, due to the fact that we needed to be alert to danger, basically.

And then there’s voluntary attention, which is when we, using the conscious will, flash the beam of thought where we want it to go.

Rosin: So [if] I sit down and read your book, that’s voluntary attention.

Hayes: Correct.

Rosin: Is one better than the other?

Hayes: Well, I mean, I think that, look—involuntary attention is probably necessary for the survival of the species. So in that sense, it’s fundamental, and I wouldn’t say it’s worse. The problem is: So let’s say you’re reading the book. You’ve made this volitional decision, and as you’re reading the book, the little haptic buzz of a notification in your phone goes off.

[Tech vibration noise]

Hayes: Now, you notice that because it’s designed to use the deep circuitry of compelled attention to force your attention onto the physical sensation of the phone.

That is a perfect example of the one-way ratchet of what I call “attention capitalism,” is that the more important attention gets, and the more that people, corporations, and platforms have sort of optimized for it competitively, the more they will try to use the tactics of compelled attention to get our attention, rather than to get the part of us that’s volitional attention.

Now, of course, you still have human will. And in that moment, you’re going to decide, Am I going to take my phone out to see what the notification was or not? But that little moment, that little interruption, that’s pretty new at scale. I think it’s totally new at scale.

And it’s also just absolutely endemic to modern life. It’s our entire lives now, is that wail of the siren going down the street, the clatter of the drop tray.

[Siren wails, glass breaks, phone buzzes]

Hayes: There’s very powerful forces attempting to compel our attention away from where we might want to put it in any moment, because that’s a kind of hack for them for getting our attention.

Rosin: Right. You’re a little less than aware of it. Like, you’re not thinking, I want to look towards the waiter dropping the tray, or I want to look towards the ambulance. You’re just kind of reactive.

Hayes: Yeah, you’re reactive, and you’re at your sort of biophysical base, right? The comparison that I use in the book, and I think this might be helpful for people to think this through, is how hunger works. With food, we have these deep biological inheritances where there’s just universal deep wiring towards sweets, for instance, or fats, because they are extremely calorie dense.

You can exploit that at scale, as McDonald’s has and other food operations, and find that you could basically sell cheeseburgers and salty fries and Coca Cola all over the world, because you’re working on that deep biological substrate in people. But it’s also the case when you ask, Well, what do humans like to eat? it’s an impossible thing to answer, because the answer is: basically everything, right? It’s amazing, all the different things.

And what we see in sort of modern food culture and the food industry is a sort of fascinating kind of battle between these twin forces, right? The kind of industrialized production and fast food that is attempting to sort of find the lowest common denominator, speak to that deepest biological substrate so that they can sell corn syrup to everyone—and then all of the amazing things that people do with food and what food means as culture, as history, as self-expression, as expression of love and bonds.

And I think, basically, there’s a very similar dynamic that we now have with attention, where our compelled attention and our deep wiring is being extracted and exploited by very sophisticated, large, and powerful economic entities.

And yet we still do have this thing called voluntary attention. And you know, what’s sort of amazing, too, about the internet age is, like—and I say this in the book—like, I’ve watched hours of people cleaning carpets, which I find totally compelling and almost sort of sublime and soothing. And I wouldn’t have guessed that that was a thing I wanted to pay attention to.

You know, the internet has opened this cornucopia of different things you can pay attention to. So we’re constantly in this battle between these two forms of attention that are in our heads and the different entities that are trying to compel our attention against our will, and then our own kind of volitional attempt to control it.

Rosin: Chris, were you high when you were watching videos of cleaning carpets?

Hayes: (Laughs.) Mostly not. Occasionally yes, but mostly I have been sober while watching the cleaning carpets, and I’ve still found them incredibly calming.

Rosin: What? (Laughs.) So that’s your ASMR, is carpet cleaning?

Hayes: I don’t know if you’ve seen these, but they take these super, super dirty carpets—it’s like a genre video. There’s a million different ones now, which indicates that that’s not just me. Lots of people feel this way.

Rosin: It’s okay. It’s okay. There’s no judgment in this podcast at all.

Hayes: This is my kink.

Rosin: (Laughs.) You can find your calm wherever you need it. I’m just curious.

Hayes: (Laughs.) So yeah, that’s basically how I think about compelled involuntary attention. And I do think that, because I think we’re more familiar with it in the context of our appetites and hunger, I think it’s a really useful and grounding metaphor, because I think it functions in a very similar way.

Rosin: Essentially, what you’re saying is, the way this works is: We’ve got some biological impulses, let’s say, for example, to want social attention, just to be noticed by others. That’s in us, and that’s fine.

Hayes: Yeah. I mean, I think the reason that it’s so foundational, social attention— and I think it’s slightly counterintuitive because I think people have very different attitudes and personal dispositions towards social attention. Lots of people don’t like it. But the foundational truth about being a human is: We come into the world utterly helpless and dependent, completely, on care. And the thing prior to that care is attention.

And the best way to see this is the child’s wail. The most powerful tool that the newborn has is the cry. And the reason they have the cry is: It’s their siren. It compels our attention. And the reason that it compels our attention, and the reason they have to have the ability to compel our attention, is because without attention, they will perish. And that is our human inheritance. That need from the moment we come gasping into the world for others’ attention—that is foundational to every single one of us.

Rosin: So we have this need for social attention. It’s a basic need. Whether we’re an introvert or an extrovert, that’s not what we’re talking about. We just have this basic need for social attention. What is different about seeking social attention online?

Hayes: Okay, this is really, I think, a key thing to think about. Before civilization, you got social attention from people that you knew that you had relationships with, right? There weren’t really strangers. And you might be able to put your social attention on someone you don’t know, like a kind of godlike figure or a mythic hero that tales were told of, right? So you could put your attention on a person you don’t know, but the social attention you received was all from people that you had a bilateral relationship with. What happens with the dawn of what we might call fame—and there’s an amazing book about this that I cite—

Rosin: Leo Braudy.

Hayes: Yeah, Leo Braudy’s great book. He says Alexander, basically, is the first famous person, and he explains why. But fame is the experience of receiving social attention from people you do not know, and at scale.

Now this is a very strange experience. And the reason I know this is because I happen to live it. And so in the progression of civilization, you start to have famous people, and more and more people can be famous with the dawn of industrial media: movie stars, pop stars, all this stuff.

But it’s still a very, very, very tiny percentage of people that can be known by strangers—that can have social attention being paid to them by strangers. That just generally doesn’t happen for most people, and most people are gonna have received social attention from people they have relationships with, and they might put their social attention on all sorts of public figures—the president or celebrities and other people—but they’re not getting it from people they don’t know.

That just is a very tiny sliver of humans that can have that experience, and now it is utterly democratized for everyone for the first time in human history. I mean, it’s genuinely new, genuinely a break, has not happened before. Anyone can have enormous social attention from oceans of strangers on them. You can have a viral moment online. You can cultivate a following. This experience of social attention from strangers—precisely because it is so at odds, I think, with our inheritance—is weird and alienating. And there’s a bunch of ways it is. One of the ways it’s alienating is that we are conditioned to care what the people we love think about us.

We’re conditioned to care if we’ve hurt someone that we have a relationship with. But it’s very different if you’ve insulted or hurt just a total stranger who’s saying mean things to you, or you’ve disappointed them, or they’re angry at you. That comes into you, psychologically, indistinguishably from it coming from kin or lover or friend.

Rosin: So we just basically, our—I don’t know if I want to call them our intimacy compass—something gets scrambled. We just don’t have the category to react or manage that category of social attention. We just don’t know what to do with it.

Hayes: Truly, there’s a kind of clash here between the data set we’re trained on, if you will, and what we’re encountering. And the reason—again, this is a place that I really know, right? I didn’t used to have people come up to me on the street, and then I became famous enough that people did. And I’ve experienced all the ways that that’s strange and alienating, and I’ve given a lot of thought—partly as a kind of full-time psychological undertaking, so that I don’t go crazy, because I do think it’s kind of distorting and madness inducing in its own way.

And what we’ve done is basically democratize the madness-inducing aspects of celebrity for the entire society. Every teenager with a phone now can be driven nuts in precisely the way that we have watched generations of celebrities and stars go crazy.

Rosin: You mentioned Bo Burnham in your book and the movie he made, Eighth Grade. When he talked about why he made that movie, he said that same thing. He had a similar experience to you—he went viral at a pretty young age—and then he realized that every eighth grader was having the kind of experience that he had had, which he found so alienating but that had now become a common experience. Can you read a paragraph for me from your “social attention” chapter, which I think is relevant to this conversation?

Hayes: Sure. I’d love to.

Rosin: Just the paragraph that starts with “the social media combination.”

Hayes: “The social media combination of mass fame and mass surveillance increasingly channels our most basic impulses—toward loving and being loved, caring for and being cared for, getting our friends to laugh at our jokes—into the project of impressing strangers, a project that cannot, by definition, sate our desires but feels close enough to real human connection that we cannot but pursue it in ever more compulsive ways.”

Rosin: That really hit me. It’s a dark vision. It’s like they tap into our thirst perfectly but then just keep the glass of water just out of reach, you know?

Hayes: Well, and I think that’s because there’s something holy or sublime in actual human connection that can’t be replicated.

Rosin: Yeah.

Hayes: —that, you know, the thing that we’re chasing is something ineffable and nonreplicable. And it’s the reason we chase it, because it’s what makes life worth living, at a certain level, is to be recognized and seen. Relationships of mutual support and affection and care with other people—you know, that’s it. That’s the stuff of it. And we are given a tantalizing facsimile that some deep part of us cannot help but chase, but it can’t also be the real thing.

Rosin: When we come back: who exactly is benefiting from this attention economy, why it feels so bad for the rest of us, and what we can do about it. That’s after the break.

[Break]

Rosin: We’re back. And we’re starting with something that everyone who gets social attention from strangers learns.

Hayes: What you quickly find is that positive compliments and recognition—they just sort of wash off you. But the insults and the negativity cuts and sticks. I mean, do you not feel that way as someone who has some public profile?

Rosin: Yes, yes. It’s happened to me, and I was so surprised at how hurt I was. And when I look back, I think, like, I literally don’t really know those people. Like, there’s just something so, Ugh. It’s, like, ancient, the feeling—like you’re being pilloried or something, like you’re in the public square—and it feels terrible, and I don’t understand why. Like, I could just shut my computer, and it’d be gone, but it does not feel that way, internally.

Hayes: Yeah, and I can think of days I spent in that haze. You know, when you come out of it, you’re like, Why did I let myself feel that way? Like, Why did I spend a whole day? Like, Why was I—I can even think of moments of being distracted from my kids because I was sitting there and feeling wounded and hurt and ruminating on a mean thing someone who I don’t know said online. And I’m distracted, and my attention’s on that instead of my wonderful child sitting on my lap, you know? (Laughs.)

Rosin: Well, I think the lesson to learn from that is what you’re talking about in this book, is how vulnerable we are. Even when it doesn’t make intellectual sense, there is some way that we’re vulnerable in this moment. We can’t completely control our reactions and choose, voluntarily, not to pay attention to this thing. We don’t have that kind of agency—not yet, anyway.

Hayes: That’s exactly right. You know, attention is the substance of life. That is what our lives add up to. It’s in every moment, we are choosing to pay attention to something, or we’re having it compelled, but we’re paying attention to something. And that’s what adds up to a day and a week and a month and a year and a life.

And it’s also finite. You know, this is one of the key points I make, is that part of the value—and the reason it’s so valuable, and the reason there is such competition for the extraction of attention—is that unlike information, it’s capped. It’s a finite resource. It’s that people are figuring out how to take one or two extra slices of the pie, not grow it. And that’s the other thing that leads to the feeling of alienation and the feeling that something has been taken away from us because of its finitude.

Rosin: Well, let’s talk about attention as a resource, because we’ve talked a lot about how it works in us, the individuals, and permeates our lives, but I want to talk about a broader social context. You make this very compelling analogy between our attention problem and Marxist ideas. I did have this image of you at a bookstore one day, like, being bored and coming across a copy of Das Kapital, and like, a lightning bolt goes off. Yes! It’s like Marx but for the information age. It’s a really compelling analogy. Can you explain it?

Hayes: Yes, I mean, you know, I started reading Marx in high school, which is a weird thing to say, but it’s true. Here’s the basic argument Marx makes about labor.

So he’s living at this time where there’s this new thing called “wage capitalism,” “wage labor.” People, you know, sell their labor on a per-hour basis.

Rosin: And how is that different from people’s relationship to labor before? Just so we get the analogy.

Hayes: Totally. So let’s think about a cobbler, right? You’re in the preindustrial age. You got your little shop. You make a shoe. And there’s a few things about this process that are distinct. One is, there’s a telos; there’s an arc to it. You start with the raw materials, then you put them together, then you put the sole on, then you put the finish on. In the end, you have a shoe, and you own that shoe, and then you sell it in your store in exchange for money.

Now, compare that experience to the wage laborer in a shoe factory who is at one position stamping soles 10 or 12 hours a day, six days a week. In both cases, you could say that sort of preindustrial cobbler and the shoe-factory worker are both laboring.

But now there’s this distinct thing called “labor as a commodity” that has a wage price and a set of institutions to take the labor in exchange for that wage, and a set of technological and economic developments that produce a situation in which you go from being the cobbler, who makes the whole shoe, to being in a factory 12 hours a day, stamping a sole.

And Marx talks about this as the root of alienation. You’re just alienated from yourself, from your humanity. You’re not doing a recognizably human thing. You’re doing something that feels robotic and mechanical, but also that the value that you’re creating is literally outside of you. I mean, to go back to the cobbler, when he makes the shoe, he actually owns the shoe. If he wanted to make the shoe and give it to his kids, he could do that—and sometimes cobblers would, right? But the factory worker doesn’t have that. The factory worker is alienated from the value of the shoe. He’s stamping the sole, and when it goes down the line, it gets sold off somewhere else. It’s literally outside of him. It’s alien to him.

So this is the basic Marx labor theory of value, right? That you have this transformation in society, economic conditions, institutions that took a thing that was fundamentally human—effort, toil, whatever you want to call it—and transformed it into this new thing that was a commodity that could be priced and bought and traded.

Rosin: Called labor.

Hayes: Called labor. And I think, basically, there’s something happening right now with attention that’s similar. People have always paid attention to things, and that attention has always had some value, and there’s people who have utilized that value for all kinds of purposes—P. T. Barnum, Mark Antony: “Friends, Romans, countrymen, lend me your ears.”

You know, there’s always been a value there, but we’ve entered an age that I think is similar to the industrial age—but for attention—where a set of institutions, technologies, and arrangements have produced a world in which our attention is being extracted from us, commodified, and sold at a price, often in millisecond auctions to advertisers.

And that extraction leads to a profound sense of alienation, similar in some ways to that sense of alienation and that alienation of the laborer. And yet there’s one more way in which it’s even more insidious, I would argue, which is that compelled, involuntary aspect.

So labor can be coerced forcibly. I mean, you can, you know, use a whip or a gun to make someone do something. If you put a gun to someone’s head and say, Dig a ditch, you’re coercing. You’re forcing that labor. But they know they’re doing it. If you fire a gun, your head will snap around before you know you’re even doing it.

And so because of this involuntary, compelled aspect of our biological wiring for attention, this new competitive attention capitalism is working to extract it at such a deep level that it’s compelling it, at some way, before we’re even able to make a volitional choice about it. And that feeling is this profound, deep feeling of alienation.

I think this alienation is so ubiquitous. I think we all feel versions of it, and I found the concept of alienation, which I always found a little foggy in the past, very clarifying. Something that should be within us is outside of us, and that within us is my control over my own thoughts. That’s the thing that should be within me. That’s the nature of consciousness itself, what it means to be of free will, and yet that is being extracted and commodified and taken outside of me.

Rosin: So we’re not exactly compelled. Nobody’s holding a gun to our head. So I don’t know that you could say it’s worse. It’s just more confusing because we are participating. So in some sense—

Hayes: Yes, that’s a good point. Yes, there’s not the same sense of violation, right? Because in some ways it feels like we’re consenting. I think you’re right. That muddies it and also gives us a weird feeling of shame and guilt.

Rosin: One consequence we’re seeing is the kind of people who thrive in this age—obviously, Donald Trump. You mention Elon Musk a lot in the book, which I think is a specific point. Like, the Trump point is kind of obvious. Like, why someone like that thrives in an age of attention, I think we intuitively understand that. Musk is a little more complicated.

Hayes: Well, look—here’s what unites them, right? It’s fundamentally: These are people that understand that attention matters more than anything, even at the cost of negative attention. And this is really the key thing to understand, I think, that has really warped our public discourse. The thing that separates social attention from other, more elevated forms of human interaction is that it’s necessary but not sufficient.

Someone flirting with you across the bar is social attention, a pleasant kind. Someone screaming at your face because you’re too close to them on the subway is also attention. And that’s the weird thing about attention. It could be of either valence and everything in between.

In a world that increasingly values attention over all else, what you get is you unlock the universe of negative attention and its power, because if all that matters is attention, then negative attention is just as good as positive attention. Now, most of us are conditioned to not like negative attention. But there’s a certain set of people who, either through a sort of intellectual understanding—sometimes this happens, where you’ll read interviews with creators who are like, Oh yeah. Once I started trolling, I got more views, right?

So part of it is: The algorithms select for negative attention. But part of it is just a deep brokenness in their personality, and I think this is true of both Donald Trump and Elon Musk, to seek out negative attention because it’s attention. And this creates a kind of troll politics writ large, and I think we’re sort of watching, in some ways, the Musk era supplant the Trump era, if that makes sense?

Rosin: What do you mean? What do you define as the Musk era?

Hayes: So most politicians, they want positive attention, and if they can’t get positive attention, they want no attention and then, underneath that, negative attention, right? So it’s like, you want people to like you and know your name, or you want to stay out of the news. And what Trump realized is that, no, it doesn’t matter whether it’s positive or negative, as long as you’re getting attention,

Musk has now taken this insight to actually having captured a platform that he purchased, where he is now operationalizing this at scale. So it’s like the higher synthesis of the insight of Trump. He’s understood that attention is the most valuable resource, and this is true in monetary terms. I mean, look at what’s happened—this I actually get wrong in the book because I was writing it too early.

Look what happened: He buys Twitter, okay? He buys it for $44 billion. So he gets it so he could be the main character on this. He so obsessively pursues this attention that it destroys the actual value of the entity. So lighting $25 billion on fire, right, all in this sort of broken pursuit of attention. But then, using this attention and using the platform, he helps elect a president who puts him, essentially, at the seat of power that produces an enormous boon in his personal wealth because people are like, Oh now he is close to power, and it has netted him hundreds of billions of dollars in his personal value.

And it’s the most incredible allegory for the entire attention age. Here are these two guys, Donald Trump and Elon Musk, who seem to recognize more than anyone that attention is the most valuable resource and that you should do whatever you can to pursue it, even if that means acting like a maniac. And it’s kind of worked for both of them.

Rosin: That seems so huge and overpowering. I mean, there’s a way of listening to you and reading this book and fully seeing it. Like, we can see the train wreck in our own lives and sort of out there in the world. But you might read the book and think, Okay, this is my own ordeal—like, something I have to combat. I have to put my phone away. I have to chain myself to the trees or whatever.

Hayes: Yeah. I mean, so the first thing I would say is that the cause for optimism, which I have some, is that I feel this is pretty untenable and unsustainable, because I think the sense of exhaustion and alienation so ubiquitous and profound that I don’t think it can keep going that way. And actually, I think that there’s unbelievable latent energy for something different than what this is.

There are ways that attention can still be bought and sold that isn’t this particular to-the-second, algorithmic, infinite scroll that we’re all now trapped in, right? So I think you are going to see flourishing of alternate means. And you see this, I mean—Substack, the longform newsletter. We’re seeing it happen. Like, Substack is growing because people do want to read long things from people that they think are interesting, and not just algorithmic serving of short-form video. That’s a different model. It’s a for-profit model, but it’s a different model and, I think, a better one and one that’s less extractive and alienating for our attention.

You know, vinyl records were completely supplanted by cassette tapes and then CDs. And then, starting about 10 years ago, they started growing, and they’ve been growing every year, and they’ve been growing at huge paces, and there’s now a thriving vinyl industry. And the reason is that, I think, when you are streaming music, you have the twitchy, short-form attention extraction of going to the next song, or maybe I want something else. When you put on a record, you commit, right?

The commitment mechanism is the triumph of the volitional will over the involuntary attention compulsion, right? It’s like Odysseus lashing himself to the mast, right? We make a commitment: I’m going to read this email from this Substacker I subscribe to. I’m going to listen to this album, which I’ve put on vinyl. These commitment methods—and, again, they could be in for-profit context—I think we are going to see flourishing and more energy behind that.

And the other example I use, because I talked about hunger before, is to think about what’s happened with how opposition to the sort of corporate, industrial food system the U.S. has worked. So you’ve had an entire thriving ecosystem and set of businesses built up in opposition to precisely the forms of extractive and exploitative food capitalism that I think is parallel to attention capitalism.

And I think we are going to see that. There are people that market dumb phones now, and I think there’s gonna be a lot more of them. I can imagine a world in which, in the same way that a certain kind of parent doesn’t feed their kids fast food, you start to see that more and more, that people kind of just opt out of this entire system, to the extent they can.

Rosin: Do you think we’re being exploited, and we should be mad about it?

Hayes: Yeah, I do. I do. I think that there’s something pretty dark and insidious about how the major platforms, particularly, are engineering this kind of attention compulsion. And I think we are going to enter an era in which we start regulating attention seriously. You’re seeing this call—you know, in Australia, they’ve already banned social media for children under 16. You’re going to see more and more calls for that. But also, I can imagine other ways that we try to regulate it, whether it’s hard caps—regulated hard caps on screen time. I mean, that sounds so crazy and kind of un-American, but I don’t know. Maybe that’s a good idea!

Rosin: Well, I take hope in the schools. I mean, schools, not just in the U.S. but all over the world, are starting to get pretty serious about no phones at all during class time, which is radical. If you’re a teenager, that’s a radical change in your life. So that’s hopeful. I will say one thing your book has really done for me very concretely is make me appreciate my group chats.

Like, after I read your book, I went back and I thanked—you know, I thought, Oh, you know, I’ve got a couple of group chats that are so fun. And I just went and thanked everybody on them.

Hayes: That makes me so happy to hear that, because this is a book written by a person who genuinely loves the internet and has loved the internet most of his adult life. I mean, I’m an early internet adopter, and what the group chat is doing is: It’s using technology to connect actual people that know each other.

And there’s lots of stuff that could happen in group chat that could be messy or bad, because humans can be mean or gossipy to each other. But fundamentally, there’s not an interposition of some entity trying to monetize it. It’s a noncommercial space. It’s a technology that’s a noncommercial space.

It feels like the early noncommercial internet. You just go on with your friends, and you make jokes, and you share stuff, and that’s it. No one comes in with a five-second ad. No one tries to extract your attention against your will. It’s a set of bilateral relationships, voluntarily entered to, in a space that is noncommercial.

And that’s the other thing we really need. Like, we have physical public spaces that are noncommercial, and they are so vital, whether that’s schools or libraries or parks. Increasingly, the internet is just totally captured by commercial spaces. And it used to be entirely noncommercial, and now it’s entirely commercial. And those commercial spaces will ultimately further the kind of extractive attention capitalism I’m critiquing. But there are ways to create—and the group chat right now is the chief among them—noncommercial spaces of digital connection.

Rosin: Okay, everyone listening, go do more group chats. Just go engage in your group chats. And Chris, thank you so much for joining me today. Thank you for writing this book and explaining this all to us.

Hayes: Thank you for reading it. It really means a lot to me and thank you for having me.

[Music]

Rosin: This episode was produced by Kevin Townsend and edited by Claudine Ebeid. Rob Smierciak engineered, and Ena Alvarado fact-checked. Claudine Ebeid is the executive producer of Atlantic audio, and Andrea Valdez is our managing editor.

My thanks again to Chris Hayes for joining me. His new book is The Sirens’ Call: How Attention Became the World’s Most Endangered Resource.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

Addiction comes in many forms and a lot of them are perfectly legal.

Daily, I fight the urge to scroll—for hours—on various social-media apps, yet I can go months without drinking alcohol and not even think about it.

The question of whether to ban harmful behaviors or substances is one laden with competing priorities: How intrusive is the government intervention? How harmful is the substance? Would banning it even work to curb the behavior? What about the economic impact of a ban? What sorts of revenues can be gained from taxation instead?

On today’s episode of Good on Paper, I talk with the journalist Danny Funt, who has been reporting for years on a behavior that’s come under much scrutiny lately: sports betting. Renewed debate over bans on sports betting erupted into public view nearly seven years ago in a pivotal Supreme Court case. The decision opened the door to a variety of new state legalization schemes and the outcomes have been mixed, at best. Although states may have stumbled onto a new source of revenue (albeit weaker than some were expecting), it has come at a cost to gamblers’ financial and mental health. The results have turned even vocal proponents into skeptics.

“I interviewed Charlie Baker, the former governor of Massachusetts who signed the bill legalizing bookmaking there in 2022, and then a few months later became president of the NCAA and has become a really vocal champion for limiting the amount of betting on college sports, particularly in light of the brutal harassment that college athletes and coaches get whenever their performance costs someone a bet,” Funt recalled. “It’s honestly horrifying, the sort of stuff they see on social media and in real life. And he has said point-blank, ‘I wish, in hindsight, this had stayed in Las Vegas.’”

