Freakonomics Radio - EXTRA: Roland Fryer Refuses to Lie to Black America (Update)

Episode Date: September 30, 2024

His research on police brutality and school incentives won him acclaim, but also enemies. He was suspended for two years by Harvard, during which time he took a hard look at corporate diversity programs. As a follow-up to our recent series on the Rooney Rule, we revisit our 2022 conversation with the controversial economist. SOURCE:Roland Fryer, professor of economics at Harvard University. RESOURCES:"How to Make Up the Covid Learning Loss," by Roland Fryer (Wall Street Journal, 2022)."Roland Fryer on Better Alternatives to Defunding the Police," by Roland Fryer (The Economist, 2020)."Harvard Suspends Roland Fryer, Star Economist, After Sexual Harassment Claims," by Ben Casselman and Jim Tankersley (The New York Times, 2019)."Why Diversity Programs Fail: And What Works Better," by Frank Dobbin and Alexandra Kalev (Harvard Business Review, 2016)."An Empirical Analysis of Racial Differences in Police Use of Force," by Roland G. Fryer, Jr (NBER Working Paper, 2016)."Getting Beneath the Veil of Effective Schools: Evidence from New York City," by Will Dobbie and Roland G. Fryer (American Economics Journal, 2013)."Financial Incentives and Student Achievement: Evidence From Randomized Trials," by Roland G. Fryer (The Quarterly Journal of Economics, 2011)."Toward a Unified Theory of Black America," by Stephen J. Dubner (The New York Times, 2005).Equal Opportunity Ventures.Intus Care.Reconstruction.Sigma Squared. EXTRAS:"Did the N.F.L. Solve Diversity Hiring?" series by Freakonomics Radio (2024)."The True Story of the Gender Pay Gap," by Freakonomics Radio (2016)."Does “Early Education” Come Way Too Late?" by Freakonomics Radio (2015).

Hey there, it's Stephen Dubner, and today we've got a bonus episode for you. It is an update of a 2022 interview we did with Roland Fryer, a much acclaimed and frequently controversial economist at Harvard. When we spoke, Fryer had recently returned from a two-year suspension, which you will hear about in the episode. The person who suspended him was Claudine Gay, who at the time was the dean of Harvard's Faculty of Arts and Sciences. Gay went on to become president of Harvard, but then she famously resigned amidst plagiarism charges and criticism of Harvard's response to anti-Semitic demonstrations. But the reason we thought you might like to hear this episode now is because it follows naturally from the two-part series we just published on the Rooney

Rule. That is the National Football League policy that was designed to increase diversity among coaches. And the Rooney Rule has since been adopted by many firms and institutions outside of sports. Roland Fryer, who is Black, has his own thoughts about how firms and institutions have handled diversity hiring. And you'll hear about that too. We have updated facts and figures as necessary. As always, thanks for listening. In 2005, I wrote a piece for the New York Times Magazine called Toward a Unified Theory of Black America. It was a profile of a young Harvard economist named Roland Fryer, whose journey to Harvard was beyond surprising, beyond unpredictable. Given his background, it may have seemed impossible. And yet, there he was. A lot of things happened to get Fryer into the upper echelons of academia,

and even more has happened since, much of it controversial. How does Fryer describe his research agenda today? Trying to make Black America happier, wealthier, healthier, more educated. That's all I've ever tried to do. And I refuse to lie to them. So, Roland, it feels like most public discussions about race these days,

at least the ones that I read in academia, in journalism and elsewhere, do treat Blackness as essentially a handicap. What are the costs to that perception? I mean, how much time you got? We've got plenty of time. Today on Freakonomics Radio, a conversation with Roland Fryer about his research on policing. I had a five-hour meeting with Obama and other folks, and we got zero done. On education.

The thing that drives me nuts is that this woman is doing everything that she thinks is right. We'll get his take on corporate diversity programs. It made me sick to my stomach, man. And we'll hear about Fryer's personal controversy, including a two-year suspension by Harvard. I broke a lot of glass early on in my career, and I don't think that was helpful. To be fair, Roland Fryer is still breaking glass.

All that on Freakonomics Radio right now. This is Freakonomics Radio, the podcast that explores the hidden side of everything. With your host, Stephen Dubner. In 2007, at age 30, Roland Fryer became the youngest African-American to receive tenure at Harvard. He would go on to win a MacArthur Fellowship, the so-called Genius Grant, as well as the John Bates Clark Medal, one of the top prizes in academic economics. He got his own research lab at Harvard to study the achievement gap between black and white kids. He even made it onto late night TV. Please welcome Roland Fryer. You have some controversial areas you study here.

You say that blacks are the worst performing ethnic group in our school system. Excuse me, but that is a pretty racist thing for you to say. You're not the first person to call me a racist. I'm not? No. I was hoping I would be the first. It's not racism. It's reality. All right. A lot of Fryer's research pushed boundaries and crossed ideological lines.

My life's work is about making those communities better. And so whatever cost there is, frankly, to me of telling what I think is the data-driven truth about these issues, whether it's health or police or education, I'm going to do it. In 2019, Fryer was suspended by Harvard over allegations that he had engaged in unwelcome conduct of a sexual nature and charges that he had violated some of Harvard's finance rules. In a letter he sent to his dean, Fryer wrote, I apologize for the insensitive and inappropriate comments that led to my suspension. I didn't appreciate the inherent power dynamics in my interactions, which led me to act in ways that I now realize were deeply inappropriate for someone in my position. In 2021, Fryer returned to teaching and research. Today, he is permitted to advise students again, but his research lab remains shut down.

We'll hear more about his suspension later in today's conversation. But let's start with Fryer's origin story. When I wrote that Times Magazine piece years ago, he and I spent time together in New York and Boston, and we visited his grandmother and father in Central Florida. We went to the small city outside Dallas, where Fryer spent his unproductive teens, and we went to Oklahoma to visit his mother, from whom he had long been estranged. When we spoke recently, I asked Fryer to summarize his unlikely path to becoming an Ivy League economics professor.

