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Hello, and welcome to the Good Science Crap Science episode of Slate Money, your guide to the business and finance news of the week. And boy, did we have a bunch of different things that we wanted to talk about this week. I am Felix Salmon of Axios. I'm here with Anna Shymansky of Breaking Views.
B
Hello.
A
I'm here with Emily Peck of HuffPost.
C
Hello.
A
And all three of us are mostly just going to take a backseat in this episode to the one and only Kathy o'. Neill. You are back.
C
Yay.
A
Welcome back. It has been a long time since you were last on Slate Money, and we love you very much. And, oh my God, do we have a lot of stuff to talk to you about. We are going to ask you the questions, which we have been saving up for months, about coronavirus and modeling it and how much should we thank or blame all of the epidemiologists who are trying to model this disease. We are going to talk about the reckoning that is happening with all the people losing their jobs in racist institutions. We are going to talk about the Ford foundation and whether they should be borrowing money right now. And if you are a Slate plus member, which you should be, you will have the glory of listening to Kathy o' Neill go off on the subject of VC funded female orgasms and smart butt plugs. It's. It's a great Slate Plus. All of that coming up on Slate Money. So let's start, Kathy, because you are the queen of all things models. Let's start with models. We've been talking about coronavirus modeling for what, three or four months now? More than that. Six months, I guess, since at least January. And give us the verdict on the first six months. How have the modelers come out of this? Have they covered themselves in glory and shame somewhere in between?
C
Yeah. I'm kind of embarrassed. I wish we had done better as an industry, if you will. I think the modelers have done pretty well. But as usual, all of their caveats and conditions were ignored and their error bars were ignored and they should have known it. I'm not giving them a free pass.
A
Basically everyone started talking about point estimates and they should have been talking about ranges. And then everyone said, we are not where your point estimate said we would be. And therefore you were wrong. And the modelers started saying, but you should have looked at the footnotes.
C
Yeah, you could say it like that. Another way of thinking about it, though, is that modelers had to make assumptions. Those assumptions were about how people would behave and the answers that they were or the estimates as you will, the approximations of death toll, for example, were highly dependent on those assumptions. And as soon as they said the numbers, which were at the beginning very high, like 2.2 million was the first one we heard, then people change their behavior. And as soon as they change their behavior, of course, the number goes way down. So in other words, there's this a feedback loop between the modeling community and the public health community, which makes the modeling community look stupid, and now they look stupid. And so my thing is, but did.
A
They also save 2 million lives by basically coming out with an estimate that was true if we just kept on with our ex ante behavior? And then because that estimate was true and we changed our behavior, we saved all of those lives. And so really we can thank the modelers for having 2 million fewer lives lost than we would otherwise.
C
I think some modelers would make that argument, but I would not. And here's why. Because we're not done. Once we are actually done, by which I mean we have herd immunity, either through a vaccine or because so many people have died, then we can look back and decide, did we save 2 million lives? Right now, though, all we can say is people got so sick of hearing 2.2 million. No, 60,000, no 500,000, no 100,000, like so many switches that people just said they threw up their hands reasonably so, and said, we don't know what to think. We're just gonna forget about it. We're gonna stop trusting you. Once you've lost trust, then public health pronouncements just lose power. And so now what we're seeing, of course, as everyone knows, is like a major uptick in cases. And in a couple weeks, we should expect a major uptick in deaths in the United States and in other countries as well. And so the verdict is not in. I mean, and I've been saying this for a while, like the Swedish approach, you know, some people are like, oh, that's it's stupid. And even the people who came up with it are now regretting it. But actually we have no idea whether it was stupid. We will not know for another n years where N is at least one. We will not know until this is all over. And that's the thing that is the most difficult for the public as a whole to understand and for modelers to explain is that we really don't know. There's so much uncertainty that we just simply cannot make a prediction that everyone will understand and believe.
D
Is it the fault of the modelers that people got sick of their models? Or is it the fault of, like, of maybe the media for miscommunicating what models actually are and. And do? Like, they're not. It's not like astrol. Like, it's not a prediction of what's going to happen. Right?