The following is a transcript of the episode:

Jerusalem Demsas: The Super Bowl is coming up, and so today we’re talking about the most important part of sports: gambling.

In 2018, the Supreme Court struck down a federal ban on sports betting that spurred four years of nonstop ads enticing me and you and everyone I know to spend all our discretionary income on FanDuel or DraftKings. At the time, advocates believed that the revenue streams that could come from sports betting were too good to pass up. After the Great Recession, states were cash-strapped and hungry for new sources of money.

States have unevenly legalized, meaning in some places, you can log onto your phone to place a bet, and in others, you might still need to go to a physical location. The Court left open other pathways for the federal government to curb or ban sports betting, and as many of the negative impacts of gambling have metastasized, more policy makers are questioning whether legalization is worth the revenue.

My name is Jerusalem Demsas. I’m a staff writer at The Atlantic. And this is Good on Paper, a policy show that questions what we really know about popular narratives. My guest today is Danny Funt, a journalist who has tracked the rise of sports betting for The Washington Post and is now working on a wide-ranging book on the topic.

[Music]

Demsas: Danny, welcome to the show.

Danny Funt: Thank you for having me.

Demsas: So I have actually never bet on sports. I grew up in a Christian household—I am Christian—and it’s just not a thing that my parents ever allowed. We couldn’t even make dollar bets at home. Like, it was just not allowed. And I feel like I knew later on that I had kind of an addictive personality. So I was like, I’m not going to do this. I’m just never going to get into betting or gambling. Have you bet on sports? Is this something that you do?

Funt: Oh yeah. I’m trying to be more honest about that. I used to be like, Well, if you were a restaurant reporter, you’d have to eat out. You’d sort of be obligated to see what the culinary scene is like. So I do the same with sports betting. But truthfully, I was betting on sports long before I ever wrote about it.

I will say that the more you learn about how significant the house’s upper hand is, it definitely gets in the back of your head, and I do a lot less now just knowing I don’t stand a chance.

Demsas: How significant is it?

Funt: It depends on what you’re betting. The standard is actually pretty low. They’ll win $5 for every $100 you bet. But nowadays, that’s getting jacked up. So you might have heard of things like parlays. The parlay hold percentage, which is like the house revenue or the house edge, can be as high as 20 percent. So you’re getting beat pretty bad if you bet a lot of parlays.

Demsas: So sports betting, I feel like, I really did not hear a lot about, other than just when the World Cup is on, and your friend might bet you 20 bucks about the outcome or something like that. And now I feel like it’s everywhere. I feel like I’m seeing ads everywhere. I feel like every time I look over on the Metro, like, there’s some 17-year-old guy on DraftKings—well, let’s hope he’s 19, not 17. But it feels like it came out of nowhere. What happened?

Funt: It really did. That’s really what got my attention: It just felt like, overnight this went from something that we had all been taught was this existential threat to sports, that the professional leagues and the NCAA would never support—there were basically a century’s worth of scandals involving gambling that motivated that concern—and then, suddenly, there was a Supreme Court decision in 2018 that struck down a federal ban on bookmaking outside of Nevada.

And that really was a starting gun for all of these states to say, Hey. This is a way we can raise money and cash in on this opportunity. And it was incredible how night and day it was, where what I described as this existential evil was suddenly repackaged as this wholesome way of enjoying sports that every sports fan ought to consider.

Demsas: So take us back to 1992, where that federal ban was enacted. It’s called the Professional and Amateur Sports Protection Act. What led to that effort? Who was pushing for it, and why did they think it was necessary?

Funt: Yeah, I was surprised to learn that it was the professional sports leagues, mainly the NFL, that went to Congress and said, Hey—we need this. So a lot of states back then were facing severe budget deficits. You know, it’s the tail end of the Reagan era; there’s a lot of resistance to tax hikes.

And naturally, when you need to raise money, but you don’t want to raise taxes, states will look at gambling. And there was sort of a groundswell of loosening the laws around tribal casinos and state lotteries. And a lot of states began looking at, basically, a version of state-sanctioned sports betting, where a state lottery is giving people the chance to wager on sporting events.

And the sports league said, We hate this idea. We’ve allowed it in Nevada because it’s been there forever, but we don’t want this to be the way that our fans engage with our product.

Demsas: Why? Why were they opposed?

Funt: For one, the 1919 Chicago White Sox scandal, where, famously, the team rigged the World Series in cahoots with gamblers—that is front and center still. Pete Rose had just been banned for life for betting on baseball as a player and as a coach. Really every decade, if you look back in the history books, there’s a major scandal involving college sports or professional sports or whatever. Beyond that, they just thought, We like the idea of fans liking the games for the games’ sake, and if they’re looking at it through this cynical gambling lens, it’ll kind of cheapen their relationship with sports and diminish our product.

Demsas: That’s very altruistic, right? I mean, I would imagine these sports leagues are just like, What can make us money? You know what I mean?

Funt: Definitely. At the same time, that does make them a lot of money. Think of all the jerseys and pennants and other merch that people buy because they’re lifelong sports fans. It fuels a lot of irrational, obsessive behavior. And then again, so does gambling.

So you can understand why it was very tempting, over time, for the leagues to flip-flop and come around on that. But the Senate and the House held these really robust hearings to evaluate the threat of gambling, the benefit that state-sanctioned gambling might pose. And it was just so striking, to me, that they laid it all out on the table in the early ’90s, and then fast-forward: 25 years later, there was really none of that. It was just, Okay, let’s cash in.

Demsas: So Nevada, you mentioned, has always been exempt from PASPA. What has been their experience?

Funt: Around the ’50s, when casinos were taking off in Nevada, sports betting was sort of an amenity, kind of like an all-you-can-eat buffet, you know? It’s just one more thing to draw people in so that they go to the table games and the slot machines that really make money. So in a lot of ways, sports betting was an afterthought.

And yet, many of us thought, If we ever wanted to bet legally on sports, that’s the place to do it. So people would schedule March Madness trips to bet on college basketball, or they’d go during the Super Bowl to bet on that. So it was a pretty big draw, but it was also very marginal in terms of the bottom line for Nevada gambling operators.

But gambling on sports still existed well beyond Nevada in the U.S., because there’s this thriving black market. And one of the big arguments for legalization, just like with cannabis, was, People are going to find a way to do it, so let’s bring it above board, tax it, implement consumer protections. And at least that was a pretty convincing argument in favor.

Demsas: You mentioned the Supreme Court decision, Murphy v. NCAA. That’s the Supreme Court decision that basically strikes down this federal ban. What was the legal argument at issue there? Why did the Supreme Court find that the federal government cannot ban sports betting?

Funt: So crucially, they very explicitly said they can ban sports betting—they had just gone about doing it with a defective bill. So naturally, Supreme Court decisions tend to get oversimplified in the public conscience, but this one is so crucial because sports betting’s advocates took the decision and said, Aha! The Supreme Court has given the green light for sports betting or okayed sports betting.

Really, the case turned on a fairly obscure Tenth Amendment concept about states’ rights. And sports betting was the focus, but it was also kind of beside the point. So New Jersey said that what the federal government has done, in essence, is said, We want to ban sports betting, but we don’t want to regulate it. So we’re going to commandeer the states to do the federal government’s bidding. If they had legalized sports betting before 1992, that’s grandfathered in; it can remain on the books. If they hadn’t, they’re prohibited from changing their mind and legalizing it.

So this argument before the Court wasn’t, Should the federal government be allowed to ban sports betting? It was, Should they be able to tell the states that if they have an existing law, they can’t change it? And, you know, it sounds like the most thrilling Supreme Court oral argument. It was actually pretty dry because it’s so obscure in that way. But the effect was to overturn this ban that had been on the books for a quarter century.

Demsas: What was the state interest in legalization? This is Murphy v. NCAA. That’s Governor Phil Murphy of New Jersey, a Democrat. Why was he so hell-bent on taking this on?

Funt: The funny thing is: It was really Chris Christie, his predecessor, who was hell-bent on taking it on, and it really annoys Christie, who views bringing sports betting to New Jersey as one of his crowning achievements. It pains him to this day that the title of that case was updated to reflect Murphy because he took office before the decision came out.

But they had this long-standing economy, mainly in Atlantic City, that was really struggling. They looked at Nevada and were quite envious that sports betting brings people to the state around these major sporting events, year after year, and they said this would be a way to revitalize Atlantic City.

So the argument they brought to the Court wasn’t, Let’s have online sports betting across the country. It was, Let’s have in-person sports betting in these casinos in Atlantic City to jumpstart this ailing economy. As you can imagine, after that, all these states said, Hey—we also could use a lot of tax revenue and jumpstart our economies. Especially during COVID, when so many states were facing pretty dire budget deficits, they said, This is a fairly easy way to snap our fingers and have access to this influx of cash.

And that tends to happen a lot with gambling—is you’re facing some sort of economic or state budgetary issue, and this is a quick fix. So once New Jersey did it, and Delaware and Pennsylvania and a number of other early adopters, there was this ripple effect, where states look to their neighbors and say, Hey—they’re making money off this. We feel like chumps because we’re not. Let’s get on board. And the bandwagon really got off and running.

Demsas: So one thing that’s interesting is that—I’m confused why there’s been such a big focus or why sports betting has been so central to this story, when it feels like all types of online gambling are legal in lots of places now. So can you help me understand why that’s been so front and center?

Funt: I mean there’s so many video games or phone-based apps where it’s like, Hey—do you want to buy some tokens with real money? And then you’re playing with tokens, and then you convert the tokens back to real money, so it’s very sly.

There’s this whole phenomenon of what are branded as sweepstakes, where it’s essentially a loophole to allow people of all ages to risk money on sports, but it’s not called gambling. And you might remember: There’s a long history of things finding loopholes to offer gambling by a different name, most notably the whole daily-fantasy-sports boom that paved the way for sports betting.

So you’re right. It is part of a wider phenomenon. It’s interesting that true online casino gambling, like slots and roulette and poker, was predicted to follow from legal sports gambling. That was what a lot of these companies were banking on. And although about a half dozen states have legalized it, it hasn’t caught on quite as quickly as some of their investors’ hopes, and we could get into that.

Demsas: Yeah, why not?

Funt: The main reason is that the brick-and-mortar casinos think it’ll cannibalize their business, that if people can bet on those games on their phones, they’re not going to bother to make the trek to a retail casino to do the same thing. So I still think that’s going to be in the headlines a lot in the coming years, as states look for more ways to bring in tax revenue.

But to your question about why sports betting seems so dominant, part of it is just: The advertising is unbelievable. These companies are spending billions of dollars every year to get it in front of potential customers in as many ways as possible. As you were saying, you see it on the train. Same here in North Carolina. Billboards, signs downtown—everywhere you look there’s an appeal to get you to start betting on sports, not to mention all the TV ads. So the marketing is just overwhelming.

And then beyond that, it is startling, in that this was seen as something that was done in the shadows, and now it’s so mainstream and really being rammed down people’s throats in a way that a lot of people are quite concerned about.

Demsas: So what is the landscape now, right? Like, after Murphy, states had to pass their own legalization schemes. Right now, D.C. and 27 states allow online sports gambling, and there’s some regional concentration here that I thought was interesting—basically, the entire Northeast and the mid-Atlantic, as well as the Midwest. But lots of the South hasn’t. The Pacific Northwest hasn’t. California and Texas haven’t. What kind of explains this regional variation?

Funt: I think in the Northeast, state lotteries are so deeply rooted. Massachusetts, for example, has the highest-grossing state lottery per capita. So I think it’s easier to transition people into a new form of gambling. In a lot of parts of the country, like California and Texas, tribal interests are so powerful—they’re resisting anything that would threaten their business. In parts of the South, there’s a strong conservative Christian aversion to gambling still, although I think that’s dissipated a lot from one of the main reasons why the country didn’t adopt more gambling sooner. So yeah, it’s a lot of cultural and political reasons.

Demsas: One story of yours really kind of shows how haphazard the legalization process has been. Can you tell us about the Abunai gambler in D.C.?

Funt: Yes, so as you mentioned, D.C. is one of the places that legalized sports betting. Like many places, they did it quite hurriedly and sort of made things up as they go. And one interesting decision the D.C. government made was to have a city-sponsored sports-betting operation, as opposed to letting these companies like FanDuel and DraftKings run the show. So you could bet through those companies at stadiums and arenas, but if you are out and about on your phone or at a lot of these betting terminals in cafés and restaurants and bars, you are betting with a city-sponsored sportsbook called Gambet[DC].

And these terminals—they sort of look like ATM machines. They popped up all over the place, including at this tiny poke shop called Abunai. And one of the interesting things about betting terminals that professional gamblers were quick to pick up on is: Unlike if you’re going to a brick-and-mortar sportsbook, where you give your ID and they pay close attention to who it is betting, you bet anonymously through these terminals. So if you’ve sort of cracked the code and figured out an edge, you can bet anonymously, basically limitlessly, through these terminals and make a killing.

And this one guy found deficiencies in the odds in this poorly run city-sponsored sportsbook. It’s kind of incredible how bad the odds were compared to the rest of the market. Like, it didn’t take a genius to pick off vulnerable games to bet on. So he just finds a list of places in the city that have these betting terminals. Abunai was the first alphabetically on the list. So he says, Okay, great. They have a nice owner and staff, who didn’t mind him basically turning it into his home office.

And day after day, he would just dump cash in this machine and bet as much as he could—so much so that it swung the entire city’s betting numbers so that an overwhelming amount of money was being bet through this one store. He was winning so much that the entire city-run sportsbook was net negative for an entire month, which is unheard of. We all know the house always wins. D.C.’s sportsbook was run so poorly the house lost, in a month.

Demsas: How does that happen? Like, what is going on there?

Funt: So basically, sports-betting odds are often like efficient markets. So just like it’s really hard to beat the stock market, it’s really hard to beat who’s gonna win, you know, a football game or a basketball game, over the long haul, because, basically, the world’s collective wisdom is informing the spreads and the odds on these games.

But the people who are running Gambet[DC], this D.C. sportsbook, were very slow to update the odds. Sometimes, they would just have errors in how they input the information, so they just clearly have the equivalent of a typo in inputting the odds. Just not a lot of oversight. Even though it’s a pretty airtight business, you still need a lot of smart people running it and automation to manage it.

So this guy just picked off all these bad lines and bad odds. And statistically, he gained the upper hand, because if Gambet[DC]’s odds are way out of sync with the rest of the market, chances are the rest of the market’s right.

Demsas: So you literally just have to look at what the market is telling you, what the odds are in other places, and then just go sit down at Abunai Poke and just say like, All right, looking at my phone, what’s going on, on DraftKings or whatever, and then just do that.

Funt: Precisely. He was betting on sports that he didn’t follow at all. He had no expert insights into them. It was just, A respected sportsbook has the odds at this number. Gambet[DC]’s are off in this way. I’m gonna err on the side of the respected sportsbook and bet against Gambet[DC]. And it was hugely profitable, at least as long as he got away with it.

Demsas: Do you know how much money he made?

Funt: Yes, so thanks to some public records that were turned over, only over the course of three months, he profited more than $400,000—pretty unheard of, even for an incredibly successful bettor. That rate of return is just remarkable.

Demsas: Wow. So I went down a rabbit hole, when I was researching for this episode, about American history on sports gambling. And I did not know the role of Attorney General Bobby Kennedy—the OG Bobby Kennedy—his crusade against sports gambling. And learning that, kind of in the middle of the 20th century—you touch on this a little bit, but—that the real focus on outlawing sports gambling was about combating organized-crime syndicates.

Bobby Kennedy wrote an article in The Atlantic in April 1962 about this issue. And just quoting from it:

As I sit down today to write this article, a business executive with an industrial firm on the Eastern seaboard is telephoning a bookmaker to place a fifty-dollar bet on a horse race; a factory worker in a Midwestern town is standing at a lunch counter filling out a basketball parlay card on which he will wager two dollars; a housewife in a West Coast suburb is handing a dime to a policy writer who operates a newsstand as a front near the supermarket where she shops.

These people, and millions like them who follow similar routines every day, see nothing wrong in what they are doing. Many of them can afford the luxury of this type of gambling. They look upon it simply as taking a chance.

He continues:

But they are taking a chance which the nation and its economy cannot afford. They are pouring dimes and dollars day by day into a vast stream of cash which finances most illegal underworld activities. The housewife, the factory worker, and the businessman will tell you that they are against such things as narcotics, bootlegging, prostitution, gang murders, the corruption of public officials and police, and the bribery of college athletes. And yet this is where their money goes.

So I did not have a sense that this was a big part of the modern conversation around sports gambling. Is this kind of resolved, or are we still worried about gambling, kind of, going to these underworld activities?

Funt: Yeah, first of all, it’s a great article you turned up. I’m excited to find it myself and read it. That was definitely one of the arguments for legalizing sports betting around 2018, after that Supreme Court decision, because a huge amount of money was being bet through offshore sportsbooks that operated illegally online, taking tens of billions of dollars in wagers from Americans. And there was some evidence that the criminal syndicates that were operating those sportsbooks did a bunch of other criminal activity.

So just as RFK was saying, you’re, in effect, patronizing those sorts of criminal activities. That’s not always the case. Some of them were just Americans who were bookmakers in the U.S. and got tired of getting arrested, so they went to Latin America and set up websites where they could take bets. It wasn’t quite as sinister as that. But at least as the argument went, it was a real boogeyman, that you’re funding criminal organizations, and, Why not fund taxed, legitimate companies by making this legal? So yes, that was definitely a significant argument.

And I think as far as that kind of conscious capitalism goes, well, the sportsbooks that operate today definitely aren’t, you know, also selling drugs and prostitution and all those things. There definitely is some hand-wringing among people of, Does gambling exploit vulnerable people? Do we know that this is making problem gambling more prevalent? And by betting safely, are you still, in effect, funding companies that take advantage of people? So it’s not quite as potent as the argument RFK laid out, but it’s definitely still relevant.

Demsas: And what has the impact been on legalization? Has legalization reduced off-book gambling. Can we even really measure that?

Funt: So you’re right. It’s impossible to know exactly how much gambling is going on under the table. It always has been. I think some of the estimates were inflated to make the argument seem more convincing, but it by no means has eliminated it or even put the dent in it that a lot of the advocates for legalization promised.

Again, in 1992, they looked at all these different types of cause-and-effect things to think about, and one of them was: If you legalize an illegal activity, do you snuff out the black market, or do you just grow the pool of people doing it and, in fact, actually convert some people who might not have been doing it, who are then going to look to the black market, for a variety of reasons? So when it comes to sports betting, yes—there are definitely those offshore, illegal sportsbooks that are hurting because of this.

But there are also people who took up sports betting because they saw ads everywhere and all these generous new-customer offers and started legally, and then they said, Hey. There’s a bunch of different reasons why betting illegally might be advantageous. Maybe I don’t want it showing up on my bank statement. Maybe I don’t want my winnings taxed. Maybe I want to be able to bet much more illegally than you’re able to do so legally, if I’m a winning bettor. So yeah, in some respects, it’s put the offshore business on the ropes, and in other respects, it’s sort of created a funnel of new customers for them.

[Music]

Demsas: After the break: what’s gained and what’s lost in states where online sports betting is legal.

[Break]

Demsas: I want to delve into the welfare harms of people who are engaging in sports gambling. But before I do that, I think because of your articles and a lot of other arguments being made and research coming out, there’s a growing narrative about the potential mistake that this was in legalizing gambling. But I think that can be helpful to go back and think in the minds of states who were interested in legalizing gambling. What was going on with them? Like, how much money are they actually making off of this? And what sorts of things is it going to?

Funt: Yeah, that was definitely the No. 1 argument, was, Hey. Let’s just bring in more revenue without taxing people—always, you know, a strong selling point for at least some people.

So whether tax revenue has exceeded or failed to meet expectations varies state by state. In total, since that Supreme Court decision and all these states started legalizing, a little more than $7 billion has been raised in taxes from sports betting for state governments. It’s important to note that $2.6 billion of that has gone to New York State alone, the largest legal sports-betting state, which also has the largest tax rate, so they’re just getting an epic windfall compared to the rest of the country.

Many states simply send the money to their general fund. Some states, like Colorado, specifically earmarked it—in Colorado’s case, for water-conservation issues. But you know, tax revenue is definitely a worthwhile thing to look at, but it’s not the whole picture. I think it’s appropriate to look at a more holistic view of, Sure, states are generating this money, but it’s not like loose change they’re finding in their couch cushions. This is coming from somewhere. It’s coming from their constituents.

We know gambling is, in many respects, kind of a regressive tax in that it, you know, pulls money from a lot of vulnerable people, as opposed to a more progressive tax that proportionately takes from people who can afford to lose. And that’s why some states, like Washington State, have been much more restrictive in the way that, yes, they’ve legalized sports betting, but you can only do it on the grounds at tribal reservations. So their idea was, Let’s give a boost to tribal economies, but we don’t want to depend on revenue from gambling to fund our state’s growing needs. We’d rather do that through progressive taxes, more sustainable, healthier for our society, something that definitely not all states have taken into account.

Demsas: I have seen a lot of that research around the regressivity of these sorts of tax revenues, but I was surprised with sports betting. And there was a Pew poll looking at the demographics of people who engage in sports betting. And they don’t really find any significant differences in educational attainment or household income. They see that men are more likely than women to say they have bet on sports, and adults under the age of 50 (when compared to those over 50), and Black Americans and Hispanic adults are more likely than white and Asian American adults. But I’m surprised that there’s not more of a difference in household income here.

Funt: You’re right. In some respects, I think sports bettors skew a little bit more middle class and well-educated, compared to other forms of gambling. But when we think about the regressivity of it or just whether it’s the healthiest way for society to generate money, it’s not just that the poor are the ones doing the gambling. It’s also—think about that people with gambling problems are, in many respects, these companies’ best customers. They’re losing such a disproportionate amount of money, compared to the rest of the clientele.

Are we comfortable generating money on the backs of people who just find this ruinous, in a lot of ways beyond financially? So that, I think, should give people pause. But you’re right—for a lot of cultural reasons, the people who bet on sports tend to be much more middle class than the people who, say, do scratch-offs or play the lottery.

Demsas: So I want to now turn to all of the harms that have now become evident over the past several years. Can you walk us through the financial impacts of gambling? What are we finding about the legalization of sports gambling on the impact on households’ financial well-being?

Funt: Yes. So last year, I’d say two of the most-buzzed-about studies that came out on that topic—one of them found a direct correlation between states that had legalized sports betting and a demonstrable impact on credit scores and other measures of financial health. A similar study, also last year, found that household savings go down in places where sports betting is legal. So you are seeing a demonstrable impact on people’s financial well-being as a result of the availability of sports betting.

Part of what I find, honestly, quite frustrating about the way this has played out in the U.S. is it’s been treated like this experiment where, We’re entering an uncharted territory. We’ll see how it goes. We’ll discover things. Like, Does this hurt people financially, or does this create a public-health problem that we didn’t anticipate? There’s a whole bunch of countries that are far ahead of the U.S. in terms of legalizing, and there’s a vast body of research that looks at the consequences. This didn’t have to be this shot in the dark for the U.S. We could have looked at Europe and Australia and Latin America and Asia and a lot of other places that are farther along and have had to reconcile the consequences of making gambling so accessible.

So in the U.K., for example, where online gambling was legalized in 2005, one study recently found that Brits lose about £5.5 billion every year betting online, which results in lost economic activity of £1.3 billion. The government estimates conservatively that gambling-related health consequences cost the population more than a billion pounds every year. And again, the people who did that study said: If you actually look at the second- and third-degree consequences, on a mental-health level and all the family trauma that it causes, it’s probably much bigger than a billion pounds, but we can safely say that.

So yes, again, the evidence is starting to trickle out in the U.S., but it’s been there overseas, and I think it’s pretty irresponsible that the states that were establishing regulations didn’t heed those warnings before getting this off and running.

Demsas: Yeah, I mean, I want to underscore this. I can imagine someone going like, All right, someone is going to, you know, buy some bad fast food out there rather than cook, or they might gamble on some sports. These are all just consumption, and they’re different levels of bad, but is it really that big of a deal?

You know, one of the studies you referenced, a Northwestern University study by Scott Baker and his co-authors—they’re finding that it’s not just displacing other gambling and consumption. People are falling into debt over this. So for every dollar spent on betting, households are putting a dollar less into investment accounts. You’re more at risk of overdrafting your bank account, maxing out credit cards.

And these effects are strongest among households that are already kind of financially precarious. Charles Lehman actually wrote a great article about this for us in The Atlantic. And this is not a situation, I think, where it’s, you know, We’re just getting money reallocated from other places. People are experiencing a lot more debt delinquency over this.

The other study that you referenced, the economist Brett Hollenbeck at UCLA and his co-authors also find, similarly, that the increase of the risk that a household goes bankrupt [goes up] by 25 to 30 percent. I mean, these are really big numbers that we’re seeing here. And can you just walk us through this kind of gambling addiction? Is this a situation where it’s a very small number of people who are getting addicted, and that’s what’s driving these stats? Or are large shares of Americans experiencing financial precarity here? What do you think?

Funt: Right. So the rate of problem gambling is definitely increasing. So for a long time, it was perceived that about 1 to 2 percent of the population is prone to problem gambling. In states that have had legal sports betting and other legal online gambling for a while, they’re seeing that rate closer to 6 or even 8 percent, and it’s even higher among young men, who are often the target audience for sports betting.

But I think it’s important to look beyond problem gambling. Even though those numbers are quite alarming, it can sort of make it seem like a marginal issue. Like, As long as I’m not in that sliver of the population, I’m good. I think that those sorts of consequences that you were describing go beyond people who have diagnosable problems.