I was born in Daytona Beach, Florida. Oddly enough, and this will tell a lot of the story, brought home from the hospital with my grandmother and lived the first few years of life in Florida. My mother kind of disappeared out of my life very, very early. My father was still there. He was kind of a copy salesman. And my uncles were there. And I grew up in this really ironic, strange, I don't know quite what to do about it, environment in which my grandmother

was a teacher. And my great aunt, my grandmother's mother's sister, was also a teacher. And the other sister ran one of the largest distributors of crack cocaine in Central Florida. So high achievers in different realms, we'll call it. Yeah. She was the CEO of a street pharmaceutical company. And yet, you know, we would chat with each other and there was no judgment and love of each other. And so I grew up in this strange world where my grandmother viewed it as hard work and get ahead, though she thought discrimination was omnipresent in the world. And my great aunt, who was, for lack of better words, an entrepreneur, who did lots of illegal stuff to get ahead. And I spent, I'd say, four months out of the year, even when my father and

I moved to Texas. Early on, my father and I had a reasonable relationship. It deteriorated over the years. And by the time I was a teenager, I was just an angry man. I was really angry at the world. Pretty good at sports, but just an angry, man. I was really angry at the world. Pretty good at sports, but just an angry kid. And I wasn't trying hard in school at all. They used to pass out books in school, and I'd say, you just keep them. I'll lose them. Never did a lick of homework.

Managed to eke out of high school with a GPA of, I don't know, two point something, but had really high test scores, oddly. And, you know, got involved in a bunch of little petty crimes when I was 15, like was driving a car without a license, stealing stuff out of stores, forged my birth certificate so I could work at McDonald's. My father eventually lost his house and he ended up going to prison and all that kind of stuff. I didn't know my mother and I just felt really, really angry and alone in the world. I made my way to a college, not a great one, but a good enough one. And it's there that I took a principles of microeconomics course. It was 8 a.m. He had office hours at 7 a.m. I know now that was a joke, but back then I thought it was pretty convenient because I'm an early morning guy. And I was there before every class at 7 a.m. And we started arguing about welfare and economic policy and how to use food stamps, what the restrictions should be, and really fell in love with it. But let me just say, I have been on an absolute quest for

the last 25 years to catch up because I spent the first 20 goofing off and being angry at the world. I was just meeting with a guy who's a really accomplished businessman, and he came from the golf course, and he says, well, why do you work so hard? What are you doing? It's time to enjoy life. And I said to him, I gave you a 20-year head start, man, and a better family and all that stuff. So every time you play golf, I catch up a little bit. Every time you take the night off, I catch up, right? And that's been my attitude, and you know that for years. I remember when I was spending time with you, you were a relatively young professor at Harvard and there was that car in the parking lot. This

car was outside early every morning, late at night. And you were like, damn, somebody is out working me. And you were pissed off. And then you later found out they were on vacation, just parked there. It was like a silver one, right? I remember that. And I was worried about that, but that's my attitude. I'm in a big hurry to catch up. And my upbringing, it really has formed my view of how to do this. Number one, data first, obviously, but this is why I don't have any politics in this stuff because I have seen that, yes, there are things that need to be changed in Black communities, but I also see the effects of discrimination, whether perceived or real, on these communities. The only thing I care about is making them better. That's it. I really don't care otherwise. Fryer is probably best known for a 2016 research paper called An Empirical Analysis of Racial Differences in Police Use of Force. It incorporated a variety of data sets, including a federal survey on interactions with police and the data on police shootings from 10 police departments around the country,

including Houston, Jacksonville, and Los Angeles County. What did he find? On average, in any given stop, Black people are 50% more likely to have force used on them than white people. Okay, that's on average not controlling for anything. That's exactly it. That's just in the raw data. Now, if we control for lots of other things, where they are in terms of the city, I mean, we had millions of data points, so we could

really be very strict on the controls. If we do that, then the difference decreases substantially. But this number I find the most compelling in this entire research is that we looked at the cases in which the police officers themselves said the civilian was perfectly compliant, didn't have contraband, was not arrested. Even in those instances, Blacks were roughly 20% more likely to have force used on them than whites. So the conclusion that one would almost be forced to draw from that is that police are, on average, racist against Blacks. No, I'm not going to say racist, but there's discrimination going on.

Okay, noted. So that's the part of your research about what's called the non-lethal use of force, and then there's lethal use of force, which essentially means a police shooting, correct? Yes, yes. Whether it's fatal or not. Exactly. So what'd you find there? What we found there was no racial differences whatsoever in lethal uses of force. Roland,

that can't be right. Roland, Roland, my friend, that cannot be right. I read the newspapers, Roland. Yeah, I know. Well, it surprised me as well. We had, I don't know, 10, 15 cities by the time we finished that research. In no city was it true. Because the thing is, if you read the Washington Post or the Guardian, they'll say things like the fraction of black people who were unarmed and were shot at by police is higher than the fraction of white people who were unarmed and shot at by the police. But that's just not, that's not the right way to do those statistics. Because why? Because they're not accounting, that's comparing apples with cars. And I'd like to compare apples with apples. I don't understand. Why is that not a relevant variable? It's not that it's not a relevant variable, it's incomplete. There are a lot more things about a police interaction than whether or not the person

eventually has a weapon. Before you got into this big data analysis, as I understand it, you also, we all saw what was going on in these videos. And the Walter Scott video is the one that got me off the couch, so to speak. I just couldn't take it. I was furious. He was a guy that was running away after a traffic stop. Is that right? Yeah. Running is generous. It was shuffling across an abandoned field. And somehow, because I think it was in South Carolina, the picture of it reminded me of Daytona Beach. And there was something about that that said to me, there but for the grace of God, go I. And it just woke me up. And I was upset. And I went to my

colleagues in the economics department, and I was all fired up about this in the hallways. And they weren't as fired up as I was, but I was pretty fired up about it. And one of them, Andre Schleifer, who is a dear friend of mine, he said to me, I don't know, Roel, do you even know what police do? And it was like a gut punch, man. I didn't know, right? The truth is I was biased. I don't like police.