C
It's like, unfortunately, that is how it's framed. So I blame both. I mean, obviously it would be always be better if we could have better communication, and some of that is due to journalistic attempts to have a headline. But on the other hand, modelers, I think, made a mistake, and here's my real belief, modelers made a mistake by even saying death tolls. What they should have said was death tolls depend on how we behave now. And what we really should be paying attention to is the R. And the R is the only thing we have control over. And if R goes above one, it will grow exponentially and desk will grow exponentially. And if R is less than 1, we all have control of this. And that's what we should be focused on, is like, what is our R today? What will R be tomorrow?
A
Have you seen that number? Do we have a good time series for how R has changed over time in various geographies?
C
It's not perfect.
D
Wait, should we just back up and say what R is?
A
Yeah. So, Kathy.
C
Yeah, sorry, I should have said what R is.
A
No, that's okay. We can go backwards and forwards. We jump around on this podcast. Oh, good. What is R0 and how accurate can you measure it?
C
So R0 is not what I mean. I mean R of T, if you want to be precise. R naught is also known as r of 0. So I mean a slightly generalized thing, but I'll start with R of 0 or R naught, which is how with the behavior we had at the beginning where nobody had yet gotten sick, how many people did the average sick and contagious person infect? If I'm sick and contagious and all around me are people who have not yet gotten sick, or so they're vulnerable, how many people with normal interactions on average will I infect? If it's above 1, then as you can imagine, the people I infect, which is more than one, go on to infect more than one people. And so that creates exponential growth. It's pretty easy to see if it's below one for whatever reason, and that could be because it's not very infective or because I don't interact with that many people, or because I have social distancing or whatever, or that it's just not that contagious, then it dies down. So it's all about this R. R of T is just a slight generalization, is what is R? What is this impact? This what you should call a multiplicative factor of contagion at time T. As you can imagine, at time T, it can go up or down depending on social practices, depending on how contagious the biological mechanism is. Some people have been talking about how it seems to be getting less contagious or more contagious. Probably not, but. So it depends on biology, it depends on social practices, and it depends, of course, on how many people around you are actually immune. And so the point is that R eventually goes down to below one eventually. And the question is, how eventually and through what mechanism does it mean?
A
And how good are we? So to answer my question, how good are we at measuring RT at any given point in time?
C
So that's a great question. We can only measure it in retrospect in some sense, because everything has this lag, which is like two or three weeks. But we do have a pretty good estimate of what R of T was three weeks ago. And the way we do that is we measure how many people are dying now. And so we can sort of figure out as trends of deaths change, like what R of T was a few weeks ago.
A
So if the number of deaths is going down, then RT is less than 1 locally.
C
Yeah. If the number of deaths in a given community is going down, you can say, okay, R was less than 13 weeks ago.
B
That discussion also perhaps goes into. One of the problems we have with trying to communicate these ideas to the general population is that it's not simple. It's much easier to just say, we expect this many deaths. And that's easy for the media and it's easy for people to understand. But then, of course, that's not really what the model says. That's not really what. However, that's how it will be communicated. And I guess I'm wondering, like, how. How do you fix that? How do you make that into a simple, easily digestible message?
C
And that's the problem exactly, that. That we have lost. Like, we. We went for the easy thing because let's face it, and I don't really blame anyone in particular, let's face it, it was an emergency a few months ago, and we needed to make people wake up. We needed to make people change their behavior. And the best way of doing that was to count future dead people because it was shocking to hear 2.2 million people were dying. My grandmother's going to die. It was shocking enough for people to actually consider the unconsiderable, which is like not flying and not going to bars. So it made sense at the time to do it as a scare tactic. But of course what it did was it made people react well and then lower that R to less than 1 at least in New York City.
B
I guess then the danger though is that when you have a time where you have a large segment of the population that already questions statistics and questions science and then when you have this happen, if people don't quite understand what it means, then it can just give more ammunition to that side.