So I find quite striking or even alarming the explosion of gambling among college students. And there was a survey recently that found that one in five college students who bet on sports dips into their tuition funds to fund their betting. So obviously, fewer than 20 percent of college students have gambling problems, but you’re still seeing people affect themselves financially because of their betting. So it’s a vast problem, and it’s an under-researched area.

It’s also something that is a developing story. So you’re not going to get a full picture out the gates. Gambling disorder, unlike some addictions where you might experience something once and become hooked on it—that can happen with gambling, but—it’s often a progressive disorder, so it can take several years or even longer to develop a problem. So if you think about it, we’re really in the early innings of this. And that sort of data and that sort of picture of how this is affecting society as a whole is still going to be emerging in the coming years.

Demsas: And, I mean, you talked a little about the mental-health impacts of gambling addiction here, but there was a paper that came out recently—it’s actually what spurred me to want to do this episode with you—about domestic violence. Can you talk to us about what that found?

Funt: Yes, it’s one of those things that’s terrible but, honestly, not totally surprising—that, again, you can see a correlation between the states that have legalized sports betting and those that haven’t, and when people lose bets, they’re more prone to commit acts of domestic violence.

There’s, similarly, a correlation, in that same respect, where sports betting is legal and higher rates of binge drinking. So you can think about it either fueling or just coinciding with a lot of other problematic activity. And it’s why, to really take stock of what this means for society, you’ve got to look at the bigger picture, not just some of these raw numbers that are thrown in our faces all the time.

Demsas: Yeah, I mean, I think that most people have probably heard there’s an older study that’s not about sports betting, but it’s just about, you know, an NFL home team’s upset loss can cause a 10 percent increase in the rate of at-home violence. This is a famous David Card study.

And the thing that I think is really interesting about the Card-Dahl study is that when we’re talking about upset losses—these are, like, unexpected losses, when the home team was predicted to win, and then they lose—you would think, Oh well, maybe in the states where there was an upset win, when the home team was predicted to lose and they actually win, maybe you see a decline in domestic violence, but that doesn’t happen. There’s basically an asymmetry here—

Funt: Oh gosh.

Demsas: —in the gain-loss utility function. So it’s like: You’re actually just gonna get more domestic violence. You’re not gonna even it out or something like that. And that, I think, becomes a really big problem when you are thinking about this paternalism issue here, because I can imagine people hearing this episode are just like, Yeah, this sounds really bad, but do I think the government should be in charge of banning something just because people are making bad decisions?

The downstream effects here are what I think are really convincing. You know, no one consents to having domestic violence happen to them, obviously, ever. But that that might increase as a result of someone else choosing to bet on sports seems, you know, even beyond the pale.

Funt: Yeah, absolutely. I think this debate often gets reduced to, Should this be outlawed, or should it be legal with hardly any restrictions? And I think it oversimplifies the argument, and it—we’re really past that. I don’t know how many states that have legalized it are going to go ahead and say, This was a mistake. Let’s outlaw it.

But there’s such a spectrum within that dichotomy, of: Should there be restrictions on advertising? Should there be restrictions on the enticements for customers? Should we require affordability checks to make sure people are betting at least vaguely within their means? All these different regulations that ought to be debated instead of, Should we ban this? which, of course—you’re right—is going to get a bad reaction from a lot of people who don’t like the government overstepping in the decisions we make.

I think consumer protections were the main argument for legalization. So whether we’re living up to that promise and delivering actual protections that protect the people who were betting illegally, and now we’ve said this is a safer way to do things—that, I hope, is where the conversation goes.

Demsas: I actually was surprised. I was trying to look up what people actually want to happen with legalization here, and I was shocked. Only 8 percent of people—there’s a Pew poll about this—only 8 percent of people thought it was good for the country that sports betting was legal. And 34 percent said it was a bad thing. The rest said they thought it was neither good nor bad. I would not have expected that. Is that what you find when you’re reporting, that people are saying that they think it’s bad that we’re allowing this?

Funt: Yeah, I try not to put too much stock in the anecdotal. Even though I’ve interviewed so many hundreds of people for my work, I’d rather rely on an academic who’s doing a proper study.

That said, yeah, I find it interesting, not only how many average people feel that way, but how many professional bettors, who you’d think would be the biggest evangelists for legalization and defending the way they make their livelihood—a lot of them are some of the most vocal about, This has gotten out of control. It’s crazy that there aren’t more guardrails to protect ordinary people.

I even hear plenty of people who work in the industry say, States and even perhaps the federal government could be doing more to protect customers. So it’s not just casual people who see all the ads and say, Gee, this has run amok. It’s people who are right in the middle of it who feel that way.

Demsas: So you mentioned that other countries have had experiences with this as well. Are there regulations you would copy from other places that maybe can improve our situation?

Funt: Yeah, and I try not to be, you know, a public-policy advocate as a reporter, but I will just say things that a lot of people, whether they’re health experts or player-safety advocates, are encouraging to at least be debated.

So one of them is: Countries that have banned advertisements that use expressions like free or risk-free or no sweat or bonus deceptively—so they’re basically making it sound like a can’t-lose proposition, when either you can lose the money you’re betting on the bonus, this offer, or you might get a little money through the bonus, but you’re obviously going to lose money over time—some countries have tried to weed that out.

There have been a lot of countries that have restricted when and how you can advertise, to try to minimize the number of young people that are seeing gambling ads day after day. So they might say you can’t advertise during sporting events or during certain hours of the day when kids are more likely to be watching TV.

Affordability checks are a polarizing one because that does tend to feel quite paternalistic, but in a lot of the places that have imposed those, the thresholds are sky-high. They’re not telling you, You should spend your money here or there. They’re saying, If someone’s spending hundreds of thousands of dollars within a day of signing up, maybe you ought to check in and see if they can afford to be doing that—things that are a lot more palatable than you might think when you hear a phrase like affordability check.

So there’s so many different reforms. Another one that is getting a lot of buzz at the federal level is this idea of a national self-exclusion list. So one thing that’s quite helpful for people with problems is they say, I’d like to cut myself off from gambling, to remove that temptation. But currently, let’s say I live in New Jersey—I can do that in New Jersey, but if I drive 15 minutes into New York or Pennsylvania, that exclusion doesn’t apply in those states. So it’s enormously tempting to do that. It might make sense to have a national self-exclusion list. So operators that are functioning across state lines have to honor exclusion, no matter where you are.

Things like that, again, it’s not about, Should we outlaw this? or, Should we backpedal on the decision to legalize? There’s this whole host of consumer protections that might be worth considering.

Demsas: Yeah, one thing I’d heard talked about is also not allowing people to make bets with credit cards, such that you have to have the money, so you can’t run up these large bills that you literally cannot pay back. And it seems like something about allowing it everywhere you are is a problem, right?

There’s a level to which I don’t know that we’re putting the genie back in the bottle on online betting, but the idea that you can pull out your phone at any point when you’re stressed out, that you don’t have to go somewhere, seems like a problem. And maybe creating some sort of temporal bounds, like maybe you can’t do it on college campuses or something like that—you can’t do it in schools in general, or you can’t do it at bars or something—you know, that might create some backlash here, but it indicates that, you know, there are ways to reduce the problem here.

Funt: You’re right that you have to use geolocation when you use these apps so that they can tell that you’re in a legal betting state, and it’s extraordinarily precise and effective. So if you’re in D.C. and you go into a federal building, suddenly your sports-betting app no longer works. It literally, like, works if I’m in a yard within the okay zone versus the not-okay zone. It’ll pick up on that.

There’s a state delegate in Maryland named Pam Queen, who’s also a professor at Morgan State University, who had the idea of: We could use this to either ban sports betting on college campuses or do something even more modest, like ban it in classrooms or in underage dorms or dorms during certain hours. The possibilities, as you were saying, are limitless, and it doesn’t have to be as severe as, you know, You can’t bet at a stadium or at a bar. It could be things that I think most people would agree sound appropriate, like, You shouldn’t bet in a freshman dorm or, you know, during class.

So yeah, that is a really potent tool that hasn’t caught on anywhere, but I think she and other people are going to be pushing for that.

Demsas: I then also want to ask you about your experiences interviewing legislators. So there are a lot of legislators who are involved in this effort, a lot of governors who have signed bills to allow sports betting or to allow online betting in their states. Have you talked to anyone who’s exhibited any kind of concern with how things have gone?

Funt: Buyer’s remorse, in some cases. Most notably, I’d say: I interviewed Charlie Baker, the former governor of Massachusetts who signed the bill legalizing bookmaking there in 2022 and then a few months later became president of the NCAA and has become a really vocal champion for limiting the amount of betting on college sports, particularly in light of the brutal harassment that college athletes and coaches get whenever their performance costs someone a bet.

It’s honestly horrifying, the sort of stuff they see on social media and in real life. And he has said point-blank, I wish, in hindsight, this had stayed in Las Vegas. As you were saying, it’s pretty commonsense that if you can bet from literally anywhere at any time of day, that’s gonna be quite a different situation than if you have to go to a casino, or even go to Las Vegas, in order to bet—or hunt down a bookie and find ways to bet through crypto or other sort of sketchy things that a lot of people are uncomfortable doing.

The idea that you can swipe to deposit money on your phone and then tap a couple of times and bet limitless amounts at any time of day is such a game changer. He was saying, We didn’t really process what a difference that would make, and I wish we had. So yes, he’s maybe the most forthcoming about that, but there are a lot of lawmakers who are seeing the fallout, in a lot of different respects, and saying, Maybe we need to re-regulate, as a lot of the rest of the world has decided is appropriate.

Demsas: Well, Danny, always our last and final question. This has been an episode chock-full of ideas that were good on paper. But what is an idea that you had that you thought was good at the time but ended up being only good on paper?

Funt: All right, so I was living in New York after college. I had a tiny balcony. I went and bought seeds to grow. I think it was, like, cucumbers and basil. And I was getting breakfast with my buddy Brian, and I was like, Dude, you will not believe how cheap these seeds are. We could totally grow vegetables and herbs and whatever else and sell it, and the margins would be crazy, and we’d make a killing. And he was like, So your business idea is farming? And I was like, Touché, Brian. You’re right. This is maybe not the most groundbreaking business idea. So he set me straight on that one.

Demsas: Oh my gosh, you didn’t live out—I actually, so my first house when I moved out of college was this group house, and we had the idea to farm some vegetables for the house, and it was successful in that we had some kale and sweet potatoes. But I have never in my life been like, I am never getting my food from my own labor. Like, this is just never happening again.

Funt: Oh, yeah.

Demsas: It’s a lot of work, and I feel like it caused so much strife in our household, too, because people were like, Who’s gonna harvest? What do we do with all this, like, extra kale now that no one wants to eat, because we have 20,000 bushels of kale. And you’re just, like, giving it away. But I’m glad that you did not actually have to execute your good on paper idea. You just figured it out beforehand.

Funt: I liked it, the basil I grew, but it wasn’t scalable. Brian was right.

Demsas: Danny, thanks so much for coming on the show.

Funt: My pleasure. Thanks again for having me.

[Music]

Demsas: Good on Paper is produced by Rosie Hughes. It was edited by Dave Shaw, fact-checked by Ena Alvarado, and engineered by Erica Huang. Our theme music is composed by Rob Smierciak. Claudine Ebeid is the executive producer of Atlantic audio. Andrea Valdez is our managing editor.x

And hey, if you like what you’re hearing, please leave us a rating and review on Apple Podcasts.

I’m Jerusalem Demsas, and we’ll see you next week.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

This week, House Republicans created a select subcommittee to investigate the January 6, 2021, attack on the Capitol and uncover the “full truth that is owed to the American people,” Speaker Mike Johnson said. Presumably this is a “truth” that somehow fell outside the frames of the thousands of videos taken that day that showed rioters storming the building and beating police officers with whatever weapons were at hand. Despite January 6 being an extraordinarily well-documented crime, many Republicans seem intent on whitewashing what many federal judges, jurors, and really any average American citizen can see with their own eyes.

In the past year, I’ve gotten to know many J6ers well. My partner, Lauren Ober, and I made the podcast We Live Here Now. The thing they had all been waiting for are the pardons that President Donald Trump delivered as promised “on day one.” Trump kept his promise. Hours after being sworn in, he gave clemency to more than 1,500 people convicted of involvement at the Capitol that day. Among them were some longtime militia leaders who carefully planned the riot. Now they’re free. For some, this is order restored; for so many other Americans, this is lawless abandon. And not everyone is reacting to the pardons the way you might expect.

The following is a transcript of the episode:

Marie Johnatakis: Hello?

Hanna Rosin: Hey, this is actually Hanna Rosin. I’m calling on my son’s phone for various reasons.

Johnatakis: Hanna! How are you?

Rosin: You sound happy.

Johnatakis: I am. I just got done bawling.

Rosin: Bawling. As in crying. Hard.

Johnatakis:  I think everything just came out. I was just holding it in for the last how many years?

Rosin: That was Marie Johnatakis, whose husband, Taylor, was just pardoned by President Donald Trump. He’d been sentenced to over seven years for what he did at the Capitol on January 6. Now he’s coming home.

This is Radio Atlantic. I’m Hanna Rosin.

A few hours into his second term, Trump pardoned more than 1,500 people charged in connection with the attack on the Capitol on January 6, 2021. Some had been charged with serious felonies, like assaulting police officers and seditious conspiracy. Others were charged with misdemeanors, like trespassing and disorderly conduct.

I’ve gotten to know a lot of January 6ers over the last couple of years, so I know how these prosecutions have upended their lives. And I know that for a lot of them, the pardons have restored their sense of justice. For them, this week feels like the world is set right again.

And as I checked in with them this week, and hung out outside the D.C. jail, mostly I just saw the chasm more clearly: how one person’s order restored is another person’s lawless abandon.

Johnatakis: I know this is going to sound crazy, but I have just really felt like Trump will do what he says he’s gonna do. And so, ever since that, I was like, “Well, if Taylor gets pardoned, it will be the first day.”

Rosin: Three weeks ago, when her world was still in chaos, Marie Johnatakis bought a one-way ticket home for Taylor. Trump had mentioned that he might pardon all the January 6ers, but you could never be sure. Politicians don’t usually do what they say, her daughter told her. And for a family whose only working parent had been in jail for more than a year, an airline ticket is a luxury.

But Marie had watched the video over and over of Trump telling an NBC reporter that he would pardon the J6ers on day one of taking office.

Donald Trump: We’re gonna look at everything. We’re gonna look at individual cases—

Kristen Welker: Everyone?

Trump: Yeah.

Welker: Okay.

Trump: But I’m going to be acting very quickly.

Welker: Within your first 100 days? First day?

Trump: First day.

Welker: First day?

Trump: Yeah. I’m looking first day.

Welker: You’ll issue these pardons.

Rosin: And then on day one, the world flipped.

Man: First we have a list of pardons and commutations relating to the events that occurred on January 6, 2021.

Trump: Okay. And how many people is this?

Man: I think this order will apply to approximately 1,500 people, sir.

Trump: So this is January 6. And these are the hostages, approximately 1,500 for a pardon. Full pardon.

Rosin: On Monday night, just before midnight, Marie finally picked Taylor up from prison, and she sent me a picture. They sat side by side, smiling, like a late Christmas-card photo. Marie hasn’t sat side by side with her husband since he was taken into custody just before Christmas 2023.

I asked her if she thought his transition home would be rocky, and she said no—it’llbe seamless. Taylor has written each of their five children a letter a week from prison, and he sometimes reads them books over the phone. In her mind, family harmony will be quickly restored, and so will the rightness of all things.

Johnatakis: I mean, this started with January 6, four years ago, and we were the scum of the Earth. We were domestic terrorists. We were people that you were supposed to be afraid of. Every time Trump had anything with criminal charges or anything like that, he has really been our hope for anything that would ever mean a pardon for us. And so a lot of us feel like it was one miracle after another.

And people don’t look to Trump—people in the movement on the chats that I’m on and stuff like that don’t look to him like a savior. But I think a lot of the people—almost everyone has faith, like a faith in God, a faith in Jesus. And I do hear a lot of like, for us, it’s a miracle.

Rosin: There is a whole other way that these pardons could have rolled out.

A little more than a week before inauguration, Vice President J. D. Vance made it clear to Fox News that he wasn’t expecting blanket pardons.

J. D. Vance: If you committed violence on that day, obviously you shouldn’t be pardoned. And there’s a little bit of a gray area there, but we’re very much committed to seeing the equal administration of law.

Rosin: During the transition, I spoke with Republican lawyers who imagined there might be some kind of review board, like maybe a Justice Department committee that would evaluate cases such as Taylor’s.

Taylor was not among the several hundred convicted solely of misdemeanors, such as trespassing or disorderly conduct. But also, he was not among the small handful convicted of seditious conspiracy. His assault charge hung on the fact that he was yelling into his bullhorn, urging a crowd to push a barricade into a row of cops. All captured on video.

Taylor Johnatakis: One foot! One, two, three, go!

Rosin: And under the J. D. Vance scenario, there would have been qualified lawyers debating in a room about degrees of “assault” and what length of sentence they merit. But instead, Trump chose to go with a blanket pardon, which sounds uncomplicated but actually brings maximum chaos.

Tuesday night, I was walking down my own street past a house that I know well. It’s a kind of safe house for January 6ers. Micki Witthoeft lives there. She’s the mother of Ashli Babbitt, who was killed at the Capitol that day. So does Nicole Reffitt, whose husband, Guy, was sentenced to over seven years for bringing a gun to the Capitol. Occasionally, a young January 6er named Brandon Fellows stays there too.

My partner, Lauren Ober, and I got to know the people in that house last year when we made an Atlantic podcast about it called We Live Here Now. I’ve walked by their house hundreds of times. But when I walked the dogs past the house on Tuesday in freezing weather, I saw Brandon outside, wearing an ICE jacket—as in Immigration and Customs Enforcement. This is his version of a sartorial troll.

Rosin: So what’s going on? I guess I don’t even know the basics of what’s going on.

Fellows: Last I heard was from Jen. We were at lunch with Stewart Rhodes—breakfast with Stewart Rhodes today.

Rosin: He’s here?

Fellows: Yes. But we’ve all been up, and he’s taking a nap real quick. So we just got back, but—

Rosin: Is he staying here?

Rosin: I froze—and not from the cold. Stewart Rhodes, the guy with the eye patch, who founded the Oathkeepers. He for years recruited and cultivated an armed militia to resist government tyranny. His estranged ex-wife recently said she fears that she and their kids are on his quote “kill list.” Rhodes’s attorneys have said that the idea that his family’s in danger is unfounded.

Before Trump’s commutation he was serving an 18-year sentence for seditious conspiracy, one of the longest of all the January 6ers. Now Stewart Rhodes was taking a nap down the block from my house.

[Music]

More on that after the break.

[Break]

Rosin: While Rhodes was napping in her house, Nicole Reffitt, was outside, being interviewed by a Dutch news crew. Her family is notorious, because her son, Jackson, turned in his father to the FBI. Someone adapted the trial transcript into an excellent play called Fatherland. Anyway, this week her husband, Guy, was about to get out of prison. But unlike Marie Johnatakis, she seemed unsettled about the pardons.

Rosin:  How do you guys feel about the blanket pardon?

Reffitt: You know, I was never a fan of that. I guess he thought it was the quickest way—pull the Band-Aid off. I was more in favor of commutations and then let’s look at everything, because not only did people do bad things that day, but there were some charges that were absolutely wielded like a weapon against people. And those things also need to be looked at because, you know, I don’t want anyone to have to go through this. And that’s my biggest concern.

Rosin: What do you mean “concern”? Like, I don’t know how to think about the blanket pardon either, Nicole. I’m trying to think what’s the difference between this and if it had gone a different way—what does it mean that it’s a blanket? Have you guys talked about that?

Reffitt: Well, because now all charges are gone.

Rosin: Yeah.

Reffitt: You know, and, uh, I’m a law-and-order gal, really. And so not all charges should be gone there. People did really bad things that day.

Rosin: In many people’s minds, Nicole’s husband, Guy, was one of the people who did really bad things that day, and he did get a fair sentence. Guy brought a gun to the Capitol, although he didn’t enter the building or use it.

Reffitt: Yeah, I never expected him not to have something, you know, like, I figured he’d be charged with something, because it was so significant, but it was just so over-the-top to me, all of the charges and that has always been my biggest issue.

[Crowd chanting]

Rosin: As of Wednesday only eight of the 22 people held at the D.C. jail had been released. But outside the jail had turned into a gathering place for people released from all over the country. Camera crews stood around from Sweden, Japan, Norway broadcasting interviews with the newly freed. And when Bob Marley’s “Redemption Song” came on the speakers, the crowd belted it out together.

[Sound of “Redemption Song” by Bob Marley]

Rosin: On Tuesday night, I caught a glimpse of Stewart Rhodes at the edge of the crowd. He’s hard to miss, with the eye patch. He was giving an interview to a right-wing YouTuber.

Stewart Rhodes: It’s a day of celebration. I mean, yesterday it was too. When President Trump was inaugurated, it was awesome. You know, like he said himself, you know, God saved him to save America, and I believe that’s true. And then he turned around and saved us last night, I mean, and restored us to our freedom. I mean, I’m not 100 percent restored yet. I’m still waiting for a pardon, but it’s so, so wonderful to be out, be out of these bars.

Rosin: That’s Rhodes’s one big complaint—that he’d been given a commutation instead of a pardon. A commutation can erase a sentence, but it does not restore all your rights, such as the right to buy guns. He told the interviewer he was applying for a pardon. He said, “ I think everyone deserves a pardon, without any exception.”

Rhodes: No one got a fair trial. It’s impossible to get a fair trial here if you’re a Trump supporter. And so you don’t have an unbiased jury, an impartial jury; you don’t have an impartial judge; you don’t have a jury that’s going to hold the government to its standard beyond reasonable doubt.

It’s not going to happen. So if you have no chance of a fair trial, then you should be presumed innocent. That’s put back in your natural state, which is an innocent and free human being.

Rosin: So that’s Rhodes’s version of history. They were sham trials. It was actually a day of peace. It’s a revision of history that Trump and his allies are likely to try to push and push for the next four years. House Speaker Mike Johnson has already formed a select subcommittee on January 6, to quote “continue our efforts to uncover the full truth that is owed to the American people”

But for a whole crew of other people involved in January 6, these pardons represent a reversal of justice.

January 6 did not require delicate forensics. It has to be one of the most well-documented crimes in modern history. There are tens of thousands of hours of video showing rioters beating up police with whatever tools are at hand.

At least five people died for reasons that are in some way related to the insurrection. Some 140 police officers were injured, and many could never work again. On Wednesday, retired officer Michael Fanone had choice words for Rhodes that he expressed live on CNN.

Michael Fanone: This is what I would say to Stewart Rhodes: Go f— yourself. You’re a liar.

Anchor: We didn’t obviously to beep that word out …

Rosin: Fanone said he’s worried for his safety and that of his family.

The judge who sentenced Taylor Johnatakis, Judge Royce Lamberth, wrote a letter in connection with the sentencing. He wrote: “Political violence rots republics. Therefore, January 6 must not become a precedent for further violence against political opponents or governmental institutions.” Lamberth is 81. His wife died a few months ago. He had a handful of new January 6 cases on his docket, but of course they’ve disappeared. In that sentencing letter, he continued, “This is not normal.”

We tried to reach him to talk about the pardons, by the way, but he wasn’t ready to talk about them yet.

 Reffitt: My husband’s being processed out of Oklahoma right now. Can’t wait to see that man. He will be here in D.C. tomorrow. And you know what? We’re getting freedom, baby! That’s right. We’re getting freedom! We are getting freedom. And that’s absolutely right.

Rosin: At the Tuesday-night rally, Nicole got a call from Guy. He was out. On the road. Headed towards the airport.

Reffitt: He’s in the car. He’s in a car! In a car!

Rosin: Stewart Rhodes told the crowd that he was headed back to California this week. As for Marie and Taylor, they fly home on Thursday. Marie told me the kids are gonna make dinner.

[Music]

Rosin: This episode of Radio Atlantic was produced by Jinae West and Kevin Townsend and edited by Claudine Ebeid. It was engineered by Rob Smierciak and fact-checked by Stef Hayes. Claudine Ebeid is the executive producer of Atlantic audio, and Andrea Valdez is our managing editor.

I’m Hanna Rosin. Thanks for listening.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

In politics, compromising with one’s ideological opponents is like walking a tightrope while both your allies and foes jeer at you. Democrats, now the out-group facing a Republican trifecta, will have to decide when to fight nominations, laws, and executive orders and when to step into that circus ring.

Jennifer Pahlka, a former Obama administration official and an author of a new report on government reform, kicked up a storm some weeks ago when she encouraged Democrats to work with Elon Musk’s Department of Government Efficiency (DOGE).

“We do need to talk about government reform, and while I’m sorry the conditions are quite a bit less than ideal, I think it’s time we admitted they were always going to be. Democrats did not do this work,” Pahlka wrote.

Pahlka was in part responding to arguments by people like Leah Greenberg, a co-founder and co-executive director of the progressive group Indivisible, who scolded Democrats for promising to work with DOGE: “Democrats should be planning to fight these corrupt plutocrats, not offering to work with them.”

On today’s episode of Good on Paper, I explore whether liberals can actually find any common ground with DOGE and whether Pahlka’s focus on what she calls “state capacity” actually explains government dysfunction. (This episode was recorded earlier this month and references Vivek Ramaswamy’s involvement with DOGE, before it was reported that he would no longer be a part of it.)