I don't like them now, right? Like I was driving down the highway yesterday. Police put his lights on. I started remembering stuff I did in seventh grade. I mean, it was scary. Luckily, it wasn't for me. But anyway, and so I decided maybe I should go embed myself in police departments. And so I did just that.

I went to Camden and did a couple double shifts in Camden, riding around. Went to Houston and did that and even did some simulation and de-escalation training with another police department. The truth is, I didn't like who I became riding around in a police car after three to four hours. If you ride around looking for bad guys, lo and behold, you see bad guys, right? I was the worst police officer you can imagine. They kept saying, Roland, it's not illegal to dribble a basketball. I was like, I'm not sure. And what was interesting though, in all seriousness, was in Camden, I met police officers who walked the beat. What happens there is that when you see someone who, you know, might look dangerous or at least uncertain or random to me, because they know

the person, they're just like, he's like that on Thursdays, right? It was really interesting for me to see them say that because most police officers see you at your worst. But if you're hanging out in the communities, it gives you a denominator for which to understand the other behavior. So were these ride-alongs before you actually started analyzing the police data? Didn't have any data yet. Part of the ride-alongs were to try to understand what data existed, to really understand from the police the types of data they collected, the types of data they wanted to collect, and also to get their sense of what was going on in these interactions. What were we missing in the videos? You know, we'd only seen 12. We had all made these huge conclusions because we had seen 12 horrific videos. But police stops happen thousands of times a day.

Look, 80% of the police shootings in our data came from a 911 call, not someone pulling someone over and it escalating, which is how we typically see it on TV, but a 911 call where the police show up, the person has a weapon, there are multiple witnesses, and a shooting happens. And if that's 80% of the data,

it's not that surprising that there are no racial differences, right? Whenever we talked about lethal use of force, they would become very earnest and say things like, discharging your weapon is a life-changing event. I heard that in city after city. Discharging your weapon, sir, is a life-changing event. Not one police officer told me roughing up a black kid in an alley is a life-changing event. So these are categorically different in their frame. Categorically different. And the incentives or disincentives, as it were, are not the same. Because once you discharge your weapon, then what happens?

There's a real investigation that happens, independent of if many people saw it and they think it was fully justified. But we don't put the same scrutiny on how we treat young Black men civilians, right? So how did these ride-alongs change the shape of your understanding of this job? It gave me a better sense of how complicated the job is, man. It's really complicated, okay? And you realize that the job is really difficult. Okay, and let's go back then to your findings on lethal use of force. On lethal uses of force,

we found no racial differences in those. And it caused, you know, some alarm among people. What do you mean by alarm? Was there alarm even before you published the research? Oh, man, I mean, I had colleagues pull me to the side and say, you crazy. Don't publish this. You're going to ruin your career. Because why? I don't know. They didn't give a full example. Ruin your career because here you are a black economist who's saying what exactly?

You know, that's the difference between you and I, Steve. When someone said, man, that's going to ruin your career. I don't go, exactly how, bud? But they came to me and said, look, after a seminar, here's what you do. You take the lower level uses of force, publish that. Don't publish the other. And I said to this person, if the results were that there were racial differences in lethal use of force that looked like discrimination, do you think I should publish them then? And they said, yeah, because then it would fit with the first part. And I said, well, then you just ensure that I'm going to publish it all because I'm not going to hide a result because you don't like it. I have heard you refer to other researchers who analyze police bias and police behavior as cowards. Is this what you're talking

about? That scholars are withholding either evidence or emphasis, at least, on the lack of racial bias in police shootings? Yes, that's exactly what I mean. Because you can look at the papers and people have similar findings, but it's an appendix table 157. And they bury it. And here's the difference, man. You're one of the rare people who have actually been to the communities where I grew up. And they haven't changed much since I was a kid.

My life's work is about making those communities better, and I refuse to lie to them, right? I just refuse, because the folks in those communities, they know when they're being lied to, and we think we're making all this progress because we now capitalize the letter B in black. No one in that neighborhood gives a crap about that. They don't. These are real issues, and I'm not going to bury the truth that can actually help folks just because people are going to be upset about it, right? The thing about lower-level uses of force is that actually, for me, provides some optimism because that's a

place that, with the police, we can dig in and try to actually make real progress together. If folks would just stay true to the data instead of trying to make it be what they want it to be, we'd all be in a better place. I've heard you use the word dignity before in discussing this or the absence of dignity. Can you talk about how that works? Really important. When I wrote this, someone I respect shot me a text and said, I don't see this as a big problem because this is about Black Lives Matter and not about being roughed up. And that really upset me because as a person who's been roughed up by police,

it is a very stressful, stressful interaction. It is not a good interaction to have. So I wrote back to him, Black Dignity Matters as well. If you talk to kids in the communities that I care about, when you ask them about their prospects and how fair the world is and how much effort matters, things like that, one of the things they will mention is police. How can it be that effort matters so much and there's this true meritocracy if I can't get a home safe for my own police? And so I think it erodes trust in the

American dream. It erodes trust in American institutions. And it's something that we could spend some good time really working on, right? Because there's a place where we're not hardly at all collecting data to hold police accountable. We don't have an incentive scheme. It feels like that is ripe for reform. And if it were me, that's where I would start. Seven days after that paper came out, I had a five-hour meeting with Obama and activists and other folks. Al Sharpton was there. And Al Sharpton and I probably don't agree on hardly anything, but there's one thing we agreed on.