C
Oh my God. And that's a really good point Anna, because I actually worry because this is what I do, I worry about people's trust in good science and I keep track of bad science because bad science gives a bad name to good science. There is underlying very, very important and very good science going on here. But because of this PR problem, this trust problem, the really, really crap science like the anti vaxing is making a comeback. And you see this, you see that some of the most vocal anti stay at home order protests were led by the anti vaxxers. And there's a reason there, there's a connection and it's a conn. If we good scientists do not acknowledge and do not change our approach, we are going to see more and more of that.
A
Let me ask the international question which is if you look at countries which have been incredibly successful at fighting coronavirus like Vietnam, say is there something about that population or those populations that is more trusting of science, more willing to just do what they're told that cannot be simply sort of read over to the United States. What's the difference between Vietnam and the United States that accounts for the massive difference in outcomes.
C
I don't know much about Vietnam but I did study Singapore pretty in depth. And so I'm going to answer your question for Singapore and for that matter China. There's two possibilities for the countries that did much better than us at the beginning anyway and again, not over. We're not done. One is that it's just an autocracy. So there's complete control from the top, top down control. That's China, the China model. And then there's the other model which is the Singapore model which is like it is pretty controlling from the top but actually the people trust the top. So there's like an. And Sweden for that matter is similar. Like they trust their.
A
Or Germany or New Zealand.
C
Yeah, there's trust and then there's autocracy. United States has neither of those. So that's one thing. But the secondary thing, which I think is just as important, if not more important, relates to what happened with Singapore. Singapore was a success story early on and was essentially because of their contact tracing, which was pretty amazing and intense and very detective like. They would call people and check up on people, and China does this too. And it looked like they had tamped down all the cases. And then guess what? There was an outbreak in the dormitories of the guest workers. So they have this separate world for guest workers where they're cramped in these dormitories. It's very, very unequal. These are guest workers, men, young men from Bangladesh. They got really sick. They had no control over that. If you think about that other factor, I'll call that the inequalityracism factor. That is very big deal in our country. So if you think about who's getting sick in our country, where are the outbreaks? They're in nursing homes, they're in prisons. They're in Queens and Bronx, where the service workers live. They're affecting people of color. And I would even argue the nursing home situation is much worse here because it's staffed by immigrant women that have to work two or three jobs because it's such a bad job. So it's all about this. I would claim that inequality and racism and mass incarceration are, in fact, causal factors for pandemics. Beyond the question of how does the country work with trust or control.
D
I think that's such a good point. And I think not only you see it in how many people who got sick and where people got sick, but in the policy response. Because I think it was back in April when the data first started coming out and became clear that black Americans were dying at higher rates, getting sick at higher rates. I think if you go back and, like, do a timeline, you can see that the policy response, particularly at the federal level, started to die off at that point. There was a big difference Then, I think after that data became clear, especially like Trump, you know, started coming out and saying, like, let's reopen the economy. And I think. I think there was a sense that it was like, oh, maybe it's not so bad for certain people. And the like unified the way the country had initially responded to Covid that. Very unified in the beginning, if you can remember it, like the stimulus packages passed unanimously. That all kind of came to an end after it became clear that there was an inequality in who's getting sick and who's dying.
C
You know, I agree with that, Emily. But at the same time, like what consistently befuddles me is just what came out yesterday. And I know this is not a topic, but it is related, which is like Trump's gonna hold rallies and he's gonna make his own supporters sign away their rights to complain if they die. And I'm just like, wow, it's not really tribal.
A
Right.
C
It's not really like I wanna protect my own, because how much more my own can you get than his own rally base? So it's a little bit less humane than what you just described. You described the kind of tribalism that is like extreme. And I think that's true. But I think another factor is simply that some people just don't care.
D
I think, I think you could go deeper on that and think about does Trump actually care about the people who attend his rallies? And like, look at how he's governed and it's not clear exactly that he actually does. Like he just views kind of props.
C
He wants them to vote.
D
Yeah. So it actual consistency, maybe you could make a case like that.
A
Yeah, he's certainly doing a hell of a lot of tracing inside the White House.
C
Exactly right.
A
For the people who come in contact with him.