“It’s an uncomfortable position to be in because it’s not like I have a crystal ball to know what Musk and Ramaswamy are going to do. And I may disagree with some of what they do, or maybe a lot of what they do, but they’ve really kind of moved the Overton window and the conversation about this inefficiency, the sludge. And I think that’s valuable, frankly, and I want Democrats to kind of get in the game of that reduction,” Pahlka tells me.

The following is a transcript of the episode:

Jerusalem Demsas: While 75 percent of Democrats tell Pew that they prefer a bigger government providing more services, fewer than a quarter of Republicans say the same. This divide is a persistent feature of modern American politics and can make it seem like government-reform efforts—like civil-service reform and getting rid of costly, inefficient regulations—are the purview of the Republican Party.

Elon Musk and Vivek Ramaswamy certainly think so. They aim to cut $2 trillion from the roughly $6 trillion federal budget under the banner of the Department of Government Efficiency, or DOGE. This could be a nearly impossible feat, seeing as discretionary spending by the federal government was only $1.7 trillion in 2023. Perhaps realizing this conundrum, Musk and Ramaswamy have negotiated against themselves and revised the number to $1 trillion or $500 billion. We’ll see.

[Music]

Demsas: I’m a bit tired of how reasonable-sounding concerns around government efficiency and effectiveness get shoehorned into a witch hunt for government waste. There are serious problems with how the federal government’s processes and regulations harm economic growth and the effectiveness of important social-welfare programs. I’m skeptical that focusing on budget cuts does much to change that, but I’m also frustrated that it seems the only political actors talking about this seriously are on the right.

My name’s Jerusalem Demsas. I’m a staff writer at The Atlantic, and this is Good on Paper, a policy show that questions what we really know about popular narratives.

My guest today is Jennifer Pahlka, a senior fellow at the Niskanen Center and founder of Code for America. She worked in the Obama administration as deputy chief technology officer, and her recent book, Recoding America, argues that the federal government is hobbled by its inability to implement its stated priorities.

Jennifer has a message to people across the political spectrum: If you want government to work, you need to reform it. In that vein, she’s much more optimistic than I on the potential for good-government types to work with DOGE and the Trump administration.

Demsas: Jen, welcome to the show.

Jennifer Pahlka: Thanks so much for having me.

Demsas: I am so excited to have this conversation. I feel like me and you—our work has been in conversation for years now, and we’ve been at some of the same conferences and things. So I’m really excited to dive in.

Pahlka: Me too.

Demsas: So you’re someone who has worked in government and now works trying to make government better. Give us the liberal case for government reform.

Pahlka: Well, I feel like liberals talk about government reform. I’m not sure they necessarily need to be sold on it so much. I think the kind of reform that we need today is a little bit of a hard pill for liberals to swallow, because we need government to sort of be faster, a little bit less process oriented and more outcome oriented. And there has been a pattern, I think, of liberals being very fond of process, of additional rules and regulations, for all the right reasons.

And with great success, right? I mean, the environmental movement really cleaned the air and our water, and that was through regulations. The civil service went from being a place where you would get a job because you were someone’s friend or you’d given money to a campaign, to a professional place. And those are all rules and regulations that have made government better and fairer and made our country better.

But we’re kind of at a point where there have been so many of them, and they’ve stacked on top of each other so much that we’re just moving very slowly. And so the kind of reform I’m talking about now does involve some things like maybe reducing, especially, regulation on government itself—reducing procedures and moving a little faster. And that is the part that liberals need to be convinced about, let’s say.

Demsas: You have a new report out with the Niskanen Center called “The How We Need Now: A Capacity Agenda for 2025 and Beyond.” What’s the main takeaway? What are you trying to solve here?

Pahlka: We’re really trying to help people understand that when you think about government reform, it just seems so big and impossible. So we’re trying to break it down and say, Actually, there are specific things that you could do if you want a government—and this could be, you know, we wrote it for federal government, but you could use it for state or local government as well—if you want government to be able to do what it says it’s going to do, to achieve its policy goals.

And so those things come in four buckets, you know—four pillars. The first thing is: You need to be able to hire the right people and fire the wrong ones. The second is: You have to reduce the procedural bloat. We’ve also talked about that as reducing the administrative burden on public servants—in addition to on the public, but we’re really talking about on public servants—so that you get more public servants focused on outcomes and less on process and compliance. The third thing is: You need to invest in digital and data infrastructure to enable all of this. And there’s a bunch the federal government could be doing at the start of the Trump administration to do that, including getting the United States Digital Service funded again and the Technology Modernization Fund funded again.

And then last, and the one I’m most interested in, is that we need to close the loop between policy and implementation. And what I mean by that is: Right now it functions as this sort of waterfall process, where you have a law, and then maybe it gets handed off to an agency to write regs, and then, you know, into the implementation phase. And it doesn’t ever sort of circle back and say, Is this working? What are we learning? What needs to be adjusted?

And especially in the era of Loper Bright, this decision from the Supreme Court that’s really going to change how the executive-branch agencies relate to Congress, we have kind of an opportunity to rethink that relationship. And I think we should rethink it along the lines of creating feedback loops that let us adjust along the way so that we actually get the outcomes that the laws and policies that we pass intend.

Demsas: I think you’re right when you talk in the abstract. Like, most people, liberal or conservative, would say, Yeah, you know, red tape is bad, and the government should definitely update technology, and, you know, it’d be good if we had a government that worked efficiently. And then when you get into the actual policy prescriptions and the trade-offs, things become more controversial, particularly when you’re talking about civil-service reform and regulatory reform.

So one of the third rails has long been hiring and firing. I want you to talk to us a little bit about what’s broken in that space and how you would change it, and I’d also like you to talk to us about the story of Jack Cable.

Pahlka: Oh, gosh. Jack, yeah. Well, first of all, what’s not broken? So, you know, we had the Civil Service Reform Act of 1978, which established these Merit System Principles. They are very good. If you read them, you are very likely to agree with them. They talk about integrity and fairness and, you know, promoting people on the basis of merit. They’re called the Merit System Principles. And I think they are a strong foundation for our civil-service system.

The problem is that (A) that was 1978, and so we’ve had many years now for those things to be operationalized with a lot more ornaments that have been attached to them, right? It’s not just those principles. It’s the regulation and the guidance and the operating manuals and the processes and the forms that have derived from those that have really, I think at this point, kind of perverted their intent.

So for instance, we say we’re going to hire on the basis of merit. We also say we’re going to hire in a way that’s nonbiased. Well, what happens is that you have HR managers who kind of control the process of selecting a candidate. What they do—I’ll give you sort of the very specifics of how this works in 90 percent of cases. This is not the accepted services, and it’s not political appointees, but open-to-the-public, competitive jobs. They get, like, a big pool of resumes, and they have to down select. The first down select they do is by looking for exact matches between the language on the resume or cover letter and what’s in the job description.

Demsas: So if you copy-paste the job description into your resume, that’s, like, points?

Pahlka: Yes, and I have a friend of mine who’s in my book—I actually originally interviewed her about this. I didn’t put that in the book. But she was looking at a resume that had not just been copied and pasted, but copied and pasted and not reformatted. Like, that part was in a different font.

Demsas: Oh my god.

Pahlka: Like, the same font, right? And she points this out to the HR manager, and they’re like, Yeah, that means that this person’s the most qualified, because it’s the exact same language. And she’s like, This person is clearly unqualified because they didn’t even know to reformat. And this is not an outlier. Like, this happens a lot.

So first they’re looking for these exact matches. And then they take everybody who was really close in language—and also, by the way, who has something called a government resume, which is different from a private-sector resume, and you have to know that somehow, magically, before you apply. Then from that pool, they send everyone a self-assessment questionnaire, and everybody who marks themselves as master, and I literally mean master—I think that’s the top rating in a lot of these—they make the next down select, so they move on to the next pool.

Demsas: Wait—so if you just say that I’m a master at this, like, without any double-checking, you just get to move forward?

Pahlka: I mean, somebody could send me a self-assessment saying, Are you a master programmer in Python? And I would just be like, Yes, and I would move into that pool. Nobody checks it. It’s actually worse—not just that no one checks it; it’s that the HR people will tell you that subject-matter experts (SMEs) are not allowed to be in that part of the process.

I mean, there are processes that do include them, and I can get to that, but you can’t have SMEs look at these resumes and exert their judgment, because they may introduce bias into the process. Now, again, I think the idea of keeping bias out is something I agree with, and I’m going to assume you agree with, and most people agree with. But that’s not actually keeping bias out, right? That’s what I mean about sort of a perversion of the intent.

But anyway, so you have this now smaller pool of people who are great at cutting and pasting and great at, you know, self-aggrandizement—or really what it is, is they just know what to do. They know how to play the game. And then from that list, you apply veterans’ preference. In other words, any veterans in that pool float to the top, and that’s the “cert,” which is just the name for the list the HR manager gives to the hiring manager. That’s the cert that the hiring manager is supposed to choose from. So this is not consistent, to me, in my mind, with Merit System Principles of fairness, and not bias, and certainly not merit.

And so what you are looking at when you see that kind of behavior is a system that’s designed to be completely defensible from the critique of your judgment, because you have exercised no judgment at all. And I understand why people defend them and do these processes to be defensible, but I think, in the end, they come up actually indefensible.

So I learned about this process, in part, through a young man named Jack Cable. I was on the Defense Innovation Board at the time, and he won the Hack the [Air Force] contest. So all these security researchers from around the country come together, and, you know, they’re looking at bugs and security bugs and Pentagon software. This young man wins the whole contest. He’s the best out of the group.

And of course, you know, the people at the Defense Digital Service and other parts of the Department of Defense say, Great. We need this guy on our team. He applies with a resume that lists his programming languages and the frameworks that he is expert in, and he is cut in the first batch because he did not cut and paste. And the people reviewing his resume see this sort of gobbledygook of programming languages—they’re not technical people. They’re not even sort of supposed to know what those are, and so he gets cut.

And it’s not just that—then the Pentagon folks intervene and try to get him hired something like 10 different times. He does eventually get hired, but even with these interventions from people in power, and sort of as it escalated with increasing levels of power in the Pentagon, this very talented security researcher continues to get cut from the process before hiring managers ever see his resume.

Demsas: Wow.

Pahlka: Oh, and one more thing: He’s told by the HR people along the way—he’s quite young—they say, Go work at Best Buy selling TVs for a year, and then you’ll be qualified for this job.

Demsas: Wow. And I feel like in that time period—obviously, this is an exceptional case where a lot of people took effort to try to get him hired. But, you know, private-sector processes are much faster than this. And what’s most likely to happen is you get all of these top performers going into the private sector.

Pahlka: Oh absolutely. And I mean, it’s just a testament to his commitment that he stuck through it. And that young man has actually stayed in government. It’s amazing. He’s done some really wonderful work.

Demsas: So there’s that part of the government reform that you talk about, which is about hiring and firing. I mean, obviously, we only touched on it a little bit. But the other part of it that you focus on a lot is around regulatory reform. And one of the laws that you’ve pointed out is the Paperwork Reduction Act. Can you walk us through how that act hobbles government?

Pahlka: Yes. I will say, we’ve had some good progress on PRA, and I should also mention that we’ve had some good progress on that assessment problem. The [Fair] Chance to Compete Act passed both houses of Congress, and it actually directs agencies to stop using those self-assessments.

I have high hopes for it, but I also will say: There was an executive order saying that under Trump. Biden renewed that executive order. And it hasn’t really gotten the agencies to change their practices yet. So there is an implementation issue, I think, and we’re going to really have to watch if the [Fair] Chance to Compete Act does what we hope it does.

Demsas: Wait—if both Trump and Biden issued the executive orders, why aren’t the agencies doing it?

Pahlka: It’s very hard to change the practices of agencies, even under direct order.

Demsas: Yeah. Mechanistically, though, what’s going on? Are there people who are just refusing to change? Or, like, what’s happening?

Pahlka: Well, it wasn’t in statute. I don’t think there was a timeline or a deadline for it. I think if you really read the language and translate it into, you know, what’s practical, it’s sort of more encouragement. I mean, it does direct them, but there’s sort of very little teeth in it.

Government moves slowly. HR people move particularly slowly. I mean, until you fix some other problems—like how detailed it is, how many rules you have to comply with in order to use a subject-matter expert in that process—it actually is, like, enormous amounts of time to run a hiring process using real assessments.

Demsas: So tell us about the Paperwork Reduction Act. What is it doing, and how is it preventing government from acting quickly and nimbly?

Pahlka: So there’s sort of the general level of it, which is just: It’s a lot of work to comply with. So imagine you’re charged with implementing the CHIPS and Science Act, for instance, and you want to stand up a form to allow companies to express their initial interest or even apply. You want to know early on what kinds of projects might companies, you know, bring to the Department of Commerce, to apply for funding under CHIPS.

Well, you can design the form. There’s going to be a lot of process and a lot of stakeholders that want to look at it. You don’t get to write something up and throw it up on the internet. But once you’ve done all that work for your internal agency stakeholders and sometimes cross-agency stakeholders, then your form, because it’s an information collection, is subject to review by the Office of Information and Regulatory Affairs at the White House.

And so you’ve got to sort of do all this pretty heavyweight documentation of your form and why you’re asking these particular questions, and you submit it to them. And because that process needs review by people—there’s only so many people in OIRA, the Office of Information and Regulatory Affairs—and because the process requires two separate times that you post it to the Federal Register, get comments from the public, respond to those comments, then potentially do a revision, then post it again, get comments, respond to those comments. And those time periods are designated in statute—I think it’s 30 days the first one and 60 days the second one—like, right there, that’s at least a month, but more because you have to do all the lead-up and then follow-up.

The average time to get through—or actually, I think it’s the minimum time to get through—a standard PRA review is nine months. And that’s just to get one form up. And it can be longer. Now, there is a fast-track process. If you get a fast-tracked application, that runs out in six months. So in six months, you’ll have to do it all over again. When you’re supposed to have moved on to the next phase of your project, you’re kind of going back to zero.

And there’s certainly value in a centralized office knowing all the things that agencies are asking the public, or companies, or anybody who would be filling out a form. And there’s absolutely value in knowing, like, Oh we have this data here. Maybe we shouldn’t be asking for it. Maybe we can get it from another agency. That would be, like, the best use of this kind of centralized function. But we have let this become quite a heavyweight process that really slows agencies down.

Demsas: You’ve outlined quite a few things in your public research and writing around how you think government—both whether we’re talking about Congress but also the executive branch—should reform in order to make things more efficient. You know, some of these things are just common-sense requirements to make hiring practices align with things that people think are good, like merit.

But most people who are talking about this, I think, are often on the right. And increasingly, I think this conversation is being brought up by people like Elon Musk and Vivek Ramaswamy, who are heading the Department of Government Efficiency, DOGE, for President-Elect Donald Trump.

You wrote, recently, a piece for your Substack called “Bringing Elon to a Knife Fight,” where you said that you support Democrats, like Congressman Ro Khanna, for pledging to work with DOGE. Why is that?

Pahlka: Well, I did say that until we know more about what they’re going to do, I think we should take an open stance. It’s very hard to know what they’re going to do. But ultimately, I said that because, as much as I may disagree with the policy goals of the administration that Musk and Ramaswamy are serving, there is so much work that needs to be done to subtract from government instead of constantly adding to it, to make it easier to get stuff done in government. I mean, people talk about regulation always as, you know, we’re regulating companies so they can’t, you know, pollute a stream. That’s wonderful.

There’s also enormous regulation on government itself, like the Paperwork Reduction Act, or like these hiring practices that really keep us from being able to serve the public in the way that we need to. And so it’s an uncomfortable position to be in because it’s not like I have any crystal ball to know what Musk and Ramaswamy are going to do. And I may disagree with some of what they do, or maybe a lot of what they do, but they’ve really kind of moved the Overton window and the conversation about this inefficiency, the sludge.

And I think that’s valuable, frankly, and I want Democrats to kind of get in the game of that reduction. And I think that if some of what they do is the wrong thing to do, but they shake government up in a way and maybe even pull some stuff out, we may be able to build back things that are kind of right-sized, the right-size procedures—not no procedure, not no process, but maybe not the heavyweight process that we have today.

Demsas: The thing I hear you saying here is, sort of, what I hear from people who have given up on their own side doing the right thing. And this is, I guess, reflected in the end of your piece, where you write, “We can wish that the government efficiency agenda were in the hands of someone else, but let’s not pretend that change was going to come from Democrats if they’d only had another term, and let’s not delude ourselves that change was ever going to happen politely, neatly, carefully.”

So, I mean, part of what it sounds like you’re saying is, Yeah, nobody wants this version of government efficiency, but there’s no other way it’s going to happen. Why is that the case? Like, why do you think the Democrats have been so unwilling to engage on this issue? I mean, you’re a Democrat. You worked in a Democratic administration, and you’ve talked to many other Democrats who have very similar views to you. Why is this such a third rail for them?

Pahlka: I’m not sure I know the exact answer to that. I think if you want to look at the Biden administration, in particular, you know—they went in with a big set of policy goals, and they actually achieved a lot of them. The four big bills are legislative accomplishments, significant legislative accomplishments. So they went for the what, but they neglected the how. And I think in their minds, it’s like, You’re going to do one or the other.

I think they should have paid equal attention to the how, to cleaning out the pipes so that the what could get through them faster. And that speed has clearly been a real problem. I mean, we’re writing now about the amount of money that could be clawed back because it didn’t get through those pipes, so really, really reducing Biden’s legacy. The frustration of not having that many electric-car chargers that were promised under the Bipartisan Infrastructure Law—all that stuff is due to this lack of focus on the how, and I don’t think it was a binary choice. I think Biden’s team could have said, We’re going to spend as much energy on the how as we are on the what.

But I do think there’s something about the way the Democrats, of course, want to be thoughtful and considered and hear all voices. And if you are thoughtful and considered and hear all voices, you tend to add policy and procedure and ways of looping everybody in. And that, actually, you know, adds instead of subtracts. Just naturally that’s sort of what happens. And in some ways, the destruction from which you can hopefully rebuild kind of needs to be done by somebody who kind of doesn’t care about that, in a certain way.

Demsas: I wonder, though, because it feels that, you know, two different theories of government reform—I worry about being [them] conflated, right?

So let’s take the DOGE theory, the Vivek-Elon theory. They presuppose that there are all these bureaucrats that are not really needed and all of these wasteful programs. And in a Wall Street Journal op-ed, they essentially have this idea that the executive branch has wildly overstepped its small-d democratic authority by being allowed to interpret laws that Congress passes as they’re implementing them.

And if that’s your theory of government reform—if your theory of government reform is that there’s just all these people who are dead weight, who are clogging up the process—then their answer, which is “mass head-count reductions across the federal bureaucracy,” is reasonable.

But as I understand it, your theory of government reform is very different. It’s that you need a capable and nimble executive branch in order to deliver on priorities like—I don’t know—providing health care to poor children. But in order to do that, you actually need a highly competent, well-paid, expensive labor pool and a good deal of it.

And so to me, it feels like, while both of these things can call themselves government-efficiency complaints—while they’re both motivated by a concern about the costs put on both private actors, individual citizens, and other government entities—they’re actually, fundamentally, two different political projects. So how do you see these things working together?

Pahlka: I agree. I have a very different view of it, and there’s some part of me that just thinks that if Elon and Vivek come in and spend any amount of time, if they don’t just get bored or frustrated and wander off, they’re gonna learn this. And they may have a different set of values, but I think it’s hard to miss it when you get into government that there are a lot of incredibly smart, talented, creative, dedicated people doing really amazing work. And you just fall in love with them once you actually get in the door. It’s from a distance that they look like, you know, these unaccountable, lazy bureaucrats. Up close, they’re pretty impressive.

But I think where I would put a little nuance on what you just said is that I do think we need this incredible workforce. And I think we’ve done a bad job of balancing between what I, in my very fancy language, call “go energy” and “stop energy.” So you have more people doing various forms of compliance and safeguards than you have the people trying to build something and get it out the door. And somebody I worked with at one point said, It’s like we’ve got six people building this product and at least 60 people telling us all the things we can’t do.

Now, those people who are saying, You can’t do that, are not dumb. They are not lazy. I mean, there are, of course, a few bad apples in government, and we can talk about that. I’m not saying everyone’s perfect. But you have people who, in fact, are—because they’re good, and because they really know the law, and because they really feel like it is their job to protect the public using this law, policy, and regulation—are very zealous in telling builders what they can’t do. And you have the very well-intentioned stop energy that overwhelms the people who have sort of go-energy jobs.

And I’m a little biased because I work with people a lot who do technology. They’re doing things like trying to get that form up, you know, trying to make sure that veterans can get their benefits. They are focused on, Can we get this application up so they can apply? Can we get the check to them? Can we get them their health care? Like, the actual outcome.

And a lot of people’s job isn’t to focus on the outcome but to make sure that all these things have been complied with, and they can do their job very well, and it slows the people who are outcome focused down. And it’s not their job, necessarily, to—you know, they’re not supposed to do their job less well. It is the job of leadership, of [the Office of Personnel Management], of the White House, of Congress, to look around and say, Why do we have so many people saying no, no, no? Oh because we put all these rules in place, and we’ve developed a culture of risk aversion that means we’re really, really focused on making sure nobody breaks any rules, at the expense of getting the job done. Leadership needs to balance the workforce between go energy and stop energy, and really take a hard look, if you’re going to add a regulation, you’re going to add a rule, Okay, what is the cost of adding that to the actual outcome that the American public expects?

[Music]

Demsas: After the break: Jen and I hash out the difference between political will and what she calls state capacity.

[Break]

Demsas: One phrase that you use a lot, and this is included in your recent report with the Niskanen Center, is state capacity. Can you define that for us?

Pahlka: Well, I didn’t even know the term until after my book came out and people were like, This is a state-capacity book. But I have since learned it’s an academic term that simply means the ability of a government—at any level and any government—to achieve its policy goals. So it is essentially, like I said, the how to the what.

Demsas: Yeah, this is a term that I think I first heard in the development-economics, development-political-science space. And it’s most commonly used to talk about the ability for these developing nations to effectuate their political priorities.

So for instance, like: Can a country collect taxes? Can it maintain the monopoly on the use of violence? These are core questions of state capacity because if you can’t collect taxes, you can’t run programs, you can’t have a police force that enforces laws. Like, there’s very little you can do on top of that, right? You can’t run a CHIPS program if you can’t do those things to begin with.

Why does this sort of idea—and how does this sort of idea—apply in the American context, where we have the ability to collect taxes? We have, relative to the rest of the world, like, a high degree of monopoly on the use of legitimate force. It’s contained within the state. What is the purpose of applying this term here?

Pahlka: Well, I mean, since you brought up applying taxes, the individual master file at the IRS, which holds all of the data about tax returns from individuals and families since the ’60s, is written in assembly code. There are vanishingly few people in the world who know what that code looks like. And it’s pretty robust. It’s lasted a long time. But, like, you’re going to run out of the human understanding of how that thing works, and you’re going to have a crisis at some point.

That’s not a crisis now, but we also don’t collect a lot of taxes. We have a serious unenforcement policy. We’re leaving a lot of money on the table because we have not empowered the IRS to be very successful. So we’re certainly not like a third-world state or an emerging state in that regard. But we are kind of going backwards in some areas.

And there’s a million examples of this, but I think that it is sort of shocking to people that state capacity is now a big concern for the United States, when it used to be that we only thought about it in relation to the countries that we would fund through the World Bank, or whatever. But national defense is a really great example of this. I mean, we keep spending more and more money, and it is not at all clear that we are getting more deterrence or more security. In fact, my thesis there is that we’re just spending too much money, not because—we shouldn’t cut spending because we want to be less secure.

But go talk to anybody in the Department of Defense. Pretty much everyone will tell you, like, unless there’s some shock to the system, we’re not going to change how we do stuff. And the way we do stuff takes decades, and we have to be able to move faster because, you know, we’re spending, I think it’s, like—what are we up to—almost a trillion dollars on national defense. And yet we seem to get less secure every year because the more money you put in a system like that, the more people double down on these very heavyweight ways of operating that are not what we need today.

Demsas: So I want to push you here a bit because this is a place—I’ve brought up to other people: I feel like the application of state capacity sometimes doesn’t feel like it fits well, and that, sometimes, what’s actually happening is that this is just a question of political will. It’s not that the government can’t accomplish what it tries to do. It’s that it actually has competing priorities, and there are trade-offs it’s unwilling to make.

One place where people have talked a lot about regulation that is holding government back is the National Environmental Policy Act. This is a piece of legislation from the 1970s that requires that the government study the environmental impact of its major actions. And it’s often talked about that it takes years to compile an environmental-impact statement, so it can take years and years in order to get a permit for, you know, a big energy project.

But something interesting happened, and this is a stat that was surfaced by Brian Potter in his Substack, “Construction Physics.” I’m reading from it: In 2009, after the Great Recession and Congress passed the American Recovery and Reinvestment Act, there were “over 190,000 projects, totaling $300 billion worth of stimulus funds, [that] were required to have NEPA reviews before the projects could begin. After the passage of [the American Recovery and Reinvestment Act], categorical exclusions were completed at a rate of more than 400 per day, and 670 environmental impact statements were completed over the next 7 months.”

So essentially, these EISs, the environmental-impact statements that often take years to complete, all of a sudden are being completed over the course of a few weeks—670 over the course of seven months is just astronomical compared to what we usually see.

And this is an example where nothing changed about the state capacity. They didn’t change anything about the legal environment. They didn’t change anything about the number of people working in government and whether they were more qualified. The HR processes didn’t change in this time period.