He said, look, if we weren't being harassed daily, then we'd be willing to listen on some of these shootings that weren't clear. That's a profound point. If we could take away the discrimination that we know exists, then there'd be room for common ground on these other things. So, Roland, what happened next? Did the president or the Justice Department issue a new manual on best policing practices as determined by Roland Fryer, for instance?

Not even close. Not even close. But we did have some follow-up meetings with other senior White House officials, and the hope was to try to get the head of the FBI at that time, Comey, involved because they serve for much longer, typically, than administrations. And to start doing these things where we can potentially look at tying federal resources to police, collecting the right data, et cetera. And just none of it happened.

You know, I was failed. Because why? Because that's just how it works in government? Is that the easiest answer? I don't know. Maybe I suck, right? I don't know. I really don't know. But it was extraordinarily frustrating to me because this is something that matters so much, and it felt like there was a wedge to really make progress. After the break, Roland Fryer and the push for corporate diversity. I said, why aren't they doing what we know works?

I'm Stephen Dubner. This is Freakonomics Radio. We'll be right back. In 2019, the economist Roland Fryer started a firm called EO Ventures. The EO stands for Equal Opportunity. When he got a two-year suspension from Harvard and had time on his hands, he worked 100 hours a week to get EO Ventures off the ground. We really want to invest in companies that move the levers that we know are important for increasing economic mobility. Most companies in their portfolio were founded by women and people of color, people who traditionally don't have the best access to venture capital.

I mean, as you know, Stephen, I did fight the good fight. I wrote a bunch of papers for academic journals, like seven people read them. You're one of them. Thank you. And spent, you know spent pretty good time with folks in Washington and other state governments, but I just had no impact whatsoever. I didn't get anything done. At some point, I had to look myself in the mirror and go, would Milton Friedman go around to all these foundations and beg them to do the right thing? No. We would try to use the

market forces to increase opportunities. When I was a kid, people told me capitalism was the problem. What I'm trying to say here is it's going to be part of the answer. One of your portfolio companies I see is called Intus Care, which is described as a data-driven elder care company. Can you tell me about that firm and how that fits into this notion of investing in a business that increases opportunity? Yeah. This is an interesting one because two of the co-founders are two young Black men from Brown University. They're former athletes. They marched into my office, these in-shape young Black gentlemen with this passionate plea for elder care. And it was like, what the heck

is going on? But, you know, it's an interesting field because they are using data in really sophisticated and interesting ways to essentially, not to sound like buzzwords, but to risk group people. What they're saying is to actually increase the quality of care. Maybe I should check on Steven three times a day because he's in a higher risk group and other people one time a day. That would have been great when trying to care for my grandmother at the final stages of her life, because I never could tell from Boston whether or not she was getting the right care, whether or not someone was stopping by to check on her. And there are big, big differences by population in terms of how that care goes based on how much income you have. There's another company that I guess is a portfolio company in your venture capital firm, but you are also involved in this company. This is called Sigma Squared, which is described as science-driven diversity.

Can you just give me the top line description on that? Sigma Squared really is trying to help companies, universities, not-for-profits, increase diversity, but do it in a way that, frankly, makes sense, that is data first. That isn't just hand-waving, let's say. Oh, the hand-waving is, that's why I started it. Because after George Floyd, I saw what a lot of corporations did in terms of the, I would call it value signaling, and it made me sick to my stomach, man. On the other hand, I went to a friend of mine and I said, why aren't they doing

what we know works in this area? You know, their theorem's proven, there are simulations that have been run. Why aren't they using that? And they rolled their eyes at me and says, because most CEOs and people in HR are not reading papers in economics from the 1990s. And I said, oh. And so we wanted to make it easy for them. So we essentially created software that does the analytics for them. It seems as though just about every kind of institution these days, corporations and government departments and universities and so on, have embarked on diversity, equity and inclusion or DEI programs. And this was certainly boosted by the outrage around the murder of George Floyd in 2020. A McKinsey analysis found that Fortune 1000 companies committed to $66 billion in 2020 to spending on racial equity initiatives. How well do you think that money is being spent?

I don't know, but I would say the jury is still out. And that's being very gracious. You recently published a piece, Roland, in Fortune magazine. It was headlined, It's Time for Data-First Diversity, Equity, and Inclusion. Here's one sentence I found particularly interesting. The average impact, you write, of corporate DEI training is zero, and some evidence suggests that the impact can become negative if the training is mandated. So, uh-oh, that doesn't sound like a very good return on $66 billion or whatever these firms are spending. Walk me through that, and then I want to know when it's failing, why it's failing, and what you want to do differently.

Yeah, this is not my research, but there have been lots of others who worked on this. Professor at Princeton, Betsy Pollack, has a recent paper, and she reports that the impact of those trainings is zero. Frank Dobbin at Harvard in the sociology department has also written things that show that not only is the impact zero, but he has shown data from companies that when it was mandated, the actual share, the percentage of minority managers goes down. So I'm looking at something that I think is from the Dobbin research done with Alexandra Kalev in the Harvard Business Review. One of the reasons they write that it doesn't work when it's mandated, and I just found this surprising, but in retrospect, maybe not, was that when it's mandated, managers don't like it

because they, quote, resist strong-arming. Can you just talk about how it actually works, how it plays out? It varies a lot company by company. Some will put folks through mandatory trainings. Some people will just add it as a resource for those who want to use it. Others will do things like mask information on resumes of applicants because they think that is the right thing to do. All of these things, even when they have really, really great intentions, scare the heck out of me. Because why? Because they are the equivalent of giving antibiotics no matter what happens when someone

comes into the doctor's office, right? So you come in with a broken leg, antibiotics. You come in, you got an earache, antibiotics. And what happens inevitably is that, you know, let's suppose that antibiotics works in 10% of the cases, then those 10% go, I told you antibiotics work. Maybe I need a different dosage. I can't quite get this broken ankle to feel better. And so what we really need to do, in my opinion, and this is, I don't think this should be

controversial. I do this in every other research project I'm in and corporations do it in every other aspect of their business. It's to start with the data. Like, where do we actually have issues? And I mean, deeper than we don't have enough black people in the engineering department. We know you don't. Okay. We don't have to look people in the engineering department. We know you don't, okay?