C
Which points out that he doesn't actually think that it's not a thing. He believes coronavirus is a thing, that it is threatening. But he's personally protected. I don't know, it's just.
A
Although, yeah, we know he's personally protected because he's taking hydrochloroquine.
D
It's hard to make sense out of it.
C
Good one, Felix.
A
So let's talk about the reckoning here. The disease was racist. It created a huge amount of grief and anger and righteousness. That grief and anger and righteousness was then catalyzed and was made to grow nationwide by a number of killings by police forces. And now this huge protest movement has started resulting in people getting fired, in basically racist bosses getting fired. And this is happening more quickly, I think, than anything we saw in MeToo. Right. But Emily, you've been covering this more closely than I have. Have you been surprised at the number of race related senior management defenestrations?
D
A little bit. I mean, it did seem to happen. It was in the span of less than a week. We saw J. Bennett, who headed up the New York Times opinion page. He left was, I guess you could say ousted. You saw over an op ed that ran, but that was really like the latest example of New York Times staffers kind of getting upset over the way he handled that page or that section. You saw Adam Rapoport at Bon Appetit, the editor in chief. He also left. The woman in charge of Refinery 29 was accused of. Or her staffers spoke up about the way they were treated. She left. And there's more.
A
Like that's just the head of retail Adidas.
D
Just the volume.
A
There's rumors. I mean, we're recording this on Friday. It is possible, by the time you listen to this on Saturday, it is possible that Anna Wintour herself might resign. I've been hearing, like, rumors in the mediaverse. I mean, which would be by far the biggest name yet. But if you look at the masthead of Vogue magazine, this is quite astonishing. The 10 most senior editors at Vogue are all white. All of them are, yeah.
D
I mean, so it was a surprising in the fast pace of it, but I think it's been a long time coming in terms of how media has covered race and who they've been hiring. I feel like it was only a matter of time before staffers said, like, you need to live up to some of the ideals that you pretend to believe in.
B
Yeah. And it just seems like it's a much, I think, a much larger underlying problem. And I think even the fact here that we are, for white people, talking about race in media, I mean, kind of is indicative of the problem, you know. And, you know, when you work in media, you just see it, and there are a number of reasons for it. You know, it's. It's an industry that's not particularly well paid. In order to get into it, you often have to go to very, very good schools. You often have to know people. There are all of these things that are much bigger than just firing one person. It's not to say you shouldn't fire someone who's doing bad things, but that doesn't change all of the other underlying factors.
D
I thought about that, but I think firing these kind of racist bad apples at these media companies. It's not like I wrote a lot during MeToo about, like, you can't just fire the one guy who's like the worst sexual harasser. Everyone's still going to be really sexist. But I think if you have one person who's really biased and mistreats people at the head of an organization, that's that.
C
That's a.
D
You remove a big cause of the rot when you do that. I think that.
B
No, I think you're. I think you're right. I mean, I do think that culture often does start from the Top. So I think, I think that it's not insignificant to fire someone at the top. However, I still think you aren't going to fundamentally change how media hires if you are simply firing a few CEOs.
A
No, but if you replace. Like if you look at what happened at Harper's Bazaar, now has its first black editor. In stark contrast to the Vogue masthead at Bon Appetit, there was this amazing Business Insider story which detailed how Adam Rapaport's Stanford graduate assistant, who was black, was being made to get his golf clubs cleaned and was being paid $35,000 a year and didn't get a raise for two and a half years. And Conde in particular, and Vogue in particular, there is, there has always been this elitism of, you only work here if you don't really need the money and you're already rich and well connected and we hire you for your wealth and connections. And because of the centuries of structural racism in this country that effectively excludes black folks from all of those magazines.
C
Can I just jump in with a positive example of this rather than sort of saying there's no end. And I don't disagree with anything that's been said. I would just like to point out that Jon Stewart, who replaced himself with Trevor Noah, actually did something pretty cool there that I don't think we discuss enough. Like, if we're worried about people of color not leading, then let's give props to the people who actually replace themselves with people of color.