What happened is that the federal government was like, We’re in an emergency space. We need to get a bunch of stimulus dollars out the door, because we’re in a free-fall recession, and we’re worried about mass unemployment. And then, all of a sudden, all of these things that seemed like state-capacity issues, that seemed like these big constraints on government, actually just disappeared, because everyone wanted them to happen.

So is it the case that the government can’t do what it wants? Or is it that there’s a lot of competing priorities, and in times of nonemergency, we’re actually not aligned on what government wants to do?

Pahlka: Well, I mean, I think COVID is another good example of when government just does it, right? Or Josh Shapiro’s getting I-95 open again. I can’t disagree with you on that. Absolutely. I will say, I remember that too, and we just looked into it, and it’s not exactly apples to apples there, so I’d just like to put a little bit of an asterisk on it.

But I think your point is valid, but it does, then, beg the question, right? So we only have 47 electric-vehicle chargers out of the money that came out of the, you know, Bipartisan Infrastructure Law. I guess it was also a bill that funded the BEAD Program for broadband-internet access, and we have zero connections from that.

Are you saying, then, that Democrats didn’t want to see those things implemented? Because I do think it is a matter of will. But we are seeing places where the political will seems to be there, but it seems to sort of stop after the law is passed.

I think I’ve also shared this with you before, but, like, I got into this through working with cities and states on benefits delivery, and we were looking at SNAP uptake. And I was in California, and it was just shocking to me that California, which had a ton of money and spent hundreds of millions of dollars on IT systems for people to apply for SNAP online, had the second-lowest rate of participation in the program in the entire country. Only Wyoming was worse than California.

Is that a political-will problem? It’s, like, a really blue state, very pro-welfare. But it kind of couldn’t get out of its own way. It so overscoped these systems that it took about almost an hour to apply online. You couldn’t do it on a mobile phone. It’s just all these ways in which they created a system which is hard to use. But it’s really clear to me that they didn’t intend to do that. They just had too much process in the way and less of a focus on the outcome.

So I do think it’s a political will, but it has to be political will to follow the thing all the way through to the outcome, to care as much about the implementation as you do about the legislative win or the money that you put into it. We’re really good at money and rules, and those things do not necessarily translate to the outcomes that we promised people. So that will has to move.

Demsas: Yeah. But I think what I’m saying is: I think this may be a case of revealed preferences, right? Like you asked me, Does this mean that Democrats didn’t really care about getting broadband out? And I don’t want to make that kind of a strong claim. I think if they could push a button, and there was rural broadband for every single person in rural America, they would have pushed the button.

But the question government asks, and government policies ask, which you’ve written about extensively, is not just: Hey—do you wish this thing existed? It’s, When you’re forced to make trade-offs between whether to push out broadband or make it easier for contractors that are different from the ones you usually go to to get access to this program, which do you choose between? If you’re going to choose between actually getting out broadband and following the most onerous environmental regulations that exist, which thing are you choosing?

And over and over again, you see, as you mentioned before, liberals choosing this process, choosing this kind of way of delaying implementation in order not to follow some shoddy or quicker, maybe more error-prone system. And in doing so, they end up not getting to the outcomes. And to me, I feel like that actually is a situation where we’re seeing what Democrats actually want, which is really clear when you look at infrastructure projects.

I mean, this is what I think is the story of California high-speed rail, where you talked to so many people, where I bet a lot of people would love for there to be high-speed rail between San Francisco and L.A. I don’t think they’re lying about wanting that to exist. But when you talk to people who are working in that program or who are working trying to implement it, and you say, Okay, well, you need to not let every single local government fleece this project for whatever priority they have on the ground, and no one wants to do that. So I’m left with the conclusion that yes, they want high-speed rail but not if it means angering a single person within the Democratic Party.

Pahlka: I completely agree with that. It’s a little bit what I was saying about, like, you kind of need a big disruptor, someone who doesn’t care, to get stuff done sometimes. I wish it weren’t Elon, necessarily. But if you’ve created a system in which you have to make everybody happy, eventually people will be so frustrated they’ll let somebody, you know, give the job to somebody who doesn’t care if he makes anybody happy.

Demsas: One of the objections I hear sometimes from liberals about making government more efficient is that all of these layers of procedure are to protect and prevent against authoritarian impulses. So yes, it’s frustrating and annoying that we have to follow all of these rules, and that there are all these government watchdogs that might sue if you don’t cross your t’s and dot your i’s. And that is annoying when you’re trying to get good policy done. But when you have someone like Donald Trump, for instance, get elected, you’ll be really happy that all of these procedures and layers of government exist. How do you respond to that?

Pahlka: Well, they’re not wrong, of course. And we just talked about trade-offs. This is exactly a trade-off conversation. The reality is that I believe that our lack of results and the slowness of government played a part, maybe not be the leading part, in driving people towards wanting someone who claims, I alone can fix it, right? Who claims to be able to bust through all that red tape.

Now, in reality, did he bust through a lot of red tape in his first administration? Well, he claimed to roll back a lot of regulations, but his team really didn’t do that much on that front. But it is a trade-off you make. I am not extreme on either end, but I do think we need a middle ground where we are looking at where safeguards and processes and procedures and the ability to sue are kind of right-sized, where there are some protections.

But where we are right now is: The extra-extra-large version of protections, which has slowed us down enough that it has driven this force in our society for, like, none, which is the pendulum swinging. I just wish the pendulum would settle a little bit in the middle. But that’s a trade-off we need to make. And we have to, as you say, piss some people off in order to get that, because you’re gonna have to say no to some people to get the job done.

Demsas: I feel like the analogy I’ve used a lot is to the filibuster—

Pahlka: Yes.

Demsas: —which I think that a lot of liberals were worried about when this was being debated more openly. If you get rid of the filibuster, that means Republicans will be able to pass their policies as well.

And I think the thing that’s interesting about this is, one, it’s the question of democracy—like, small-d democracy. Do you want the government to be able to do things such that the public can actually evaluate them? Versus someone who gets into office, and they can’t actually enact a bunch of their priorities. So it’s actually quite unclear what signal you’re supposed to be sending as a voter.

But also secondly, I think there’s, like, an asymmetry here, where if you are a small-c conservative, versus a lower-l liberal, you have different sorts of desires from government. Like, there are a lot more active policies that are trying to be passed by people who are liberal, who are progressive. And so there’s kind of an asymmetry of what gets constrained in that kind of a paradigm.

And so I think that it’s hard because you look at the looming potential changes in a Trump administration, and you think, like, Well, it’s really good that there are all these different ways of constraining this. But in the long run, there’s just this larger question here about whether it’s democratic at all to have that happen. Like, if people are electing an executive, how exactly are we supposed to evaluate that work if after four years, so many of the policies that they promised, whether they’re harmful or whether they’re good, don’t actually get passed?

Pahlka: It’s such a hard question. And yeah, I kind of want to stand on—as uncomfortable as this is—if you think state capacity is important to the country, you kind of have to be okay with people who you, let’s softly say, don’t agree with having it. But we’re in this sort of thermostatic nature of elections right now, and I have no crystal ball, but if the Democrats were to get the White House back in four years or even take back Congress in two years, you really don’t want them to be dealing with this huge incapacity once again, or at least I don’t. And that’s just a tough pill to swallow, but I think it’s one we have to swallow, again in the sense of making trade-offs. I agree—it’s much like the filibuster.

You could also say the Administrative Procedures Act is a lot like the filibuster. It needs to be reformed for all the reasons you mentioned when you talked about NEPA to be able to get these, you know, big infrastructure projects built, because it creates such a huge surface area for attack by minority interests. And if you were to do that today, you would really empower Trump to do a lot of what he couldn’t do last time, and that’s really problematic.

But the reality is it’s not going to get repealed today. Like, if you started working on that now, maybe it would happen at the end of the administration and benefit the Democrats. Now, I know that’s sort of like a Pollyannaish view of it, but at the end of the day, it kind of just does need to get reformed if we’re going to be able to govern at all.

And you used the word democracy, right? If we have the system in which we vote for elected officials, and then they go through that messy political process to say—well, let’s use the example of housing, right—to say, This area needs more housing. We’re going to build more housing, and then a bunch of people who have an interest in having that housing not be built can stop it, is that democracy? We have thwarted the will of what the democratic process actually came up with.

Demsas: Well, Jen, always our last and final question: What is an idea that you had that you thought was good at the time but ended up being only good on paper?

Pahlka: I love this question. You asked it of a guest a couple of episodes ago who answered, “small plates,” which just made me laugh so hard. And now I’m just not ever going to order a small plate at a restaurant again. So I’m just co-signing that.

But I guess my more original answer would be: When I started working with local governments, I really had this sense that more data was better. It was kind of shocking. Sometimes you’d go in there, and you were just like, You’re not making decisions based on data. How awful. We need more. We need more. And then over time, I realized there’s a human aspect to this that we neglect. So there became this whole trend of doing data dashboards for local governments. And then, like, no one looks at them really. They were sort of a lot of work for, in some cases, not much return, depending on the human and cultural and, you know, organizational infrastructure into which they were inserted.

But I also really saw, when I was working on the unemployment-insurance crisis during the pandemic, the ways that a lot of leaders see data as a grade that they’re getting, not a compass that they can use to steer the ship where they need to go. And I really changed my view on, like, what kinds of data are good in, like, a governing context, in a performance-management context, and really now sort of see it as good only if it’s introduced in the right ways and if the people who are supposed to be using it as a compass actually are empowered and encouraged to do that.

[Music]

Demsas: Well, Jen, thank you so much for coming on the show.

Pahlka: Thank you so much, Jerusalem. This was fun.

Demsas: Good on Paper is produced by Rosie Hughes. It was edited by Dave Shaw, fact-checked by Ena Alvarado, and engineered by Erica Huang. Our theme music is composed by Rob Smierciak. Claudine Ebeid is the executive producer of Atlantic audio. Andrea Valdez is our managing editor.

And hey, if you like what you’re hearing, please leave us a rating and review on Apple Podcasts.

I’m Jerusalem Demsas, and we’ll see you next week.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

Donald Trump has said, at different times, that he will pardon some, most, or even all of the January 6 insurrectionists. He’s also said at least once that he would do this on his first day in office, which is imminent. Given Trump’s past rhetoric about the incident (calling it a “day of love”) and the people who were jailed for acts they committed that day (“political prisoners,” “hostages”), his pardons can be understood only as part of his alarming—and alarmingly successful—attempt to rewrite the history of the day that nearly brought down our democracy. But what if the pardon were to come in a different spirit? That could move the country a long way toward healing.

In this episode of Radio Atlantic, we invite the author and scholar Linda Kinstler to talk about a centuries-old legal theory, embraced at calmer times in American history, of “oblivion.” When two sides have viciously different experiences of an event, how do you move forward? You do a version of forgetting, although it’s more like a memory game, Kinstler says, “a kind of collective agreement about how you’re going to move past something that is fundamentally irreconcilable.”

The following is a transcript of the episode:

Hanna Rosin: What if President Joe Biden had pardoned the January 6 insurrectionists—that is, the 1,500 or so people charged with federal crimes related to the riot?

And yeah. I said Joe Biden, not President-Elect Donald Trump.

This is an idea I’ve heard floated around these past few weeks. And on its face, it sounds illogical. Like, why on earth would the outgoing Democratic president pardon people who damaged property or injured law enforcement officers or plotted to overthrow democracy?

Trump has said many times that he will pardon the J6ers. He said he’ll pardon some of them or most of them, or even consider pardoning all of them, at different times. He’s said he’ll pardon them on his very first day in office, which is just in a few days.

Donald Trump: People that were doing some bad things weren’t prosecuted, and people that didn’t even walk into the building are in jail right now. So we’ll be looking at the whole thing, but I’ll be making major pardons.

Rosin: Right. So why would Biden do that, again?

[Music]

Rosin: I’m Hanna Rosin. This is Radio Atlantic.

The answer to that question requires you to zoom out to different countries and different periods of history to understand the long political traditions that pardons are a part of and what, at their very best, they could accomplish. And it matters who does the pardoning and their motive for doing it.

I myself did a lot of research on the January 6 prosecutions for a podcast series I hosted for The Atlantic called We Live Here Now. And as I was researching, I came across a couple of articles by author and journalist Linda Kinstler that helped me understand these cases and this charged political moment in a new way. Linda is a junior fellow at the Harvard Society of Fellows. She writes about politics and collective memory, and she’s written for many publications, including The Atlantic.

She’s also working on a new book about the idea we’re talking about today, which is: oblivion.

[Music]

Rosin: Linda, welcome to the show.

Linda Kinstler: Thank you for having me.

Rosin: Absolutely. So the J6 prosecutions are, for the most part, unfolding at the federal courthouse in D.C., just a few blocks from where we are now. Linda, you attended some of these cases. I did also. What is your most vivid or lasting impression from these trials?

Kinstler: Oh, wow. I mean, I spent months—I mean, the better part of a year, actually—attending these trials in downtown D.C. And there are so many elements, as you have described, about the courthouse—namely, that it’s right across from the Capitol and overlooks the grounds upon which all of these crimes happened. And there were so many times I was walking through the halls of the courtroom. And some of them had little windows you can peer through, and almost on every single one—there was one day when you could see in the monitors in the courtroom, and you could see that they were all playing January 6 footage.

[Crowd noise from January 6]

Kinstler: You know, different angles. You could hear the sounds of the footage that the prosecuting attorneys had assembled.

[Crowd noise from January 6]

Man: [indistinguishable] We’re trying to make our way through all this.

Kinstler: And you really do get the sense there that in this building, this really pivotal event in history is being litigated and worked through in real time—kind of away from the public eye, even though these are open to anyone who wants to come see them.

[Crowd noise from January 6]

Man: We need to hold the doors of the Capitol.

Rosin: A few of these cases have stuck with Linda, for different reasons. One was the hearing of a member of the Proud Boys: It was the juxtaposition of this violent offender and his young kids, who were playing around on the courthouse benches at his sentencing.

And the other was a woman, a nonviolent offender with no prior record.

Kinstler: She just kind of walked through the building and clearly made horrible, horrible choices that day, as many of them did who were there. And she repented before the judge. And the judge said, I’m choosing to view this as an aberration in your life, as a kind of lapse of judgment. And she cried.

[Crowd noise from January 6]

Man: [indistinguishable] We’ve lost the line. We’ve lost the line. [indistinguishable] Get back.

Rosin: And did you feel—how did you feel in that moment? Did you feel like, Oh, there’s some injustice being done? Or not quite that?

Kinstler: No. I mean, I think this is justice, right? This is actually the levers of justice working. It is absolutely that these people broke the law, and they are being brought to court because they violated public order in different ways, so it is kind of like our ur-definition of justice.

But it’s a different question—and I think this is the one that has kind of been left undealt with in public, is: Okay. This is one version of justice, but this is not a kind of public reckoning with what January 6 was. And the, kind of, how these individual offenders are being treated and punished for what they did is not the same thing as, How is the country going to deal with what January 6 threatened to, kind of, the fabric of democracy? Those are two separate questions, I think.

Rosin: Interesting. So what you’re saying is: There is a legal process unfolding. The courts can do what the courts can do. But what you’re saying is the courts can only do so much.

Kinstler: Correct.

Rosin: Yeah. Okay.

Kinstler: Right. And there’s, in general, been an overreliance, I think, upon the legal process to deal with January 6 for, quote-unquote, “us”—for us, the public—in a way. And I don’t think there has been a broader conversation about what it means in the long haul.

Rosin: Okay. I want to take what you just said and compare it to the public conversation that is happening around these court cases—namely, from Trump, because we’re a few days from him taking office.

Announcer: Ladies and gentlemen, please rise for the horribly and unfairly treated January 6 hostages.

[Recording of “Justice for All” by the J6 Prison Choir]

Rosin: And the way he puts it is that the J6ers were treated unfairly, persecuted by the justice system; they’re hostages. He’s said this in many different ways, with many different degrees of passion throughout the course of his campaign.

Trump: Well, thank you very much. And you see the spirit from the hostages—and that’s what they are, is hostages. They’ve been treated terribly and very unfairly, and you know that.

Rosin: What do you think of that argument, and how does that fit into what you are saying?

Kinstler: Yeah. On the face of it, what they are doing is manipulating historical terminology, right, for their political ends.

Rosin: So you don’t think they were unfairly—your argument is not at all that they were unfairly persecuted.

Kinstler: No, no. I mean, I think that they broke the law, and they should be punished for what they did. I think there’s a genuine argument you could have about which offenders should be facing jail time, but I don’t think that’s the conversation we’re having right now.

But I do think what this question raises is the fact that Trump himself has not been held accountable for what he did on January 6, right? And there were many efforts to do that. And my view of this whole process is that, historically speaking, we’re doing it backwards. Historically, it was the top people in power who oversaw the crime, who would be the first to be held responsible for what they had done.

In this case, we have almost the exact opposite, right? We have the lower-level offenders—the people who are easier to find, the kind of foot soldiers of Trump’s movement—who are being the ones hauled into court. And, obviously, we have seen: The efforts to prosecute Trump himself have sequentially collapsed and now are almost certainly not going to happen.

Rosin: Do you have an example in your head of a time when, historically, it unfolded in the correct way? Like, a way that promotes a sense of fairness and justice?

Kinstler: Yeah. I mean, this is the kind of subject that has fascinated me for many years—is, like: How have societies worked through moments in which you have a population of perpetrators or people who have violated the public order, who nevertheless must remain in the country or the city in some way? How have you dealt with that?

And so in my work, the prototypical example comes from ancient Athens after the reign of the Thirty Tyrants, where you had a population of oligarchs—30 of them—who overtook the city, stripped people of their rights and properties, killed people unjustly, oversaw all of these abuses, and then were deposed by the victorious democrats. After the fact, there was a kind of general amnesty for most of the supporters of the Thirty. But the Thirty Tyrants themselves were made to choose between standing trial and exile from the city.

So in that case, you have this prototype of the people who are responsible having to account for their crimes—verbally and in, you know, a kind of legal system—while the lower level of people were offered a different set of choices.

And, of course, the reason this is so fascinating is because this becomes the blueprint for centuries of leaders after that: if you look at 1660, after the English civil war; it kind of comes after World War II, where there’s this question of, What do we do with Nazi perpetrators? How wide and deep should the justice run? And we know that denazification failed in many ways. So I do think, in our country, we are going through something like this, in a sense.

Rosin: Can we talk about Nazi Germany for a minute? I mean, I realize we always have to be careful when we’re making historical comparisons to Nazi Germany. But you threw out this sentence, Denazification didn’t work. There were, though, a lot of higher Nazi officials who were held accountable. So how can we use what happened in Nazi Germany to inform what you’re saying we have to figure out right now?

Kinstler: Right. So yes, of course. Saying denazification didn’t work is a huge, sweeping claim, and we can argue about that a lot. But what you had there was the Nuremberg trials—of course, what we think of as Nuremberg—did hold the top brass accountable for what they had done. And then you had many, many smaller, sequential trials, both in West Germany and in the former Soviet Union.

But what I often think of—and I want to be careful about making the comparison today, of course—but I have been thinking about this line that the philosopher Judith Shklar said, which was that why denazification failed, in many ways, was because the prosecutors mistook a group of individual offenders for a social movement. So in other words, they thought that by continuing with all these trials that they would squash the kind of violent, virulent sentiment underlying Nazism itself.

Rosin: Which holds some intuitive appeal because you think, I’m holding people accountable. That’s what we’re supposed to do as a society: hold people accountable.

Kinstler: Totally. And it feels good. It appeals to all of our liberal sensibilities about how order and justice are supposed to work.

Rosin: And particularly—you say liberal, because I think right now, we do have this divide where Democrats, or maybe the left, are trusting in institutions, and the right is a lot less trusting in institutions. So Democrats are putting their faith, in this case, in this institution—the court—to go through the paces and do the right thing.

Kinstler: Exactly. We are in a very legalistic society, in that we like to talk about courts and legal cases as solving political problems. And I do think we repeatedly have seen that over the last however many years—about, you know, Oh, maybe the courts will save us from Trumpism writ large. And we have seen, of course, that the legal system is just not capacious enough to do that for many reasons.

Rosin: That’s a really interesting and concise way of looking at it. We have been relying on Jack Smith, the cases against Trump, these January 6 cases, of which there are, you know, 1,500. What’s the gap? What does the legal strategy leave out?

Kinstler: I mean, so much, in that it’s just a legal strategy, right? It doesn’t—and I think I can kind of see this in the almost allergy that people have when talk of pardons comes up, for example, right? There’s this notion that if you pardon someone, you’re letting them off the hook. But that’s not what a pardon does. A pardon confirms the crime.

And I guess I’m saying there is this paucity of a wider understanding of what happened that day because it has become this legalistic football, right? Of, like, Who was standing where? Who was part of the mob? What does it mean to be part of the mob? Who was commanding them? Etcetera, etcetera. You get lost in all these details and all these individual cases. And, of course, this is the role of historians, to say, This is what that event did that day, and this is its lasting impact.

But that’s what I’m saying—that’s the gap, right? The gap is: What is the narrative of this event? How do you protect it from manipulation, particularly when the person who’s about to be inaugurated has been one of its kind of manipulators in chief? And I do think there are answers.

Rosin: Okay. Let’s just ground ourselves in the moment we’re in. (Laughs.)

Kinstler: (Laughs.)

Rosin: Let’s say, on day one, Trump does what he has many times said he’s going to do: pardon the J6ers.

Trump: I’m going to be acting very quickly.

Kristen Welker: Within your first 100 days? First day?

Trump: First day.

Welker: First day?

Trump: Yeah. I’m looking first day.

Welker: And issue these pardons?

Trump: These people have been there—how long is it? Three or four years?

Rosin: Is it possible that it accomplishes any of the goals of putting this to rest? Like, any of the goals of reconciliation?

Kinstler: I mean, reconciliation, I think, is a different question. I think it’s not going to accomplish that. I think the only sense in which it “puts it to rest,” quote-unquote, is that it will, as I said, confirm their crimes, right? A pardon does not erase what people did.

It’s unfortunate, in my view, that Trump will be the one to pardon them, because I do think there was an opportunity for the Democrats to extend a kind of grace towards some of the January 6 offenders—and by no means all of them—if they had been the ones to pardon them.

Rosin: Okay. You said that casually, and there have been a few law professors who floated that idea. It is, on its face, a kind of shocking idea. Like, when you read a headline that says, Should Joe Biden pardon the J6ers? it’s actually kind of hard to get your head around. What do you think of that idea?

Kinstler: Well, I think, first of all, historically, pardons have been almost a routine thing that any new ruler or president has done upon taking office.

Interviewer: Are you glad that you pardoned those people that went to Canada, the draft evaders?

Jimmy Carter: Yes, I am.

Interviewer: Why?

Carter: Well, it was a festering sore and involved tens of thousands of young men.

Rosin: Like, I was reading about Jimmy Carter, who pardoned draft dodgers, and thinking that, like, we can look in retrospect and say they were peaceful, and the January 6ers were violent rioters. But it must have been hurtful to a lot of people whose children, or who they themselves, went to Vietnam, didn’t want to. And it was quite controversial. So to what end does a new president pardon people?

Kinstler: Well, I mean, on the face of it, it’s a gesture of goodwill. But it’s supposed to say, We are all subject to the law, and let’s start on the right foot, etcetera, etcetera.

Rosin: So it sets a national mood.

Kinstler: Yeah.

Rosin: It sets a mood of, I’m the president for all of you. We’re all in this together. And the value of this country is mercy. Mercy is a value.

Kinstler: Yes.

Carter: So after I made my inaugural speech, before I even left the site, I went just inside the door at the national Capitol, and I signed the pardon for those young men. And yes, I think it was the right thing to do. I thought that it was time to get it over with—I think the same attitude that President Ford had in giving Nixon a pardon.

Gerald Ford: We would needlessly be diverted from meeting those challenges if we, as a people, were to remain sharply divided over whether to indict, bring to trial, and punish a former president who is already condemned.

Rosin: I was looking for historical precedent and read about George Washington and the Whiskey Rebellion, because that was a fairly violent rebellion—and it was hundreds of people—and he pardoned some of them. And I was wondering if that was analogous.

Kinstler: Yeah. I mean, I don’t know about the analogy, but it is kind of an instance in which you have a violent community of offenders who nevertheless must remain in the country, right?

Ford: The power has been used sometimes as Alexander Hamilton saw its purposes: “In seasons of insurrection … when a well-timed offer of pardon to the insurgents or rebels may restore the tranquility of the commonwealth; and which, if served [sic] to pass unimproved, it may never be possible afterwards to recall.”

Kinstler: You can’t get rid of all of them. It wasn’t moral forgiveness. It was just a measure that allowed them to remain in the society in a way that wouldn’t cripple the society itself at this moment of extreme fragility.

[Music]

Rosin: So yes, there are presidential pardons. But if we can neither forgive nor forget something, we just may need something else to move forward: an act of oblivion.

That’s after the break.

[Music]

[Break]

Rosin: Linda, you have researched and written about what’s called “an act of oblivion.” Can you lay out the basics of what that is?

Kinstler: Yes. So historically speaking, we see that there were either acts of oblivion, laws of oblivion, or articles of oblivion that appeared in peace treaties or as legislative measures or as kind of kingly edicts that were issued in the aftermath of revolutions, wars, and uprisings. And what they were, essentially, is a kind of resetting of the legal order, where they said—and this is generally happening in the, quote-unquote, “Western world,” but we also see similar measures elsewhere.