We don't have to look. Like most companies, that's true. And so the question becomes, can I get a full picture of what's going on in my company? And what type of bias is producing those disparities? Social scientists tend to group disparities in different parts. Maybe it's good old-fashioned bigotry. But bucket number two could be information. Maybe you don't have perfect information when you hire or promote or assign work.

And in those cases, maybe you rely on your stereotypes accidentally or on purpose. The third one is what I loosely call structural bias. And that is you're doing something that on its surface seems absolutely fine, but unknowingly, it's got a disparate impact on one group or the other. I was talking to a company a couple months ago and they had some supply issues. They couldn't get enough people to apply to their internships. Okay. And I said, well, how do you find people for your internships? They said, oh, Roland, it's really random. I said, what do you mean random? Well, we all just look at our alma maters, and we kind of select any random kid from our alma mater who wants to work here.

And I said, well, where'd you go to school? He said, Yeshiva University. And that's fantastic, but he might not get the diversity. That is not a historically Black school as far as I understand, correct? Not historically. And again, it's unwittingly. In my experience, the vast majority of the disparities that we see in companies are being produced by buckets two and three.

But you need to know that because imagine it is an information problem, okay? The last thing you want to do is hide information on the resume. And so that's my antibiotics versus ankle pain issue, which is you want to do is hide information on the resume. And so that's my antibiotics versus ankle pain issue, which is you have to take the data, diagnose, and then figure out solutions that actually work. We're doing it all wrong. So this magic software of yours sounds to me from the outside a little bit like science fiction in that you have some kind of magic x-ray wand that you can wave across a firm and you can glean what is in people's minds and hearts. But I assume this is real science. Persuade me that it's real and tell me

how it actually works. It is not at all science fiction. It's going to be embarrassingly simple when I tell you how it works. What happens is we integrate into their HR data where they may have data from their applicant tracking systems, etc. The first thing we try to do is understand what the real disparities truly are. Because average disparities are very different than once you actually account for apples and apples, right? Let me give you an example from a case study. So a hospital network reached out to us and said, we have a 33% difference in wages. So women earn 33% less in our hospital. We've done all the training we can do, implicit bias. We've done everything. And so what can we do? We got their data and that 33% was true on average, but, you know, it's a hospital network.

You can't compare doctor's salaries with nurse's salaries and things like that. And so once you actually accounted for some basic demographics to compare apples with apples, that 33% went down to 8.9%. surprise anyone who's familiar with the research of your Harvard colleague, Claudia Golden, who's been writing about the gender pay gap and how we kind of get it wrong. Yes, right. But still, 8 point something percent is not zero. So what did you want to do next? Oh, and that's important. It's not zero, but it's not 33%. So you'd be surprised, or maybe you wouldn't, that this emboldened the COO. The COO was a woman who said, 8.9% I can do something with. 33, I don't know what to do. That's step one,

understanding what the true disparities are. And for this particular network of hospitals, once you accounted for overtime hours, that's what explained the 8.9%. And so we had to figure out why is it that women weren't working as many hours? Was it because they didn't demand as many hours or was there a structural barrier to them getting the hours they wanted? Like family care, perhaps? There you go. And so what happened is very simple. They had shifts from seven to seven. Okay. That's just the way they've always done it, 7 to 7. And when they changed the shifts to 10 to 10, then this disparity went away. Walk me through that. 7 to 7, 7 a.m. to 7 p.m., that is?

Yeah, that was the shift for the nurses, for the hospital network. And the issue for this particular network of hospitals, not all, obviously, but this particular one, that many of the female employees who were working those shifts told the administration, it's really hard to find childcare in the morning. But if I can get my kids to school and come to work, it's easier to find in the evenings. And so, therefore, if you shift the schedule back, we can work as many hours because we want to work hours. They were going on. Turns out it was actually 8.9%. Turns out if you made a scheduling change, even that was dramatically reduced.

And so by using data in a matter of a few weeks, it completely transformed how they thought about the disparities in their organization. That example is incredibly compelling. It also strikes me as very different from a lot of what we read about as DEI, you know, awareness and training and hiring, because the example you gave was so empirical, it was so concrete, it was so actionable, and so on. I hate to be cynical about it, And I'm sure that the cases that become public that we read about are just a small fraction of them, but they make a really big impression. I remember there was a story about Wells Fargo, which had done all kinds of illegal junk over the previous several years. But in 2020, they pledged to increase diversity and they took up this policy that required that all hires over certain salary level, I think it was $100,000, would include at least one interview with a

candidate who was female or a person of color, right? It was kind of the corporate version of what's called the Rooney Rule in the NFL. It was later revealed, and this was just a couple years ago, that Wells Fargo had conducted fake interviews with women and minorities after the job had already been promised to someone else, which I'm assuming is often a white man. So when you read that kind of story, you say, oh gosh, $66 billion worth of hand-waving and window dressing. I'm sure it's not that bad, but can you talk to me about how bad it actually is? Well, I read the same stories you do. I just approach it from a different way. Some training and those programs, they can work, but when targeted to the problem.

This is not controversial, right? This is not a magic wand. This is, let's start with the data, and if the data lead us to a particular empirical issue that we think the Rooney Rule can solve, let's do it, right? Let's actually do it, and it's not fake do it, but let's actually do it. If the data lead us to a place where we think training is really important, so be it. But the issue, I believe, is people are desperate to make a difference. They are desperate to show that they are an ally.

They are desperate to show that they are on the right side of history here. So they're in a big scramble to just do something. And I think that is dangerous because over and over again, we have examples that even if they're earnest attempts, guessing hurts the people a lot of times that we're trying to help. In DEI, we're scared to make mistakes, right? And so I want to introduce, lo and behold, I'm an economist, a little bit of experimentation, a little bit of trying things, data-driven, to try to really make progress. This approach is about getting 2% better every day, not about checking a box so that you can appear on the nightly news and say, we did this great thing and move on. So let me ask you this, Roland. You've said in the past that your research on police bias hasn't changed policing and that your research in education hasn't really changed education.

I'm guessing your work on DEI programs probably isn't going to change DEI also? It's doing amazing. Third time's a charm. No, the truth is I don't know what impact it has had, but it's not enough for me because I'm committed to what we're doing, but I don't want to lie to myself either about the impact we're making. The reason that we started EO Ventures was because founders have real power. You know, the schools in my grandmother's neighborhood in Florida are all still bad, but everybody's got an iPhone. Okay. These founders, these technology companies have really changed the way, obviously, duh, changed the way we live and work. Can we use that same power to make real changes in the neighborhoods that I've been concentrating on my whole career and in companies and things like that?

I really believe that's true. And so I am 100% behind the strategy of using market forces to close racial gaps. Hey, that's pretty good. I got to put that on a T-shirt. Coming up after the break, more Roland Fryer-isms that ought to go on a T-shirt. Shalom, brother. And what happened when the New York City schools made Fryer their chief equity officer? Well, kids have a lot of cell phones in schools.

Do I get credit for that? This is Freakonomics Radio. I'm Stephen Dubner. We'll be right back. A quick reintroduction. This is who we are speaking with today. I'm Roland Fryer, and I am a professor of economics at Harvard University and the managing partner at EO Ventures. And then there's another project you're involved in called the Reconstruction Education Project, which offers what one person calls

an unapologetically Black education. And this is not instead of school, right? It's online classes on top of school? Yeah, this is supplemental. But, you know, it's a Hebrew school for Black kids, right? It is. Shalom, brother. Shalom to you, too.

My co-founder and CEO on that is Kaya Henderson, who is like an American hero, right? She did amazing work in DC public schools and with other organizations. And Kaya's got a real vision that black communities should support and nurture and take over how we tell history and how we get a chance to write our own story. She wants kids to see themselves differently in life and in school. Again, very similar to what lots of other groups do, whether it's a Saturday school for folks who are Korean or Hebrew school, that's what Reconstruction is. And they're doing really, really quite well. You know, it's interesting as I hear you just describe Kaya and that project,

it seems that the public discourse about race treats Blackness as a problem. And it seems that you not only never thought like that, but think quite the opposite. And that feels manifest in something like this reconstruction project. Can you talk about that for a moment? And maybe I'm wrong. Tell me if I'm wrong, Roland. No, man, that's a great point, Stephen. You are exactly right. And you met years ago my grandmother. I did.

Who was really close to me. And we had our issues, but love, love, love that woman. And one of the things that she did when I was a kid was anytime we saw a white person mess up anything, it could be accidentally tripping over a curb. It could be that they weren't quite dancing on beat. It could be that they gave the wrong change at the grocery store. She would look at me right in the eyes, and then she would roll hers, and she would say, hmm, that's that superior race. And she just made me always feel like I was so lucky to be Black. And so I've never, ever, for one second, thought of Blackness as a problem.

And you're right. Many people are seeing that, or at least implicitly and sometimes explicitly saying that in public discourse. We, as a community, can take over what we teach our kids, what we signal to them. And reconstruction is a celebration of Black culture. It's a celebration of Black love. It's a celebration of Black excellence. So, Roland, you are not what I think of at least as a behavioral economist, but you certainly know enough about behavioral ideas like anchoring and framing to understand how strong those concepts are for many people and how they can set expectations. It's huge because it implicitly puts a cap on what kids think they can achieve,

right? Like, I really thought I could be anything. And I didn't understand that we grew up without money until I got to Harvard. And someone says, wow, you grew up without money. I didn't understand. We didn't summer places. And so I think it's really important. You mentioned framing and anchoring. Let's add another one to that, which economists don't know a whole lot about, which is identity, right? Two of my favorite economists, George Akerlof and Rachel Cranton, somewhere around 2000, wrote a paper on the economics of identity. And they start this paper with this beautiful sentence that identity is one of the most important choices that an individual can make. That's what I think this is about. Who am I? Who are my people? You know,

when I was in school in Texas, it was like, well, there was slavery, and then there was Jim Crow, and then there's you, right? Let's take a test. Whereas we didn't learn about the rich history that all of us come from. And other cultures have institutions or organizations that help them understand their history and their role in promoting their own culture and how they situate positively in that history. And we don't do a good job of that. I'm really influenced by that question, Stephen, because I just returned a couple of weeks ago from Israel, and I called Kaya from Israel, and I said, wow, right? This is an example of some of the things we were trying to do in terms of a shared understanding of our history, the ups and the downs, and building upon that history to make a generation of super kids who, like me, felt like they could do anything. Way back in 2008, you went on the Colbert Report, and you said that the achievement

gap in this country is our biggest civil rights concern. That statement has some echoes, to me at least, of Du Bois saying the problem of the 20th century is the problem of the color line. Fifteen years later, how do you think about that statement of yours? The achievement gap is the biggest civil rights concern. Do you think that's still the case? Yeah, absolutely. The issue is development, and that's what I meant. It's development, period, the end. And yes, yes, of course there's discrimination in the world. Of course there is. But if you just look at the data, the vast majority of the disparities are driven by differences in development.

This is apropos of everything we've been talking about. Folks have now decided it's not the achievement gap anymore because that's offensive. It's the opportunity gap. Give me a break. You think that's helping the people in the neighborhood? Oh, thanks. Appreciate that. I can really go now.