But what they would say is: Everything that happened prior to this law—whatever it was, whether hostility, war, killing, theft, etcetera—none of that can be litigated or spoken of, quote, “in public,” which often meant: You can’t bring a lawsuit after this measure is passed.

Rosin: So it’s not actual forgetting. It’s like a public declaration that we shall all forget together.

Kinstler: Right. And in some ways, forgetting isn’t even the right word. And the interesting thing to me is that the word oblivion is the kind of Roman invention that was used to describe it, that Cicero used after the fact, and that was kind of like his spin on it, right? And everyone is telling tales about how to make a democracy work or how to make a state or a kingdom work, right? Not all of these are democracies.

But, yeah, forgetting is, in some ways—it’s not really the correct description of what’s going on. It’s more of a kind of collective agreement about how you’re going to move past something that is fundamentally irreconcilable.

Rosin: Got it. It’s almost a funny word. Like, I’m gonna blast you into oblivion. It’s a very powerful word. I don’t know if it was meant as kind of campy—probably not—by the Romans. (Laughs.) But there is something kind of, like, huge about it, you know?

Kinstler: Yeah. Oblivione sempiterna: “eternal oblivion,” to kind of wash away everything. It’s a totally beguiling word, and it kind of connotes erosion, in English, and erasure. But there’s also, in other languages: in Russian it’s вечное забвение, “eternal oblivion,” right? Eternal forgetting, in a way.

Rosin: So it’s almost so grand and big that it’s not connected to the mundane act of, Oh, I forgot my keys.

Kinstler: (Laughs.)

Rosin: Like, it’s almost so big that it’s on a grand, national scale. Maybe it’s something like that.

Kinstler: Yeah, I mean, like, you’re always rescuing things from oblivion or losing things to oblivion. I mean, it is in a way, right? Because you’re burying something in oblivion. It’s a physical location, right? It’s a noun, oblivion. And so to me, I think of it as, Okay, you’re burying it, but you’re not forgetting where it is, right?

Rosin: Right.

Kinstler: It’s always there.

Rosin: So what’s the difference between what you just described and whitewashing, revisionist history—sort of what we’ve seen happen with January 6 and Trump calling it a “day of love”?

Trump: But that was a day of love from the standpoint of the millions—it’s, like, hundreds of thousands—

Rosin: Like, sort of actively describing it as something it wasn’t. Can you compare those two modes?

Kinstler: Yeah. I would say they’re kind of fundamentally opposite, right? One is constructive, and one is malignant, right? Which is not to say that the two couldn’t be conflated. But for the sake of argument, the oblivions I have been looking at have been kind of, like, ideal types. Obviously, none of these, historically, ever work perfectly, right? It’s more about the idea that people wanted them to work, that there was this desire for reconciliation that would be operative.

And obviously, that’s not what you see at all in the language that Trump has been using and in the way he and his supporters have been framing January 6. Usually, I think, if we were to follow the framework of oblivion, what should have happened was that Biden—upon taking office and kind of restoring liberal order, we could say—would have passed an act of oblivion for the January 6ers that would have mandated that, kind of, Trump and his immediate circle would have to stand trial for their actions that day. And what we have been seeing with the lower-level offenders, that some of them would not have had to explicitly, as a kind of gesture of goodwill.

Rosin: A couple of challenges I can think of to using this approach with January 6: The first, surface one is just the sheer amount of documentation, YouTube videos. Like, what you’re describing—which is a clever act of forgetting or a memory game—I mean, if you’re a prosecutor working in the federal courthouse, this is a gift. You’ve seen these trials. Basically, what you’re doing at these trials is watching videos. Like, some Facebook video that somebody made, saying, Hey. I was at the Capitol. I did this—me. Nobody else did this.

Kinstler: Yeah.

Rosin: Literally, that’s what some of them say because they’re proud in that moment.

[Crowd noise, chanting from January 6]

Man: Whatever it takes. I’ll lay my life down if it takes. Absolutely.

Rosin: And then—I mean, there’s footage from everywhere.

Kinstler: Yeah.

[Crowd noise, overlapping screaming from January 6]

Rosin: So since you are talking about historical examples: What do you do with an era in which everything is über-documented?

Kinstler: Yeah. And it’s actually interesting. I was in a couple of trials where the judge, to the prosecutor, was saying, Listen. I’ve been to so many of these trials. You do not need to establish for me what happened on January 6 writ large. Like, I get it. Can you please fast forward?

But I guess what I’m talking about is not even about, Oh, you know, keep these videos from circulating, or, Don’t talk about what happened. It’s more about: Don’t expect the legal process to achieve something that cannot be achieved through law.

Rosin: Okay. That makes sense. You just have to accept the fact that the footage is everywhere. The footage is—in fact, maybe that makes what you’re saying more urgent. Because I do find, even with myself—like, if I hear a Capitol Police officer on the radio, if I watch that A24 movie that’s a documentary about January 6, it’s, like, right there all over again, and you just have to be, maybe, aware that that’s the age we live in.

Kinstler: Right.

Rosin: Second question I have is: I read your various articles you’ve written about oblivion. And it almost scared me, reading them, only because we live—this is the first era that I’ve lived through, as an adult, where I’ve watched the revising of history happen in real time. I don’t recall a president talking about facts the opposite of what I saw with my own eyes.

It’s a very bad feeling. So in that context, I feel nervous about even entering into a conversation about oblivion, memory games, or anything like that. And I wonder how you’ve squared that.

Kinstler: Oh my gosh, absolutely. This is what fascinates me, precisely because we are in this era of, kind of, historical revisionism, and we have been in for a long time. But the thing about acts of oblivion is that they actually, in my mind, consecrated what happened, right? They protected the historical record. They didn’t literally say, Oh this never happened. And in fact, what you see is that they’re often accompanied by records—like, historical accounts—of what happened, such that an act of oblivion was necessary, right? Like, Okay, actually, what happened here was a civil war or a tyranny or a revolution that totally wiped out the legal order, so we needed to do this extremely drastic thing if we were to reestablish democratic law.

The one that I often point to is: After the Revolutionary War, there were—because you did have the kind of legacy of British law, right—acts of oblivion came to the Americas from the European system. So there you did have, kind of, royalists who were subjected to acts of oblivion. It was individual states passing them over their royalist populations to allow them to remain, even though they had been defeated.

Rosin: So it was essentially an act of mercy saying, The royalists are going to live among us. They’re not going back. And what? How did it define—

Kinstler: It meant that they couldn’t be ostracized, essentially. They couldn’t be perpetually held accountable for what they had done, for everything that they had done against their neighbors, right? And often, it was a kind of very local, proximate question of, like, We’re not going to kick you out unless you want to be kicked out. That kind of thing.

Rosin: So you could imagine that kind of thing would be controversial at first. People would want vengeance. And so in the immediate, it would be difficult to swallow. But then in the long term, it would put things to rest. That’s the idea.

Kinstler: Yeah. And, I mean, there are a lot of failed oblivions. After the Civil War, a lot of the Southern states were, quote-unquote, “crying for an act of oblivion.” And it was a term that was circulating in the papers. And there’s this amazing quote from Frederick Douglass, who said, you know, I look in Congress, and I see the solid South enthroned, and the minute that that is not the case, we will join you in calling for an act of oblivion, but as long as they have not been held accountable, we cannot support this.

Rosin: Okay. So let’s move to the current moment. If you were King Linda—

Kinstler: (Laughs.)

Rosin: So is what you would want an act of oblivion around January 6?

Kinstler: No. No. Because I would never be so bold as to say that. But I do think it’s a useful political concept. I think that there was a missed opportunity during the Biden administration to do something concerted—that wasn’t just the Jack Smith investigation—about it. I think there could have been something really meaningful done.

Rosin: Okay. So you’re not going all the way to saying, you know, an act of oblivion. But you’ve started to eke at little things. Like, what do you mean by Biden could have? I mean, we’re in the very, very last days of the Biden administration. But if he had pardoned some of the low-level offenders, would that have been in the spirit of oblivion?

Kinstler: Yeah. I think that would have been a really potentially transformative thing to do, because it would not have done anything to jeopardize the record of what occurred that day or what it meant to participate in it.

But we are going to move beyond it, and I think we will see the narrative of January 6 begin to settle in some way, right? And as always happens, the conspiracies about it will become part of the narrative of how this is told, right—not in a kind of whitewashing way, but just in, like, it shows how volatile it is and how manipulable.

And I think there’s been this debate about how to memorialize that day, whether it’s through a physical memorial, a memorial to the Capitol officers who died, or to anyone who died that day. I think those are the questions that we haven’t kind of figured out, really.

Rosin: I see. So there is a potential that, even though we’re not figuring them out now, they’ll be figured out in a sideways way through questions down the road—like, questions about how we will ultimately remember that day—not necessarily how we’ll remember it in this charged political moment, but how we’ll remember it 10, 20 years from now.

Kinstler: Yeah. I mean, I was at the Capitol for the year anniversary of January 6 and watched all the ceremonies from the press gallery. And it just struck me how it was almost like a kind of nothing. You know, like how it was—

Rosin: What do you mean?

Kinstler: It was just so quiet, somber, of course. But there was no fan—you didn’t get the sense of the enormity of the event that was being consecrated, right? And it was almost like—and understandable because it was so close and so terrifying—there was this sense that we haven’t figured this out yet.

William Hungate: The Subcommittee on Criminal Justice of the House Committee on the Judiciary today welcomes the president of the United States, Gerald R. Ford.

Ford: As a people, we have a long record of forgiving even those who have been our country’s most destructive foes. Yet to forgive is not to forget the lessons of evil and whatever ways evil has operated against us.

[Music]

Rosin: This episode of Radio Atlantic was produced by Jinae West and edited by Claudine Ebeid. It was engineered by Rob Smierciak and fact-checked by Sara Krolewski. Claudine Ebeid is the executive producer of Atlantic audio, and Andrea Valdez is our managing editor.

I’m Hanna Rosin. Thanks for listening.

Subscribe here: Apple Podcasts | Spotify | YouTube | Overcast | Pocket Casts

People have long worried about robots automating the jobs of truck drivers and restaurant servers. After all, from the invention of the cotton gin to the washing machine, we’re used to an economy where technology transforms low-wage, physically arduous work.

But the past few years have shown that highly educated white-collar workers should be the ones bracing for artificial intelligence to fundamentally transform their—I should probably say our—professions. The angst this has spurred from all corners of white-collar America has been intense, and not without merit. AI has the potential to take over much of our creative life, and the risks to humanity are well documented.

The discourse around AI has focused so squarely on the terrifying risks and potential job losses that I’ve noticed there’s been very little discussion around why so many people are working so hard to create this doom monster in the first place.

On today’s episode of Good on Paper, I’m joined by someone researching what happens when AI enters a workplace. Aidan Toner-Rodgers is a Ph.D. student of economics at MIT and has a working paper out on what happened to scientific discovery (and the jobs of scientists) when an R&D lab at a U.S. firm introduced artificial intelligence to aid in the discovery of new materials.

Materials science is an area of research where we can see the direct applications of scientific innovation. Materials scientists were the ones who developed graphene, thus transforming “numerous products ranging from batteries to desalination filters” and photovoltaic structures that “have enhanced solar panel efficiency, driving down the steep decline in renewable energy costs,” Toner-Rodgers writes. There are also countless more applications in fields such as medicine and industrial manufacturing.

New discoveries in this field have the potential to transform human life, making us happier, healthier, and richer. And when scientists at this company were required to integrate an AI assistant in generating new ideas, they became more productive, discovering 44 percent more materials.

“I think a big takeaway from economic-growth models is that in the long run, really, productivity is the key driver of improvements in living standards and in health,” Toner-Rodgers argued when we spoke. “So I think all the big improvements in living standards we’ve seen over the last 250 years or so really are driven fundamentally by improvements in productivity. And those come, really, from advances in science and innovation driving new technologies.”

The following is a transcript of the episode:

[Music]

Jerusalem Demsas: What is the point of artificial intelligence? Why, when there is so much concern about the potential consequences, are we hurtling towards a technology that could be a mass job killer? Why, when we face so many competing energy and land-use needs, are we devoting ever more resources to data centers for AI?

There are good reasons to worry about its negative consequences, and the media has a bias toward negativity. As a result, we don’t tend to explore these questions.

My name’s Jerusalem Demsas. I’m a staff writer at The Atlantic, and this is Good on Paper, a policy show that questions what we really know about popular narratives.

Today’s episode is about one of the best applications of AI: helping push the boundaries of science forward to make life better for billions of people. This isn’t a Pollyannaish conversation that skates past concerns with AI, but I do want to spend some time investigating the ways that this technology could improve our lives before we get into the business of complicating it.

In some ways, this conversation isn’t just about AI. It’s about technological progress and the trade-offs that come with it. Are the productivity benefits of AI worth all the downstream consequences? How can we know?

My guest today is Aidan Toner-Rodgers. He’s a Ph.D. student in economics at MIT with a fascinating new working paper that shows what happens when scientists are required to begin using AI in their work.

Aidan, welcome to the show!

Aidan Toner-Rodgers: Thanks so much for having me.

Demsas: You have a really great paper that I’m interested in talking to you about, but first I want us to sort of set the stage here a bit about productivity. So productivity is something that economists talk about a lot, and I think it can be ephemeral to people about why it’s so important.

So why do economists care about productivity?

Toner-Rodgers: Yeah, so I think a big takeaway from economic-growth models is that in the long run, really, productivity is the key driver of improvements in living standards and in health. So I think all the big improvements in living standards we’ve seen over the last, like, 250 years or so really are driven fundamentally by improvements in productivity.

And those come, really, from advances in science and innovation driving new technologies. So when economists think about what are the most important drivers of living standards, it really is kind of coming back to productivity.

Demsas: Yeah, and I think that sometimes it’s useful to think about ways in which society gets better, right?

Like, most increases in inputs—so if you increase labor, it means you have less leisure time. And if you increase investments in capital, that means you’re lowering your current consumption. So you’re moving away from buying things that you may want in order to invest in the future, and if you’re increasing material inputs, that reduces natural resources.

So the idea is: How can we get more efficient? And one stat that I like to point to is that “productivity increases have enabled the U.S. business sector to produce nine times more goods and services since 1947 with a [pretty] small increase in hours worked.” So we’re just getting a lot more stuff without having to kill ourselves working to get it. And that can be, you know, just clothes and things like that, but that can also be services. Like now, because it’s really easy to produce a T-shirt, you need less people making T-shirts, and they can teach yoga or do other things. And so I think that’s really important to set the stage here.

But I want to ask you, because your paper is about AI, about this bet that I wonder which side you take on. There’s this bet—I don’t know if you’ve heard about it. It’s between Robert Gordon and Erik Brynjolfsson. Have you heard about this bet?

Toner-Rodgers: I don’t think so, actually.

Demsas: Okay, yeah. It’s basically a $400 bet to GiveWell, so I don’t know if it really has the impact of me making people put their money where their mouth is.

But Robert Gordon is an economist. He’s kind of a longtime skeptic of digital technology’s ability to match the impact of things like electricity or the internal combustion engine. And his argument, basically, is just that he doesn’t expect AI to have a significant impact on productivity. And he argues that because, you know—he points at things like how the U.S. stock of robots has doubled in the past decade, but you haven’t seen this massive revolution in production, productivity growth, and manufacturing. And he also says that AI is really nothing new. You know, we’ve had human customer-service representatives replaced by digital systems without much to show for it. And then he also says things like a lot of economic activity that is relevant to people’s lives, like home construction, isn’t really going to be impacted by AI.

So it’s one side of the debate. It’s kind of more pessimistic on AI. And the other is kind of represented by Erik Brynjolfsson—he’s more of a techno-optimist—and he argues that recent breakthroughs in machine learning will boost productivity in places like biotech, medicine, energy, finance, but it’ll take a few years to show up in the official statistics, because organizations need time to adjust.

Again, they’re only betting $400, so I don’t know if they’re putting their money where their mouth is, but whose side do you kind of take in this debate?

Toner-Rodgers I mean, I think I’m probably more on Erik’s side. So Robert Gordon’s research, I think, has done a great job showing that over the past 40 years or so there’s been this big stagnation, kind of, in innovation in the physical world.

But I think something I’m really excited about in AI is that all these advances in digital technologies, computing power, and algorithms maybe can now, finally, have this impact kind of back to physical infrastructure and physical things in the world. So I think, actually, materials science is a great example of this, where we have these kinds of new AI algorithms that can maybe come up with new important materials that can then be used in physical things.

Because I think a lot of the advances in information technology so far haven’t had big productivity improvements, because they were kind of confined just to the digital world, but now maybe we can use these breakthroughs to actually create new things in the world. And I do think the point—that there’s a lot of constraints to building things, and a lot of the barriers to productivity growth are not, like, we don’t know how to do things, but there’s just big either regulatory or other barriers to building things in the world—is very important.

And I think that’s why the people who are super optimistic about AI’s impact—I think I’m a bit more pessimistic than them because of these kind of bottlenecks in the world. But I’m very excited about things—like biomedicine, drug discovery, or materials science—where we can maybe create new actual things with AI.

Demsas: So materials science, I think, is the place where your research really is focused. So can you just set the stage for us? What type of company were you looking at, and what kind of work are the employees doing?

Toner-Rodgers: Yeah, so the setting of my paper is the R & D lab of a large U.S. firm which focuses on materials discovery. So this involves coming up with new materials that are then incorporated into products. And so this lab focuses on applications in areas like healthcare, optics, or industrial manufacturing.

And so the scientists in this lab, many hold Ph.D.s or other advanced degrees in areas like chemical engineering or materials science or physics. And what they’re doing is trying to come up with materials that have useful properties and then incorporate these into products that are then going to be sold to consumers or other firms.

Demsas: And help us set—what do you mean by materials? Like, what are we trying to find here?

Toner-Rodgers: So in some sense, everything in every product uses materials in important ways. Like, one estimate I have in the paper: Someone was kind of looking at all-new technologies and products—How important were new materials to these?—and he found that two-thirds of new technologies really relied on some advance in discovering or manufacturing at scale some new material. So this could be anything from the glass in your iPhone, to the metals in semiconductors, to different kinds of methods for drug delivery. So this is like a lot of the technologies in the world really are relying on new materials.

Demsas: Yeah. I mean, you note in your paper that materials science is kind of the unsung hero of technological progress. And when you start to think about it, it really just adds up. Like, basically every single thing that you could care about, it ends up boiling down to specific materials that you want to find—so whether it’s computing or it’s biomedical innovation, like you said, but also just stuff that we’ve been surprised by recently, like the lowering costs of solar panels. Like, new photovoltaic structures being found is helping drive down the cost of those renewables.

So all these different things—and I think it’s funny, because, I mean, we are an increasingly service-sector-based economy. So I think that we’re kind of abstracted away from some of the materials’ impact on our lives, because we just don’t really see it in our day-to-day. But it’s just as important. I think the pandemic really showed this one when we were missing semiconductor chips.

Toner-Rodgers: Yeah, maybe an economics way to put this is that materials science is very central in the innovation network. So there’s been some papers looking at which other fields rely on research from materials science. And it’s really one that’s very central in this network, where things like biomedicine to manufacturing are really relying on new discoveries in materials science. And so kind of focusing on this is a key driver of growth in a lot of areas.

Demsas: And so the scientists in this firm—can you just walk us through what they’re actually doing? Like, what is the process of their work? And then we can get into how AI changed it.

Toner-Rodgers: Sure. So a lot of what they’re doing is basically coming up with ideas, designs for new materials. And then because materials discovery is very hard, many, many of these materials don’t end up having the properties that they hope they do or don’t yield a viable, stable compound. So a lot of what they’re doing is doing tests either in silico tests—like doing simulations—or actually kind of making these materials and testing their properties to see which ones are actually going to be helpful and can later be incorporated into products.

So their time is split. Maybe, like, 40 percent or so is on this initial idea-generation phase, and then the rest is testing these things and seeing which materials are actually viable.

Demsas: When I was reading your paper, I analogized it to coming up with recipes in a kitchen. And you can have a test kitchen or something like that, where basically, if your goal is to come up with a bunch of new recipes for food or for baking or whatever, you may come up with some on paper, and then you’re like, Okay, well, I have to pick which one is potentially going to be a really good recipe, and then you would, you know, test it. And probably you don’t do a simulation. You probably just go make the donut or whatever it is. Is that kind of a good analogy for this?

Toner-Rodgers: Yeah, I think it is, and also just in the sense that we know a lot about the ingredients or sets of elements and their bonds, and we know a lot about that at a small scale, but it becomes very hard to predict what a material’s property will be as these materials become bigger and more complicated. And so even though we know a lot in some small sense, actually prediction gets pretty hard.

Demsas: So AI gets introduced at this company because they want to figure out if that can help their scientists be more productive at coming up with new materials. At what point in the process is AI coming in? What is it actually doing? How does it change the scientists’ jobs?

Toner-Rodgers: Yeah, so AI’s role is really in this initial idea-generation phase. And so how it works is that scientists are going to input to the tool some set of desired properties that they want a material to possess. So in this setting, this is really driven by commercial application because this is a corporate R & D lab. So they want to come up with something that’s going to be used in a product. And then they’re going to input these desired properties to the AI tool, which is then going to generate a large set of suggested compounds that are predicted by the AI to possess these properties.

And so before, scientists would have been coming up with these material designs themselves. And now this part is automated by the tool.

Jerusalem Demsas: So it’s like, Now I’m having an AI tool give me a bunch of potential donut recipes instead of me coming up with them myself.

Toner-Rodgers: Exactly. And I think it’s important to note that this whole prediction process is very hard. And so even though I’m going to find pretty large improvements from the AI tool on average, many, many of its suggestions are just not that good and either aren’t going to yield a stable compound or aren’t going to actually have the other properties that you wanted to begin with.

Demsas: Yeah. And so before we get into your results, which are really shocking to me actually, it’s kind of cool—the company set up a natural experiment, basically, for you. Can you walk us through what they did and how they randomized researchers?

Toner-Rodgers: Yeah. So I think the lab had just a lot of uncertainty going in about whether this tool was going to be actually helpful. Like, you could have thought, Maybe it’s going to generate a lot of stuff, and it’s all bad, or it’s going to kind of slow people down as they have to sort through all these AI suggestions.

So I think they just had a lot of questions about: Is this tool going to work, and are we going to get actually helpful compounds? So what they did, instead of just rolling it out all at once, was to do three waves of adoption where they randomly assigned teams of scientists to waves. And so this allows me, as a researcher, to look at treated and not-yet-treated scientists and identify the effects of the tool.

Demsas: And did they control for different things? Like, did they control for, you know, what types of research they were working on or how many years of experience they had?

Toner-Rodgers: Yeah, so there’s a lot of balance between waves because of the randomization on what exactly these scientists are working on, which types of technologies and materials, as well as just the team composition in terms of their areas of expertise and tenure in the lab and so on.

Demsas: So now I want to turn to the results. What did you find?

Toner-Rodgers: So my first result is just looking, on average, at how this tool impacted both the discovery of new materials as well as downstream innovation in terms of patent filings and product prototypes. So I find that researchers with access to the AI tool discover 44 percent more materials, and then this results in a 39 percent increase in patent filings and then a 17 percent rise in downstream product innovation, which I measure using the creation of new product prototypes that incorporate those materials.

Demsas: These are, like, massive numbers.

Toner-Rodgers: Yeah, I think they’re pretty big. And also, I think it’s helpful to kind of step back and look at the underlying rate of productivity growth in terms of the output of these researchers. So I look back at the last five years before the tool was introduced, and output per researcher had actually declined over this period. So these are huge numbers relative to the baseline rate of improvement.

Demsas: So it’s interesting—well, I guess first: How? Like, why are people becoming more productive here?

Toner-Rodgers: I think there’s two things. So one is just that the tool is pretty good at coming up with new compounds. So being able to train a model on a huge set of existing compounds is able to give a lot of good suggestions.

And then second: Not having to do that compound design part of the process themselves frees scientists to spend more time on those second two categories, kind of deciding which materials to test and then actually going and testing their properties.

Demsas: It’s interesting when I was looking at your results because you’re able to kind of look at, you know, one month after, four months after the adoption of this new AI tool, how it changes things. Things look kind of grim in the short run, right? Like, four months after AI adoption, the number of new materials actually drops. And it’s not until eight months after that you see a significant increase in new materials. And that’s around when you see the patent filings increase. And it’s not until 20 months after that you actually see it show up in product prototypes.

And, you know, part of the problem of trying to figure out if new technology like AI is having a big impact is that it might take a while to show up in statistics. Is that why you think maybe we’re not seeing a massive jump in productivity right now in the U.S., despite the rollout of a ton of new machine-learning tools?

Toner-Rodgers: Yeah, I think that’s partly true. Like, you definitely need some forms of organizational adaptation or people learning to actually utilize these tools well. So part of why there’s this lag in the results is just that materials discovery takes a while. So it takes a little bit to actually go and kind of synthesize these compounds and then go and find their properties.

But another thing I find is that in the first couple months after the tool’s introduction, scientists are very bad, across the board, at determining which of the AI suggestions are good and which are bad. And this is part of the reason we don’t see effects right away.

Demsas: So it’s like your job has changed significantly, and you just need time to adjust to that.

Toner-Rodgers: Yeah, totally.

Demsas: So I want to ask you about material quality, though, because what you’re measuring, largely, is the number of materials made. But has the quality of the materials improved or declined, and how would we know?

Toner-Rodgers: So I think that’s a key concern when you’re doing these things, is we don’t only care about how many new discoveries we’re getting, but what they are. So a very nice thing about my setting and materials science, in general, is that there’s direct measures of quality in terms of the properties of these compounds. And in particular, at the beginning of the discovery phase, scientists define a set of target properties that they want materials to possess.

And so I can compare those target properties to the measured properties of materials that are actually created. And so when I do this, I find that, in fact, quality increases in the treatment group, which is showing that we’re not actually having this compromised quality as a result of faster discovery.

Demsas: So there’s this joke that I was looking up, and apparently Wikipedia tells me it’s attributed to this character from Muslim folklore called Nasreddin, but I could not independently verify this. Most people have probably heard some version of this. It goes: A policeman sees a drunk man searching for his keys under a streetlight, and he tries to help him find it. They look for it for a bit of time, and then he’s like, Are you sure you dropped them here? And the drunk guy is like, No, I lost them in a park somewhere else. The policeman is kind of incredulous; he’s like, Why are you looking for them here? And the drunk guy goes, This is where the light is.

And this has been, you know, referred to by a lot of researchers as the streetlight effect, right? So it’s a phenomenon that people tend to work where the light is or like easiest problems, even if those aren’t the ones that are actually likely to bear the most fruit. Do you think that AI helps us avoid the streetlight effect or it exacerbates the problem?

Toner-Rodgers: So I think talking to people before this project, I would have guessed that it would exacerbate the problem. And the reason is that the tool is trained on a huge set of existing compounds. So you might expect that the things it suggests are going to be just very similar to what we already know. So you might think that because of that, the streetlight effect is going to get worse. We’re not going to come up with the best things but rather just things that look very similar to what we already know.

And I think, surprisingly to me, I find that, in my setting, this is not the case. And so to do that, I measure novelty at each stage of R & D. So first I look at the novelty of the new materials themselves. And to do that, I look at their chemical structures—so the sets of atoms in a material, as well as how they’re arranged geometrically. And I can compare this to existing compounds and see, like, Are we creating things that look very similar to existing materials, or are they very novel?

So on this measure, AI decreases average material similarity by 0.4 standard deviation. So these things are becoming more novel. And it also increases the share of materials that are highly distinct—which I define as being in the bottom quartile of the similarity distribution—by four percentage points. So it seems like, both on average and in terms of coming up with highly distinct things, we’re getting more.

Demsas: This is kind of surprising to me, right? There’s a paper by some researchers at NYU and Tel Aviv University called “The Impact of Large Language Models on Open-Source Innovation,” and they sort of raised this question about whether AI has asymmetric impact on outside-the-box thinking and inside-the-box thinking. And you know, the thing is that most AI systems are evaluated on tasks with well-defined solutions, rather than open-ended exploration. And, you know, models are predicting the most likely next response. Like, what’s happening with ChatGPT is it’s just predicting what the next word is going to be. Or that’s what most of these systems are trying to do. And they’re trained on this corpus of existing stuff, and it’s not like they’re independent minds.

And so they kind of theorize that, you know, AI might be good at finding answers to questions that have right answers or ones where there’s clearly defined evaluation metrics. But can it really push the bounds of human understanding, and does our reliance on it really reduce innovation in the long term? So I mean, this seems to be a really big problem in the field of AI, and I wonder: How confident are you that your findings are really pushing against this? Or is it kind of like, maybe in the short term, there’s some low-hanging fruit that looks really novel, and in the long term, you’re not really going to have that?

Toner-Rodgers: Yeah, so I think one drawback of the measurements I have is that I can see that, on average, novelty increases, but what I can’t see is whether the likelihood of coming up with really truly revolutionary discoveries has changed. And so if you think of science as being driven, really, by these far-right-tail breakthroughs, you’re just not going to see much of these in your data. This has been an issue highlighted by Michael Nielsen in some essays that I like a lot.

And so one kind of thing you might be worried about is, Well, we got, on average, more novel things, but maybe these very revolutionary discoveries have a lower probability of being discovered by the AI, and that in the long term this is not a good trade-off. And because you’re just never going to see very many of these right-tail discoveries in your data, you just can’t say much about this using these types of methods.

Demsas: I mean, how confident, then, are you that we can even test whether this is happening?

Toner-Rodgers: Yeah, I think one answer is that we’ll just need some time to see, like, do these new materials open up new avenues for research? Like, are there other materials that are going to be built on these new ideas that the AI generated? But one thing I’d say is just that I think a lot of people would have said beforehand that, even on average, I expect novelty to go down. And the fact that it went up, I think, does push back somewhat against the view that these things are going to be bad for novelty.

Demsas: And then I guess, kind of on this question of generalizability to other fields, like, materials science is a place, of course, where you can measure productivity pretty cleanly. Like, you can see what the compounds are. You can see what people are trying to look for. A lot of fields, even in science, are not like this. They’re not super easy to measure what exactly you’re trying to find, and innovations can have spurts and stops for long periods of time, even if a lot of work is happening. So I guess, do you expect AI to be as helpful in fields that look a lot less like materials science?

Toner-Rodgers: So I think in the short run, I would say probably not, right? I think there’s areas where it does look a lot like this, like things like drug discovery, but then there’s a lot of areas where it doesn’t look like this at all. I would say, I think kind of fundamentally, this comes down to how much of science is about prediction versus maybe coming up with new theories or something like that. And I think maybe I’ve been surprised over the last several years how many parts of science, at least in part, can have big impacts from AI, right?

So we see in things like math, where maybe it really feels like it’s not a prediction problem at all, like doing a proof, but we see things like large language models and other more specialized tools really being able to make progress in these areas. And I think they’re not at the frontier of research by any means, but I think we’ve seen huge improvements.

So this is absolutely an open question how much these tools can generalize to other fields and come up with new discoveries more broadly. But I would say that betting against deep learning has not had a great track record in recent years.

Demsas: Yeah, fair.

[Music]

After the break: AI doesn’t benefit everyone equally, even when we’re talking about brilliant scientists.

[Break]

Demsas: I want to ask you about the distributional impacts. I think this is probably the most pessimistic, concerning part of your paper. You find that the bottom third of researchers see minimal gains to productivity, while the top 10 percent have their productivity increase by 81 percent. Can you talk through how you’re measuring the sort of productivity of these researchers and this finding, in particular?

Toner-Rodgers: Yeah. So first I kind of just look at scientists’ discoveries in the two years before the tool was introduced. And there’s a fair amount of heterogeneity across scientists and their rate of discovery. And I do some tests showing that these are kind of correlated over time, so it’s not like some scientists are just particularly lucky. And, instead, there do seem to be these kinds of persistent productivity differences across scientists. And then I just look at each decile of initial productivity: How much do those scientists’ output change once the tool is introduced? And we see these just massive gains at the high end. And at the low end, on average, they do see some improvement, maybe 10 percent or so, but nowhere near as much as the kind of initially high-productivity scientists.

Demsas: Why? Like, at what stage are the low-productivity scientists getting caught up? Because, you know, if this tool is just giving them a bunch of potential recipes for new materials, are they just worse at selecting which ones to test, or what’s happening?

Toner-Rodgers: Yeah, so I think the key mechanism that I identify in the paper is that it’s really this ability to discern between the AI suggestions that are going to be actually yielding a compound that’s helpful versus not. So I think just the vast majority of AI suggestions are bad. They’re not going to yield a stable compound, or it’s not going to have desirable properties. And so because actually synthesizing and testing these things is very costly, being able to determine the good from the bad is very important in this setting. And I find that it’s exactly these initially high-performing scientists that are good at doing this. And so the lower-performing scientists spend a lot of time testing false positives, while these high-ability ones are able to kind of pick out the good suggestions and see their productivity improve a lot.

Demsas: But lower-performing scientists aren’t getting worse at their jobs, right? They’re just not really helped by the tool.

Toner-Rodgers: Yeah, that’s true. But I think it’s worth saying that it’s not like they’re not using the tool. So it really is that their research process changed a lot, but because their discernment is not great, it ended up being kind of a similar productivity level to before.

Demsas: And were you able to observe this inequality over time? Was it stagnant? Did it widen? Did it decrease? Was there learning that you were able to see happen with less-productive researchers?

Toner-Rodgers: Yeah. So I think something very interesting is, like, if I look in the first five months after the tool was introduced, across the productivity distribution, scientists are pretty bad at this discernment. So all of them are kind of doing something that looks like testing at random. They’re not really able to pick out the best AI suggestions. But as we look further on, scientists in the top quartile of initial productivity do seem to start being able to prioritize the best ones, while scientists in the bottom quartile show basically no improvement at all. And so I think this is pretty striking. And there’s just something about these scientists that’s allowing some to learn and some to see no improvement.

Demsas: And how long were you able to observe this for? Like, is it possible that maybe they just needed more time?

Toner-Rodgers: Yeah, so I think I see, like, two years of post-treatment observations. So in that time, I don’t see improvement. I think it’s possible either they need more time, or maybe they need some sort of training to be able to learn to do this better. So I think one question: Is this something fundamental about these scientists that’s not allowing them to do this? Or is there some form of either training or different kind of hiring characteristics the firm could look at to identify scientists that are good at this task?

Demsas: So were you surprised by this finding? After reading your paper, our CEO here at The Atlantic, Nicholas Thompson—he pointed out that in studies of call centers, the opposite is often true. For instance, the guy we mentioned earlier, Erik Brynjolfsson, who’s kind of a techno-optimist, and two of his co-authors recently put out a working paper that looks at over 5,000 customer-service agents and found that AI increased worker productivity. And they’re measuring that as issues resolved per hour. And it increases their productivity by 14 percent, with less-experienced and lower-skilled workers improving the speed and quality of their output, while the most experienced and the highest skilled saw only small gains. So I guess, looking at the field, in general, is it strange that you’re seeing the biggest impact happening with the most-skilled people? Should we expect the opposite?

Toner-Rodgers: Yeah, so I think a lot of the early results on AI have found that result that you just mentioned, where the productivity kind of compresses, and it’s these lower-performing people that benefit the most. And I think in that call-center paper, for example, I think one thing that’s going on is just that the top performers are already maybe nearly as good as you’re going to get at being a call-center person. Like, there’s kind of just a cap on how good you can do in this job.

Demsas: You can’t resolve an issue every second. You actually have to have a conversation.

Toner-Rodgers: Right. You kind of have to do it. And they’re maybe close to the productivity frontier in that setting. So that’s one thing.

And I think in materials science, this is just not the case at all. Like, this is just super hard, and these are very expert scientists struggling to come up with things, is one thing. And then I think the second thing is that in the call-center setting, AI is going to give you some suggestions of what to say to your customer. And it’s probably not that hard to kind of evaluate whether that suggestion is good or bad. Like, you kind of read the text and, like, All right, I’m gonna say this.

And in materials science, that’s also not the case—where, like, you’re getting some new compound. It’s very hard to tell if this thing is good or bad. Many, many of them are bad. And so this kind of judgment step, where you’re deciding whether to trust the suggestion or not, is very important. And I think in a lot of the settings where we’ve seen productivity compression, this step is just not there at all, and you can kind of out-of-the-box use the AI suggestion.

Demsas: So do you think a good heuristic is if AI is being applied to a job where there’s a right way to do things that we kind of basically know how to do, or there’s very little sort of experimentation or imagination or creativity necessary to do that job, that you will see the lower-skilled, the less-experienced people gain the most? And then when it’s the opposite, when a lot of creativity is needed, high-skilled people are going to get the most out of AI?

Toner-Rodgers: Yeah, I think that sounds true to me. And I think maybe one way I’d put it is it’s something about the variation and the quality of the AI’s output that’s very important. So even in materials science, I’m not sure that, say, in three years or something, the AI could just be incredibly good and, like, 90 percent of its suggestions are awesome, and you’re not going to see this effect where this judgment step is very important.

So I think it really depends on the quality of the AI output relative to your goal. And if there’s a lot of variation, and it’s hard to tell the good suggestions from the bad, that seems to be the type of setting where we’re seeing the top performers benefit the most.

Demsas: And I assume that with this tool at this company, like, when they come up with successful materials, they’re feeding that information back into the model. Did you observe that the tool was getting better at providing more high-quality suggestions over time?

Toner-Rodgers: Yeah, so they’re definitely doing that. There’s definitely some reinforcement learning with the actual tests. Like, I think over this period, I don’t see huge results like that. I think, relative to the amount of data it was trained on initially and the previous test results that went into the first version of the model, it’s just not that much data. But I think as these things are adopted at scale, we could absolutely see something like that.

Demsas: If that sort of reinforcement learning happens, do you think that that increases the likelihood that AI kind of pushes us down the same sorts of paths? Like, so you get kind of path dependent because you’re basically telling the model, Oh, good job. You did really good on these things, and then it becomes trained to sort of do those sorts of things over and over, and it gets less creative over time?

Toner-Rodgers: Yeah, I think that is definitely a concern. And I think something that people are thinking about is maybe there’s ways to reward novel output, per se. Because I think in these settings, one thing that’s helpful with novel output, even if it’s not actually a good compound, is that you learn about new areas of the design space. And even getting a result that’s very novel and not good is pretty helpful information. So I think rewarding the model for novelty, per se, is maybe one kind of avenue for fixing that problem.

Demsas: So this paper and this field, in general, kind of reminds me of some of the findings in the remote-work space. We had Natalia Emanuel from the New York Fed on the show, actually on our very first, inaugural episode. And you know, we talked about her research on remote work, and one finding that she has is that more-senior people are more productive or have higher gains of productivity when they’re able to go remote, because they stop having to mentor young people, and that is a drain on their productivity in person. They’re having someone younger than you kind of ask you questions, interrupt your day and, like—I’m not saying they hate the job—but that takes away from your ability to just work and not have to focus on other things.

And I wonder if AI becoming the sort of “bouncing off” buddy of scientists, rather than, like, you’re turning to your less-productive lab partner and just kind of tossing out ideas or talking. Instead, you’re sort of engaging with this AI tool, and that’s what you’re using to sort of figure out new methods and materials. Does that change science to become less collaborative with human peers, and does that have those knock-on harms, where maybe these most-productive scientists are getting better, but the less-productive scientists aren’t able to actually get the learning necessary to improve their own productivity?

Toner-Rodgers: Yeah, I think that’s super interesting. And I think a general question about these results are, like: What does this look like in the longer term?

I think something that might absolutely be true is: These people who are very good at judgment might have gotten good at judgment by designing the materials themselves in the past, and this is kind of where you got that expertise. But going forward, if the AI is just used, maybe new scientists that enter the firm never get that experience and maybe never have the ability to get the judgment. And so that’s one reason you could see different effects in the long run.

In terms of the specific question of collaboration, I think that’s something super interesting. I don’t have, really, evidence on that in the paper, because I don’t see good data on how much scientists are communicating with each other. But something I’m very interested in is: We have some scientists that are good at judgment. Like, could they teach whatever that skill is to the people who are worse? And I think one way to get at this, which I haven’t done yet, is: If you have a teammate who’s very good at this task, do you somehow learn, over time, from them? And I think that would be very interesting to look at.

Demsas: And you mentioned, like, how does someone become a high-productivity scientist, and that requires you doing this on your own, potentially. And I wonder—companies, whether they will have the incentive at all to invest in this long-term training when there are these sorts of short- and even medium-run, huge benefits they could get. I mean, you’re talking about massive increases in patents and new technologies they’re able to operationalize and commercialize, even. And if that’s the case, even if everyone knows that there’s this long-term cost to science and to scientists, who is actually incentivized to make sure this training happens until we’re already kind of in a bad place where a lot of technology has stagnated?

Toner-Rodgers: Yeah, I think that makes a lot of sense. Like, there’s kind of a collective-action problem where you don’t want to be the one that’s doing all the training in the short run while all your competitors are, like, coming out with all these amazing materials and products.

Demsas: And then poaching all your people.

Toner-Rodgers: Exactly. I think that’s definitely a concern. But also more generally, I do kind of have some confidence that organizations are going to be able to adapt to these tools and find out new ways to either train scientists for these things, kind of as they’re using them, or be able to, in the selection process for new employees, find predictors of being good at that this new task. Because, in some sense, what we’re saying is that these new technologies are changing the skills required to make scientific discoveries, and I think we’ve seen a long history of technological progress that’s done exactly that—like, changed the returns to different skills—and firms have adjusted to that.

Demsas: What I want to ask you about next is about the survey you did about the scientists’ job satisfaction. Can you tell us about that survey?

Toner-Rodgers: Yeah. So the goal of the survey was just to see both how scientists use the tool and then whether they liked it—how did this impact their job satisfaction?

And so after the whole experiment was completed, I just conducted a survey of all the lab scientists. About half answered. And one thing I found is that, basically across the board, scientists were fairly unhappy with the changes in the content of their work brought on by AI. So what they say is that they found a lot of enjoyment from this process of coming up with ideas for compounds themselves, and when this was automated, their job became a lot less enjoyable. So they say, like, My job became less creative, and some of the key skills that I’d built over time, I’m no longer getting to use.

And I think one thing that’s very striking is this is true both for the scientists that saw huge productivity improvements from AI, as well as the lower performers. And so we really see that it’s not as much dependent on productivity. I also ask, kind of, Well, you’re also getting more productive. Does this somehow somewhat offset your dissatisfaction with the tasks you’re doing at work? And it does somewhat. But overall, I find that 82 percent of scientists report a kind of net reduction in job satisfaction.

Demsas: I mean, that’s kind of depressing, right? Obviously, if you’re told, like, Oh, your work is having a big impact on the world and maybe making life better for people who are sick or who need renewable energy, or whatever it is, that can feel good. But if your day-to-day just sucks, you can imagine there’s gonna be some attrition, right?

Toner-Rodgers: Yeah, absolutely. Because yeah—one thing sometimes people say when they hear this result is, like, Well, scientific discovery is very important. Maybe these new materials are gonna be used by millions of people. Why do we really care about these scientists and how much they’re enjoying their job? But I really think it could have important implications for who chooses to go into these fields and the overall kind of direction of scientific progress. So I think it’s very important to think about these questions of well-being at the subjective, individual level for that reason.

Demsas: I feel like it’s really difficult for me to kind of weigh out what actually happens in the long term here, because I could imagine that the types of scientists who went into these fields were selected for people who really, really enjoyed the creativity aspect of figuring out new materials. Whether or not they’re productive at doing that, like, that’s just the kind of thing you’re selecting for.

And I would analogize it to someone who’s really excited about coming up with new recipes. And I’m someone who likes—I don’t like coming up with new recipes, but some of my favorite recipes are ones where I saw a New York Times Cooking recipe, and then I change some things about it. And as I’ve cooked it a bunch of times, I’ve tweaked some things, and I’ve come up with something that’s sort of my own, sort of already existing. And I can imagine there are a lot of people like that and that the skill of discernment does not necessarily correlate with the skill of loving to be creative.

So you could see shifts happening in the field, right, where the types of people who go into materials science change, and these scientists go do something else where they’re able to be more creative. And you mentioned that a lot of them are thinking about taking on new skills. How do you think that all kind of shakes out?

Toner-Rodgers: This really maybe comes back to the question of training. So I think a lot of these people’s complaints were like, Look—I built up all this expertise for one thing, and now I don’t get to do that thing anymore. And you could think that now if we start training people for this slightly different task, which also requires a lot of expertise, of judgment, that that also is fulfilling. And whether that’s true in the long run, I think I’m not sure.

So one analogy that someone said to me is, like, Well, you’re a Ph.D. student. Imagine if, instead of writing papers, you just did referee reports all the time.

Demsas: Yeah. And sorry—can you explain what a referee report is?

Toner-Rodgers: It’s like you’re looking at someone else’s research and saying, like, It’s good, or, It has these problems.

And that doesn’t sound awesome. Like, it definitely takes a lot of expertise to do a referee report, but it’s not why you got into this—like, you do want to come up with ideas. And so I think I’m very uncertain how this is going to all shake out. I do think that part of it really was, like, I got trained to do a thing, and now I don’t get to do it anymore. And I think that part will go away somewhat, but whether this is just fundamentally a worse job, I think it definitely could be.

Demsas: It’s interesting, the way in which we kind of have always thought of automation as disrupting the jobs of people with less-well-compensated skills—so, like, manufacturing jobs, or, you know, now your job is shifting a lot if you’re someone who works at a restaurant. Now robots are doing some of that work. And you know, there’s just been this kind of pejorative, like, Learn to code! sort of response to some of those people.

And it’s interesting to see that, like, a lot of generative AI is actually really impacting the fields of higher-income individuals, like people who are working in heavily writing fields or like legal fields and now, also, science fields. And it does, really, I think, raise this question of just: Will society be as tolerant of disruptions in those spaces as it has been in disruptions in spaces where workers have had less kind of political and social power?

Toner-Rodgers: Yeah, I totally agree. And I think there really is something different about these technologies where they’re creating novel output based on patterns in their training data, whereas before, like, from industrial robots to computers, it really was about automating routine tasks. And now for the first time, we’re automating the creative tasks. And I think how people feel about this and how we react might look very different.

Demsas: Yeah. I came across this quote from the chief AI officer at Western University, Mark Daley. It’s a blog post. He’s commenting on your paper. He writes, “Because AI isn’t just augmenting human creativity—it’s replacing it. The study found that artificial intelligence now handles 57 percent of ‘idea generation’ tasks, traditionally the most intellectually rewarding part of scientific work. Instead of dreaming up new possibilities, scientists may find themselves relegated to testing AI’s ideas in the lab, reduced to what one might grimly call highly educated lab technicians.”

I don’t know if there’s a survey of scientists or whatever, but I wonder here if you see that there’s a kind of a growing pessimism as a result of findings like this and just, like, the experiences many people are having with AI where they do feel like, Hey, the good part of life—I don’t want AI or robots or technology to be taking away the fun, creative stuff like writing or art or whatever. I want them to take away the drudgery the way that, like, laundry machines took away drudgery or dishwashers took away drudgery. I don’t know how you think about that as a shift in how the discourse is happening on this issue.

Toner-Rodgers: Yeah. I think that’s interesting. And I also think, when I talk to scientists, for example, materials scientists that work on actually building the computational tools, like, they’re super excited about this stuff because they’re coming up with ideas for the tool itself and, like, going and testing it and all these things.

Something in this setting is like: This was a tool that was kind of imposed on these people, not something they kind of created themself. And I think that’s maybe something we’ll see, where the people that are actually having input and creating the new technologies themselves might find, like, they’re very happy with the output, even though these tasks are being automated. Whereas people in this setting, where the tool kind of just came in and changed their job a lot, maybe see kind of big decreases in enjoyment.

Demsas: Well, Aidan, always our last and final question: What is an idea that you thought was good at the time but ended up only being good on paper?

Toner-Rodgers: So I went to undergrad in Minnesota. And for background, I’m from California. So the first winter I was there, me and a couple of friends decided it’d be a great idea to go ice fishing.

Demsas: Okay.

Toner-Rodgers: And so we drive up to this lake. And literally three steps out on the ice, I step on a crack and fall through into this frozen lake. So ice fishing for Californians is good on paper.

Demsas: This is like the scene in Little Women where, like, Amy falls into the lake or whatever. What happened? Was it actually dangerous, or did you just immediately pull yourself out?

Toner-Rodgers: Luckily, we weren’t far from civilization. Like, we were near the car, so we ran back to the car.

Demsas: Oh my God.

Toner-Rodgers: And that was the end of my ice-fishing career.

Demsas: I’m glad you learned this early in your Minnesota life and did not get too adventurous. Well, Aidan, thank you so much for coming on the show.

Toner-Rodgers: Yeah, it was great. Thanks so much.

[Music]

Demsas: Good on Paper is produced by Rosie Hughes. It was edited by Dave Shaw, fact-checked by Ena Alvarado, and engineered by Erica Huang. Our theme music is composed by Rob Smierciak. Claudine Ebeid is the executive producer of Atlantic audio. Andrea Valdez is our managing editor.

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Last month, Donald Trump appointed the venture capitalist Sriram Krishnan as his senior AI-policy adviser. Krishnan, an Indian immigrant and U.S. citizen, was seen by some as being friendly to H-1B visas, which are often used in Silicon Valley to allow skilled laborers to work in the tech industry. This sent part of the MAGA faction into a frenzy, spurred by troll in chief Laura Loomer, who declared the appointment a betrayal of the “America First” movement.

The argument over H-1Bs exposes an important fissure in the MAGA alliance that worked together to help elect Trump. How Trump navigates this rift will give us clues about what his real priorities will be as president.

In this episode of Radio Atlantic, we talk with Ali Breland, who writes about the internet, technology, and politics, about this new rift in Trump’s camp and other places it might show up. And we’ll go beyond the politics, with staff writer Rogé Karma, to discuss what a solid body of research shows about the relationship between immigrant labor and the American worker—because even though some prominent Democrats, such as Bernie Sanders, agree with Loomer that there is a negative effect from H-1B visas on American workers, research doesn’t back them up.

The following is a transcript of the episode:

Hanna Rosin: There are already cracks starting to show in the MAGA alliance, and those cracks happen to show up in the issue that Trump has declared one of his top priorities, which is drastically reshaping U.S. immigration policy. Trump appointed to a senior position someone seen as being friendly to H-1B visas, the visas that allow people with specialized skills to work in the U.S. People in Silicon Valley love these visas. They depend on them. And maybe more importantly, the H-1B visa lovers include Elon Musk.

But the “America First” wing of Trump supporters—sometimes known as the nativist right—they do not love these visas. “America First,” to them, means, literally, Americans first. No exceptions.