Really? But yes, that's it, right? If we can solve that problem, many of the other things that are social ills, you know, there's no magic bullet here, but they will get a lot better, right? When I wrote about defunding the police, I was like, why don't we invest in kids and they'll have, you know, productive jobs and the police can defund themselves. Years ago, you were something called the chief equity officer in the New York City schools. Tell me how that went and what you learned from it. I was fresh out of graduate school, wanting to make a difference. I called up PS70 in the Bronx, which was off of Colgate Avenue in the South Bronx, close to where my uncle used to live. And they wanted to do an incentive program. I love

the idea of an incentive program. It fit everything I knew as a young economist. And so they would take tests and they would literally email me the results and I'd order pizza. That's how it started. Meaning the kids who did well got pizza or cash later, right? Absolutely. No, no cash. Pizza, man. They got pizza. Well, didn't you try some cash later? No, I've tried a whole lot of cash later. Yes. And so that was the start of it. One school. And then that blossomed to 14 and then to 140 in New York City and, you know, half of the school district in Washington, D.C. and schools around the country. And yes,

one of our first things as the chief equity officer in the New York City Department of Education was to try innovative programs and rigorously evaluate them. Okay. Data first. Really simple stuff here. Collect data, analyze it, be honest about the answer. Don't bury the results when you don't like them. And then have a real strategy about how to execute on ideas that are promising. That's all we were trying to do in the New York City DOE. That's all I've tried to do with the police and all I'm trying to do now with corporate DEI. So in that case, we ran incentive programs. Some of them worked, some of them didn't. But then the cool thing that we tried to do, Stephen, that we never quite got off the ground was I wanted to rebrand education for kids and communities. And so we had this campaign called School is Money. One of my ideas

was let's get a rare shoe that LeBron James will wear. And the only way to get that shoe is to make, you know, good grades in New York City public schools. All the adults, they were like, oh, this is great, Roland. This is so smart, right? We focus group this with kids. And in 37 seconds, a kid looked at me and said, man, I don't want those air nerds. That was done. But we tried all sorts of things like that. So we tried an initiative called the Million Program where we gave kids cell phones phones and we texted them things throughout the day to try to give them messages to change the culture around trying hard in school. So we would say

stuff like, your average life expectancy is 72 years. That's a long time to be broke. Or give them the fraction of millionaires who also have a high school or college degree, things like that, to try to get them to rebrand education. So this was all a part of that job of chief equity officer. And again, some things really worked and some things didn't, but that's the whole point. It was kind of an R&D unit within the New York City Department of Education. And kudos to Joel Klein and Mike Bloomberg for letting a 28-year-old kid come and try new things. That would be kind of unheard of now. Are any of those programs or ones like them still in existence, either in New York or elsewhere? Well, kids have a lot of cell phones in schools. Do I get credit for that?

Yes. I think we'll give you all the credit for that. Thank you. Thank you, Verizon. There are many incentive programs going on across the country. They're just not well publicized because they're still controversial, oddly enough. Controversial because of the idea that learning should be driven intrinsically, right, by the love of learning versus rewards? Yes, absolutely, yes. What do you think of that idea? I agree with that. I also think that there should be peace in the Middle East,

and I think, you know, global warming should stop. Okay. Anything else? But no, seriously, seriously, I took it the opposite direction, right? They thought you're going to destroy the love of learning. I thought this is a way to cultivate it. Do you think you were mostly right then or no? I think both of us were wrong. I think it had no effect because we measured, lo and behold, there's that data again. We measured using their measures, pre and post love of learning, and the coefficient was positive, but it wasn't statistically significant. So we had no real effect or big effect on love of learning either way.

What we did have an effect on is test scores went up. And is that not enough? To me, that's fantastic, right? If you can get test score gains and you don't change the love of learning, that to me is a policy worth doing. Never mind, it's really inexpensive relative to other reforms, right? This isn't changing the number of kids in a classroom, which is really expensive, but this is something where you can actually increase student achievement at a relatively low price. Most education reformers, even the most idealistic, also care about test scores, and you are offering here a route to a relatively inexpensive intervention

that raises them, I would think, therefore, that incentive programs in schools would be everywhere and widely publicized. Why are they not? Because there's real pushback on incentive programs in schools by lots of folks. It's not just the progressives who believe that we should do it for the love of learning. I mean, I published this piece in the Wall Street Journal a couple months ago about using incentives to battle COVID loss. And, you know, I got it from both sides there again. Some people said, you're going to destroy the love of learning. The other says, here you go again, wanting another welfare program. It's just a controversial thing.

And I think that schools are doing it in secret. I think they're doing it without cash. They're doing it with school t-shirts and pizza parties and things like that. There's lots of charter schools and public schools who are doing this that Written On. It's by Wai-Wa Chin. She's a fellow at the Manhattan Institute. She's also the founding president of the Chinese-American Citizens Alliance of Greater New York. Here's the opening of this piece in The Post. When renowned economist and education innovator Roland Fryer served at the School Board of Massachusetts and attended a public meeting to close a failing school, a Black mother walked up to him and told him that the school was a good school. No, ma'am, said Fryer, who was also Black. It's not.

The mother pulled out her child's report card from her purse. It was all A's. The mother insisted, this is a good school. Fryer had to tell her, ma'am, they have lied to you. That story sounds as though it must have come from you originally. So first of all, is that a true story? It is a true story, yes. What does that even mean that the school lied to parents that the A's that their kids were

getting weren't real A's? The issue is, this is one of the toughest things I did serve on the school board of Massachusetts. It was an amazing experience to see it from that angle, I took it very seriously. And the hardest thing I did during my tenure there was to have those meetings where busloads of parents came. It was really hard for me to watch parents fight to keep open a school where the literacy rates and the test scores were so low. And what I meant by they have lied to you is that there's no way a kid can get all A's and still perform so poorly on these exams that are measuring basic skills.