I’m Hanna Rosin. This is Radio Atlantic. On today’s show, we’ll talk about this MAGA infighting. In the second half of the show, we’ll get into what’s actually true about the relationship between immigration and the American worker, because it turns out that even a lot of Democrats don’t get that one right. But first, let’s dive into the recent news and what it means. To help me with that is Ali Breland, an Atlantic staff writer who writes about the internet, politics, and technology.

Hey, Ali.

Ali Breland: Hey. Thank you for having me.

Rosin: So, Ali, this fracture in the MAGA alliance seemed to start around Christmas, when Trump announced a senior AI-policy adviser. Who is he, and how did people respond?

Breland: Yeah, his name is Sriram Krishnan. He’s this Silicon Valley figure who has a long history. He works in tech, and he was being appointed to be an adviser on Trump’s AI team, which is being headed up by another big guy in tech: David Sacks, who’s a part of the infamous “PayPal Mafia” that includes Peter Thiel, Elon Musk, etcetera.

Rosin: So these are, like—this is a faction. Like, these guys are becoming more and more powerful, sort of Trump’s tech allies.

Breland: Yeah, there’s some different ideological things happening, but for the most part, they’re largely on the same page. And a lot of people right now are kind of calling them the “new tech right,” or just, like, the “tech right.”

Rosin: So they’re on one side, and then how did the discussion around H-1B visas get going?

Breland: Yeah, so there’s this provocateur troll in Trump World called Laura Loomer. She’s been kind of this weird thing on the right for a long time. She’s chained herself to the headquarters of Twitter in protest of her account being banned at one point. But she sees this appointment, and she decides to make hay of it.

She pulls out a tweet that Krishnan made about country caps for green cards, rather, and high-skilled immigration. And she points to these things and says, This is not what we want. This is not “America First.” These things are not good for our constituency. And so that’s, like, the sort of obvious bit of it.

The other bit, too, is you can kind of see how race is this animating issue in this fight. David Sacks had already been appointed by Trump to be his chief adviser on issues of AI and crypto. David Sacks has talked about H-1B visas. He’s pushed Trump on this. He’s successfully gotten Trump to say that he would support the continued use of H-1B visas.

But Loomer didn’t attack him on that and didn’t turn this into a huge issue. Instead, she went after Sriram Krishnan, who is South Asian. And I think, you know, her targeting him, specifically, on this issue and associating him with that kind of speaks to the sort of nativist sentiment undergirding all of this.

Kind of right after the election, I sort of thought that maybe there was a chance that there was going to be some sort of fractious element at some point in the future, because these are two sides that kind of believe sort of different things.

The tech right is reactionary, like the nativist right that includes people like Laura Loomer, people like Steve Bannon. They sort of all have this streak of being frustrated with the progress that’s taken place in America. They are frustrated with what they see as, like, American weakness. But the distinction is that the tech right also loves business. They love being rich. They love making a lot of money and having their industry be benefitted.

The sort of nativist right cares much more about the American constituency and, specifically, the white American constituency—and benefitting what they see as, like, the natural order of whiteness and the average American, and things that some people in the tech right kind of care about but prioritize less than their own companies and less than their own industry.

Rosin: It’s really complicated because they both have ideas like, There’s an optimum society; there’s a right way that things should be. And then they’re slightly different. So what is each side’s ideal “America made great again” look like?

Breland: Yeah, I think it on the sort of nativist right, the ideal America is this place that prioritizes—with some exceptions, more so now—but fundamentally, it’s this white, sort of very classic, conventional, conservative vision for what the United States is. It’s this, like, return fantasy to a version of the 1950s America that prioritizes white American interests above other people—again, with exceptions. There’s—you know, these people would all say that they’re not racist, that they’re just meritocratic, or things like that.

The tech right is more agnostic to those kinds of things. People like Marc Andreessen and Peter Thiel kind of, to some degree, see value in that. But they only see value as far as that doesn’t get in the way of their vision for creating this sort of all-star team of Americans that can sort of dominate the global stage in technology and dominate economically.

And so they’re willing to go to look to other countries to bring people in; to try to, like, get the best talent, according to them; to try to solve the toughest engineering problems; and to do things like beat China, which is something that they’re all very obsessed with.

Rosin: So they’re less concerned about where people come from. I mean, what makes it especially complicated and charged that this came up so soon is that it came up in immigration. Trump has made controlling immigration one of his top priorities. How did Trump himself end up weighing in on this?

Breland: After a few days of silence—perhaps because this was happening literally over Christmas and the days after—Trump did say that he does support H-1B visas. And he seemed to kind of take Elon’s side on this.

I wasn’t super surprised, because on an episode of the All-In Podcast—which is a sort of who’s who of the tech right; it includes David Sacks—Trump was pressed on the H-1B visa issue, and he did say, Yeah, I support it; I’m down for this. This was in the summer. And so it was consistent for him to come back up with this. And the other thing it’s sort of consistent with, in a sort of more general, patterny kind of way, is that in the past, when there is sort of tension between his sort of more nationalist, nativist base versus the wealthier interests that are in his coalition—not always, but—he often tends to go with the sort of interests of the wealthy, the people who have given him the most amount of money, people who he probably respects because he has a great deal of respect for people who have built wealth.

And so it wasn’t super surprising to see him break that way, especially because it seems like his larger immigration priority is not regarding H-1Bs, and he seems more flexible on that. His larger immigration priority is people who, as he would say, came here illegally and are not quote-unquote “high-skilled workers.”

And so on the sort of issue of mass deportation, this doesn’t signal that he’s, like, going to break from that at all. He’s talked a lot, very aggressively, about conducting mass deportations and quote-unquote “securing the southern border.” And they talk about the southern border, specifically, because they’re talking about a different kind of immigrant, and they have a different set of priorities when it comes to people coming across the southern border.

Rosin: Interesting. So then, maybe, the thing to explore is the nativist right, not just Laura Loomer. Laura Loomer is, you know, a little more on the fringes. But what about someone like Stephen Miller, who will be Trump’s deputy chief of staff for policy and who is credited with shaping a lot of the more draconian immigration policies in the last administration. He has solid power in this administration. Have we heard from him or someone closer to power about what they think about H-1B visas?

Breland: Miller hasn’t weighed in directly on this specific moment and this specific issue. He sort of gave a cryptic tweet that signaled that he is still anti-H-1B.

But he’s been very consistent on this in the past, and there’s no reason to believe that he would change, as someone who is, like, motivated primarily by this sort of nativist perspective that is, again, sort of galvanized by racial animus and, in many cases, just outright racism. I don’t think he’ll change his perspective, and he’s going to fight on this, and so there’s going to be weird tension moving forward.

Elon seemed to—I don’t want to say he walked back from this position, but, like, after a few days of fighting, he did seem to try to want to soften the blows and sort of extend an olive branch. People in sort of fairly influential but niche figures in this sort of nationalist, reactionary wing of the party also tried to sort of smooth over the tension and make it seem like there was common cause being found. And so they have an interest among themselves in trying to come together and paint themselves as a united front and sort of reach a consensus on this.

Rosin: Yeah, I mean, it’s still early. He hasn’t even taken office yet. But could you imagine a universe where, then, it just moves forward, and we quietly make an exception for elite workers and do mass deportations for everyone else? Like, is that where immigration policy could land?

Breland: Yeah, exactly. I mean, I think that—from my perspective and the things I pay attention to—that seems exactly the direction it’s going to go in.

The tech right is aware of the mass deportations [but] has not really talked out against them. Elon Musk has tweeted acknowledging them and sees them as an inevitability that he doesn’t seem to have a clear problem with. That could change when we sort of get, like, harrowing images of ICE conducting raids and things like that, but right now, that’s the track that we’re on.

Rosin: So if what you said is true, and if the past history holds, he is going to make an exception for elite immigrant workers. What does that imply about how he might handle other economic issues?

Breland: Yeah, if we extrapolate this out, which we can—both from this example but then, also, from how 2016 through 2020 went—Trump is probably going to side, I guess, with more of the wealthier faction, which includes the tech right, which includes people in his coalition, who are people like the hedge-fund manager Scott Bessent, who also sort of have this prioritization of more, like, economically laissez-faire issues. They have this sort of more traditional, conservative perspective on economics. And that’s something that’s going to run into tension with what the nationalists want. They want this sort of economic nationalist perspective that is a departure from this hyper-free-market sort of way of viewing the world that’s been the dominant conservative perspective for the past several decades.

Rosin: So essentially, this rift that you pointed out in the MAGA world—between, you know, Is he going to take the side of the elites, or is he going to take the side of all the workers? even if that means the nativist right—that’s a rift you can track kind of up and down various issues for the next many years, just to see, Okay, whose side does he take on a lot of these issues?

Breland: Exactly. Yeah. AI and automation is going to be a really big one in this area, too, because the tech right obviously cares a lot about AI and automation. They’re very pro-AI and automation. They see this as, like, an existential issue in the United States versus China, and that the U.S. must—to continue its being, like, the most important country in the world—that must beat China on this.

But a lot of the sort of more nationalist right doesn’t agree with this. They see this as a different kind of issue. Tucker Carlson, who I think kind of squarely falls in this nativist camp and is one of its most influential members, has outright said that he opposes—not necessarily the development of AI and automation but—its implementation and use.

He’s talked directly about never using AI for, like, things like driverless trucks. But Elon at Tesla is directly making self-driving trucks. And so yeah, there’s a lot of weird places where these sort of fractures are going to play out.

Rosin: And Tucker Carlson takes that issue because it’s a betrayal of the American worker.

Breland: Precisely.

Rosin: Interesting. So this is, actually, the central fissure of the Trump administration, basically?

Breland: Yeah. Yeah, it seems like that. I do want to say that this is kind of a unique issue, in that it draws in race, which is a very big thing, and it draws in immigration. And so it might get a uniquely high amount of attention. But there’s still going to be versions of this fight that might not play out as aggressively that are going to happen over the next four years.

Rosin: Well, Ali, thank you for pointing out this line to us. We’ll be watching it for the next four years, and thank you for joining me.

Breland: Yeah, thank you so much for having me. I appreciate it.

Rosin: After the break, we explore what’s behind the politics. Trump and his allies made the argument often in the campaign that immigrants take away jobs from Americans. It’s an argument that, on the surface, has some intuitive logic. But it actually doesn’t work like that. More soon.

[Break]

Rosin: Joining me is Atlantic staff writer Rogé Karma, who mainly covers economics. Rogé, welcome to the show.

Rogé Karma: It’s great to be here. Thanks for having me.

Rosin: Sure. So an early rift broke out in the Trump administration over H-1B visas, which we’ve been discussing on this show, with the nativist right saying what people say about all kinds of immigration: These immigrants take jobs away from American workers. So what do we know about the relationship between H-1B visa holders and the American worker?

Karma: Well, luckily, the H-1B program allocates workers randomly to companies based on a lottery. And that allows researchers to study what actually happens to the companies that did get workers, as opposed to the companies that didn’t.

And I agree with you. I think there’s a real sort of “man on the street” argument. There’s a sort of view that there’s a fixed pool of jobs, and so any immigrant that we bring in is going to take away a job that would otherwise go to an American. But when researchers have looked at this, the overwhelming majority of the studies have actually found no negative impact on either employment or wages, which I think at first sounds a little bit counterintuitive.

But the reason is a few fold. One: Companies who get H-1B workers actually end up growing and scaling up faster than the companies who don’t. And then because of that, they have to then hire a bunch of more native-born workers around that immigrant. The second reason is innovation.

One of my favorite statistics comes from Jeremy Neufeld, who’s a fellow at the Institute for Progress. And he pointed out that 30 percent of U.S. patents, almost 40 percent of U.S. Nobel Prizes in science, and more than 50 percent of billion-dollar U.S. startups belong to immigrants. Now, not all of those are H-1B holders, but there’s a lot of evidence that the companies who are awarded H-1B visas—they produce more patents, more new products, get more VC funding, and all of that actually creates jobs. So on the whole, I actually don’t think there’s a lot of evidence for this broader nativist claim about this program.

Rosin: Let’s make this a little more concrete. So let’s just play out a theoretical company. Here’s a theoretical company, hires H-1B visa holders. How does it work? Like, innovation is a vague word. How does it actually play out?

Karma: I think what’s important to remember here is that getting one of these H-1B visas is actually pretty difficult. And so the idea that a company is going to be able to systematically bring in foreign workers to replace their native ones using this program—it’s just really hard to do because there’s such a low chance they’re even going to get those workers in the first place. And so a lot of times when companies use this program, what they’re doing is they’re looking for a very important skill set.

So let’s use semiconductors as an example. This is an industry, when it comes to the manufacturing of semiconductors, that U.S. companies haven’t really done for a while. A lot of the most advanced chips are made in places like Taiwan, and so a lot of the best talent is abroad. And so if you’re a U.S. semiconductor manufacturer, the industry in the U.S. estimates that even if we had the best job-training programs possible, that would only fill about 50 percent of the high-skilled demand for the labor force in this field.

And so you need to bring in folks who have this highly specialized knowledge, probably because they’ve worked in other countries. But then, what that allows you to do, once you have a subset of foreign-born workers who can do this sort of specialized manufacturing—what you then have is people to come in and support around them. And then because a company has that need met, they’re able to then hire a bunch of other workers to fill other needs that they have but that don’t require that same kind of specialized knowledge.

And on the other flip side is that we actually have some studies that look at: What happens to the companies that don’t get H-1B visas? What happens to those companies? Do they hire more native workers? Do they invest in more job training? And it turns out that they don’t. In fact, they end up often just either (A) producing less or growing less quickly, or (B)—and this is a finding of a lot of the recent literature—they end up outsourcing the jobs instead. And so instead of bringing in this new worker and then hiring more native workers around them, they just say, Well, look, we have an office in China, or we have an office in Singapore, or we have an office in Hong Kong or India. Let’s just hire more there because we’re not going to be able to get the talent that we need here.

There are a handful of outlier studies, but I think, right now, the broad consensus in the field is that the H-1B program, even for all its flaws, doesn’t seem to have these negative employment or wage effects.

Rosin: So that’s what the research shows. It’s fairly definitive until now, and yet even some Democrats have repeated the line, The H-1B visas take away American jobs—for example, Bernie Sanders. What do you make of that?

Karma: Well, I think where Bernie’s coming from—and I think where a lot of Democrats are coming from and, quite frankly, some Republicans—is that there are two things that are true here at once. The first thing that’s true is that we don’t find these huge negative effects from the H-1B program. And the second thing that’s also true is that, despite that, the H-1B program has a lot of flaws, a lot of loopholes that companies have learned how to game.

So one of these is that a significant portion of H-1B visas are used by so-called outsourcing firms, which are these companies that basically bring in foreign workers. They train them here, and then, when their H-1B visa expires, they employ them in their home countries for a fraction of the cost. And so they’re functionally using the H-1B visa to train workers here and then employ them at lower labor costs elsewhere.

That’s just bad, on the face of it. The fact that we still don’t see negative effects, overall, is really telling, but we should fix that loophole by, among other things, raising the minimum wage for H-1B visa holders, making the program merit-based instead of random—like, you can more closely regulate how companies use those workers.

So I think part of what Bernie Sanders is getting at, part of what some of these critiques are getting at, is that this program does have a lot of flaws that allow corporations to game it. And it’s actually kind of shocking that, despite all these flaws, it still hasn’t produced these horribly negative results.

But imagine how much better it could be if we fix them. So I really think that this might be a place where you see the sort of messy realities of immigration politics running up against what, really, people all across the political spectrum agree is a pretty common-sense set of reforms. But that doesn’t always mean it makes good politics.

Rosin: Right. Right. Okay. So we’ve been talking exclusively about the H-1B visas because they came up in the news, but the whole of Trump’s promise is not specifically about H-1B visas at all; it’s a promise of mass deportation and immigrant labor, in general. I know that you’ve been looking into the research about the relationship between immigrant labor and the American worker. What did you find?

Karma: Well, I went into this because I kept hearing Donald Trump, J. D. Vance, Stephen Miller make these kind of claims that sound kind of intuitive—that when immigrants come in, they take jobs from natives, right? There’s a sort of Econ 101 logic, which says that when the supply of any good goes up, including labor, the price of that good, like wages, goes down.

And so I kept hearing these arguments and thinking, Well, maybe there’s something to this, and so let’s actually look at what is happening. And it turns out that the sort of Trump-Vance view was pretty much the conventional wisdom for most of the 20th century, both among policymakers and economists, until a study came along that sort of shattered the consensus.

And so to tell you about the study, I’m gonna go back a little bit. So in 1980, Fidel Castro, the president of Cuba, opened up emigration from his country. He lifted the ban on emigration. And what that allowed is for 125,000 Cubans to leave from Mariel Harbor to Miami, Florida, an event that ended up becoming known as the Mariel Boatlift. And in just a few short months, Miami’s workforce expands by about 25 times as much as the U.S. workforce expands every year because of immigration. And this created the perfect conditions for what economists call a “natural experiment.” It was like this big, massive shock that only happened to Miami.

And so what the economist David Card later realized is that you could compare what happened to workers in Miami to workers in other cities that had not experienced the boatlift, track how wages did in both, and then see what actually happened. And his view was, Look—if there is a negative effect of immigration on wages, Miami in the 1980s is exactly where it should show up. It’s this big, unprecedented shock. That makes what he ended up finding so shocking, because he ends up finding that this huge influx of immigrants has virtually no effect on both employment or wages of native-born workers in Miami, including those without a college degree.

Rosin: And why? I mean, it seems counterintuitive.

Karma: It seems completely counterintuitive. There are a few reasons, but I think the big one—and the big thing that the common-sense view of immigration misses—is that immigrants aren’t just workers. They’re also consumers. You know, they’re people who buy things, like healthcare and housing and groceries. And so at the same time that they’re, you know, competing with Americans for jobs, they’re also buying lots of things that then increase the need for more jobs.

And I think this sounds counterintuitive, but we think about it in other contexts all the time, right? When’s the last time you heard a Republican politician railing against the upcoming group of high-school graduates because they were about to come in and compete with, you know, people currently in the workforce?

You probably haven’t, because we understand that population growth has these two sides to it: that people are consumers who create demand for jobs and workers who take jobs. And so I think that’s the gist of the problem with the conventional view.

Rosin: So that was a singular study. Has that held up over time?

Karma: It has. And so after that study, it got a lot of researchers interested, and this has now been studied in countries all over the world, from Israel to Denmark to Portugal to France, and almost all of the high-quality studies come back with very similar results.

I think the one complication in all of this—the one challenge—has been, Well, what about the least-skilled workers? What about: Okay, maybe on average, immigrants don’t hurt the employment prospects or the wages of native-born workers, but what about the least-skilled workers? What about high-school dropouts, folks without a high-school diploma? And a lot of the more recent literature has shown that even that group doesn’t suffer when immigrants come in.

And so I think the broad consensus in the literature now is that immigration does have costs. It can exacerbate inequality. Tellingly, the wages of other immigrants often get hurt by new immigration. You could see some negative effects in certain sectors, even if it’s balanced out by other sectors, but on the whole, it appears to be really beneficial for basically all classes of native workers.

Rosin: So at this point, there’s a large body of research saying the arrival of immigrants—even sudden arrival of immigrants—doesn’t have a great effect on the American worker, may even have a positive effect. Now, what about the disappearance of immigrant labor? Because Trump’s promise is mass deportations. I’m not sure if you can just flip, you know, the findings of this research. Like, is there a similar natural experiment or study that shows how that might affect workers or the economy?

Karma: There is, actually. And I think the claim from Trump and his advisers is that the ultimate pro-worker policy is mass deportation, right? Because what happens when you get rid of a bunch of immigrant laborers is now those employers have to hire natives at higher wages, because there’s a sort of artificially created labor shortage.

Rosin: Right.

Karma: And again, very intuitive. But when we actually look at what happens in the real world, we see something very different. So the best study on this, I think—although there’s a few—is from the Secure Communities program, which is a Department of Homeland Security program that between 2008 and 2014 deported about 500,000 immigrants. And because the program was rolled out community by community, it created this really nice natural experiment where you could see what happened to the communities that had experienced it and the ones [that] hadn’t.

You could compare them and see what the overall effect [was]. And what researchers found, actually, shocked me—it shocked many of them—was that for every hundred immigrants that were deported, you actually ended up with nine fewer jobs for natives. That’s not just temporary work. That’s, like, nine jobs permanently gone in this community.

And there are many studies that reinforce this finding from all across history, from the Bracero program, studies on the H-2B program—which is like H-1B, but for lower-skilled immigrants—studies going all the way back to the Great Depression that all find similar things.

And the reason is that immigrants are deeply interwoven into their local economies. And so take the restaurant industry. If you’re a restaurant owner, and suddenly you lose a big chunk of your workforce, to the point where you either have to have higher labor costs and at the same time you have less demand, there’s a good chance you have to go out of business altogether. And when you go out of business, that doesn’t just hurt the immigrants who are working for you. That also hurts the native-born workers.

And so there are all these sort of synchronicities, all of these interconnections, that allow immigration to have this positive sum effect. But then as soon as you—if you rip out the immigrants, then native workers often get caught in the crossfire.

Rosin: Yeah. So if the research is so consistent—so strong—and makes a lot of sense, if you think about it a tiny bit more deeply, why do you think this sentiment persists? Is it just a feeling, you know? Because it persists on both the right and the left. It’s not as if the left is fighting back. They don’t necessarily advocate mass deportations, but they are also not fighting back against this idea that immigrants take away American jobs.

Karma: I think part of the fixation on the economics of immigration is a way for many people like us—elites, people in the media—to try to find a more materialist explanation for a set of instincts that I think many of us are uncomfortable with. And I think that is actually kind of a tragedy.

I think if people oppose immigration or feel strongly about immigration because of certain cultural beliefs or concerns about national identity, it’s important to take those concerns seriously. And I think it’s actually a problem, and even a bit patronizing, that we tend to project these sort of more wonky economic concerns onto that.

Rosin: Yeah. I had a conversation with Representative Ritchie Torres of New York right after the election, who talked about how a lot of the immigrants in his neighborhood had a surprising amount of anti-undocumented immigrant sentiment.

And it made me wonder about—I don’t even know how to define this, but sense of chaos, just a feeling of things not being in control. It’s sort of the way people feel about crime. There just seems to be a sense that things have run away, and you can’t get ahead. It’s a vague thing, but it is related to—There’s just so much out of control, and I need someone to stop it.

Karma: I actually think that’s a really important point. One of the greatest shifts in public opinion on immigration has happened in the last few years, where in 2020, according to Gallup, only 28 percent of Americans said they wanted immigration decreased.

Four years later, that number was 55 percent. So it had almost doubled. And that is much larger and much faster than even the public-opinion shift on something like gay marriage. So this is a huge, almost unprecedented shift. And as I dug into why, what came up over and over again is this feeling of chaos, this feeling that we are not in control of our own border. And when you actually look at questions about how people feel towards immigrants themselves, they hadn’t changed nearly as much.

People weren’t necessarily anti-immigrant, as much as they felt like the immigration process had gotten out of control and the immigration process was no longer serving the country. And so I think it is really important to distinguish [between] those two things. And I think a lot of the public-opinion shift we’ve seen over the last few years—it isn’t about economics. It’s really about this sense of control and chaos.

Rosin: Yeah. So maybe the place to end is this: Have you talked to anyone or done any thinking about how, in a situation like this, you close the gap? Because we, as journalists—it’s frustrating to us to know that there is an answer. You know, there’s an answer that research has provided. There are truths and facts. And separate from that, there is a perception. So have you thought of or seen anybody talk interestingly about how you bridge a gap like that, where people feel one way that is discordant with what the reality is?

Karma: Unfortunately, like any good journalist, I’m not quite as good at the solutions as I am about identifying the problems. But I will say, I think at the root of a lot of this is the fact that there’s an underlying scarcity. Right?

So I think an example of this is housing. Recently—you know, we haven’t talked about this, in particular—but J. D. Vance and Donald Trump made a big deal in their campaign about how immigrants were responsible for driving up housing costs. That argument has never held weight in American politics before, because it is only over the last decade that housing costs and a housing shortage has become a big problem. When there is material scarcity, people look for a villain; people look for someone to blame. And so I think one answer to, for example, the blaming [of] immigrants for housing costs is to say, Well, if we fix the housing shortage such that people don’t feel that scarcity, maybe we can avoid some of that.

I think the other sort of way I’d look at this is: In some senses, one of the most pro-immigrant things you could do is reduce the amount of chaos, right? So I think there’s actually a sort of middle ground here where you could reduce a lot of the chaos at the border while expanding legal immigration in a way that keeps immigrants coming in but creates a more orderly process that people feel comfortable with. And you can actually get more positive sentiment as a result.

I just think what makes it difficult is the politics are almost perfectly aligned to make that difficult from happening. And it’s been, you know—immigration reform is something that politicians have been talking about for more than 20 years now, and it hasn’t happened.

Rosin: Well, that was really helpful. Rogé, thank you so much for joining me today and talking about this.

Karma: Thank you so much for having me. It was a pleasure.

Rosin: This episode was produced by Kevin Townsend and edited by Claudine Ebeid. Rob Smierciak engineered, and Sara Krolewski fact-checked. Claudine Ebeid is the executive producer of Atlantic audio, and Andrea Valdez is our managing editor.

My thanks to Ali Breland and Rogé Karma for joining me. If you’d like to hear Rogé go even deeper on the research into immigration’s economic impact, you can hear him on another Atlantic podcast called Good on Paper. It’s hosted by staff writer Jerusalem Demsas, and that episode is linked in the show notes.

I’m Hanna Rosin. Thank you for listening.