And so the expectations must be very low in that school. And so that's what I was reacting to. And it was sad, man. The thing that drives me nuts, sorry, I'm gonna get fired up about this, is that this woman's doing everything that she thinks is right. Part of it's on us dumb researchers who keep saying stuff in standard deviation units. Parents don't understand things in standard deviation units, folks, okay? We are obfuscating the truth by providing this in a way that not all parents can digest in the way they should. And so that's what I was seeing. This woman looked at the school, saw great report cards, so she thought it was a good school, but her kids were not being served there. Is this what's behind the motivation of a lot of schools

to get rid of standardized tests then? I don't know if it's to get rid of them. It may even be to make them easier. I really do believe that kids will live up or down to your expectations, that if we really held those things high, and this is not just Roland talking, when we did our work on effective schools, one of the five tenets that makes a school effective is high expectations. When you don't have that, then there is this gap between what a kid thinks that they're doing and their report card potentially, and actual skills. You mentioned that high expectations are one of five behaviors or policies that make good schools good. This was in a study you did of charter schools, but as I understand it, this would apply universally. Can you list the other four?

Sure. More time in school. So basic physics of education, that's pretty simple. Then there's using data to drive instruction. It wasn't just that you use data because nearly every school now has some form of data. What was different about the schools that were effective is that they had a real plan. If we take this assessment and 50% of the kids pass, then we pause and we reteach, right? We don't just keep going. Number three was, you know, small group instruction, or as my grandmother would call it, good old fashioned tutoring. If you tutored kids in groups of six or less for four or more days per week, then your test scores were a lot higher.

Then human capital, right? How you select, retain, and develop teachers, and particular teacher feedback, really, really important. And then the last one was, as I said before, a culture of high expectations. So they all understood that they were dealing with high poverty rates. They all understood that they were dealing with, unfortunately, many single family households, et cetera, but they didn't use it as an excuse not to teach. And those five factors explained 50% of the variance in what made some charter schools good and others not so good.

Let me ask you this. If you look back at your life and career, how would you think about measuring the costs and benefits of your being Black, both professionally and personally? Man, that's a great question. Never really think about it, except for, you know, I'm a lot cooler than my colleagues. Honestly, I don't really think about it. But look, let's be honest.

It has opened doors. It has closed windows, right? I have been given tremendous opportunities, and I try to take advantage of them. I don't have any to spare, put it that way. I think it's helped me some. It's hurt me some. What the net effect is, don't know, don't care. Do you think race played some significant role in what happened with you at Harvard,

in the suspension, or no? You know, I think that probably, but not in the ways that you might think. I also believe that, you know, being an asshole probably didn't help, right? I'm no angel here either. Early in my career, for example, I really tried not to have any money that I raised privately go to overhead for the university. I was trying to give it to poor communities. And that's probably not the best way to build teamwork. And there was a point at which like folks inside the university didn't want to be associated with my incentives research because it was too controversial. So did I push the boundaries trying to do things for the kids in

the neighborhoods I served? Yes. Did I spend more time off campus because I thought that the kids in these neighborhoods needed my time more than the kids on campus? Yes, I did. And did that rub people the wrong way? And did that come across as an asshole? I'm sure it did. Do you regret it? Or do you feel like that's just who you are, and you've learned from it, and you're in a different mode now? Of course, of course, I regret it and have apologized for it. And the thing that I worked really hard on while I was off campus was trying to be authentically me, but not have anything that could be even perceived as offensive to someone else. And that's hard.

But I took it very seriously. And I'm back better. I'm back stronger. You know, I used to, it would have been nothing for me to have on Thanksgiving to have 20 students over my house for Thanksgiving dinner, cook a bunch. You know, they fall asleep on the couch. We play video games. I don't do that anymore. So I would say that there's clear delineation from my living room to work. And I think that's a good thing. I was worried that was not going to be, I thought, how could I do really cutting edge work?

But I was wrong about that. I can still be me. You and I have mixed it up the whole time here. I'm still Roland. I still care about these issues. I refuse to not tell the truth, but I'm at a different and dare I say, more mature part of life.

I broke a lot of glass early on in my career that had nothing to do with that, but all to do with me being impatient as hell and wanting to help and trying to do the right thing. And I don't think that was helpful. Thanks to Roland Fryer for this conversation. We covered a lot of ground. And even though I thought I knew his work pretty well, I learned an awful lot. I hope you did, too. We checked back in recently with Fryer to get an update on his various projects. He told us that his early stage investing fund, EO Ventures, raised $100 million in 2022. And Sigma Squared, his data-driven diversity consulting firm, raised $10 million in Series

A funding. It is now leveraging its analytics platform beyond enterprise HR. Police departments around the country have started using Sigma Squared's toolkit as an early warning sign to flag bias in police practices. Fryer is also now a Wall Street Journal contributor

and his first piece there caught my eye. So he and I have decided to turn that into a future Freakonomics Radio episode. So keep your ears open for that. We will be back soon right here with our regular weekly episode. Until then, take care of yourself and if you can, someone else too. Freakonomics Radio is produced by Stitcher and Renbud Radio. You can find our entire archive on any podcast app, also at Freakonomics.com where we publish transcripts and show notes. This episode was produced by Alina Kullman. Our staff also includes Augusta Chapman,

Dalvin Abawaji, Eleanor Osborne, Ellen Frankman, Elsa Hernandez, Gabriel Roth, Greg Rippin, Jasmine Klinger, Jeremy Johnston, John Snars, Julie Canfor, Lyric Bowditch, Morgan Levy, Neil Carruth, Rebecca Lee Douglas, Sarah Lilly, Tao Jacobs, and Zach Lipinski. Our theme song is Mr. Fortune by the Hitchhikers. Our composer is Luis Guerra. As always, thank you for listening. My favorite quote of all of our things when we were going around, he said,

wow, man, you're really in shape for whatever it was at that point, 80. And he said, what's your secret? Oh, man, I eat well. I don't eat any pork. No, I definitely don't eat no pork. Well, what do you have in your beans there, sir? Ham.

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