B
Actually, that's a really good point because I was just gonna say, because the Daily show under Trevor Noah, it deals with race a lot and it has a lot of.
C
And Trevor has been killing it, and.
B
It'S a much better show, I would also just say. So, yeah, I think that's a great point.
D
And Alexis Ohanian, he's the founder of Reddit, right? And he was still on the board until this week. He stepped down and said, you know, I should have done this long time ago. I want to make way for someone of color to take my place, which is sort of a positive development that people kept bringing up to me that people need to step down and make way for sort of the next, the next generation. I just don't think that's, that's not like a, like, that's not a strategy that's gonna, that's gonna scale, in the words of the technology.
A
Although if you, if you look at the statements from the likes of Adam Rappaport and Audrey Gelman, who just stepped down as the CEO of the Wing and people like that, they all use exactly the same language, right? Which is they go through the standard corporate statement, which is, racism is bad and there's structural racism in the country and also in our company, and we need to do better. And then they say, well, as part of that, I should step down and make way for someone who is less white than me, basically, or at least more woke in various different ways and doesn't have the whole history of racism that people are accusing me of. And Alexis did it, obviously from an entirely voluntary basis, whereas I'm sure that Adam Rapperborough and Audrey Gilman did not. But the form of words is the same in both cases. What has actually struck me is the way in which the need for change and the acceptance of the reality of racism in corporate America has been accepted by everyone. And Frank Lutz and the New York Times had a good article about that about this this week. Public opinion has changed faster on this issue than on virtually any other issue in the history of polling that if you ask white people, is America racist? Are the police racist? They are saying yes now. And just a month or two ago, they were saying no. It's a massive change. And even the people who are stepping down, who are accused of being racist are saying, yeah, I'm kind of racist. I shouldn't be here.
D
I just wonder how far, like, all the examples that we've talked about and that I've seen are mostly contained to media or the entertainment industry. What I'm wondering about now is, like, banking, the finance industry, because I've been doing a little more reporting this week, just talking to people and at places like that, or consulting, where the racism is pretty insidious and hardwired. And I wonder, even though public opinion has shifted, I wonder if those places, those institutions are really gonna be able to actually change. Because I just, from what I'm hearing, like, it's bad in there.
A
I don't know if you guys all saw the letter from Fred Baba at Goldman Sachs, who wrote this very sort of heartfelt letter about his experiences. He's a Nigerian American managing director over there. And one of the things that really struck me, looking at the banking industry in the US and the uk, is how there's a fair amount of black folk that I would interact with. I mean, as we discussed last week, in emerging markets, you tend to find more. But one of the things that strikes me about Fred Barber and many of the people that I would talk to quite a lot just doing my job, is that they're West African or otherwise. Not American, and they're African Americans. The people who come from the families who've been living in this country for 400 years and have had to live under a systemically racist regime for 400 years are massively underrepresented, even among the black employees on Wall Street. It's actually much easier to find someone from Suriname or Ghana than it is to find someone from Alabama.
C
That's totally true.
D
I don't think that's an accident. I mean, there's so much research that you just show people, hiring managers, resumes, you just change the names, and they make different decisions based on who they think the color of the person's skin is or their gender or whatever. And you talk to people who work in these institutions and they're treated differently. Despite them putting out posts about standing with their employees or Black Lives Matter this or that, people are still treated differently. And there's no newspaper or public with the newspapers. They have actual coverage. The Philadelphia paper, they had a headline that said, what buildings matter too? And it was like, jesus Christ, everything needs to change immediately. But with the banks and stuff, I feel like it's just harder now. We have laws and stuff that they have to abide by to keep them from being very discriminatory. But it's hard to really get in those places and understand those dynamics.
C
Right.
D
So it makes it harder to have the reckoning there.
B
Yeah. And I think it's similar. It's probably so much what you see in tech and a lot of these industries where you have not everyone, but you do have a lot of people who've been raised around a lot of privilege, and they really, honestly believe that everything is just about merit. Like, they will say, oh, no, we'll just hire the best person. It doesn't matter their color or gender. We'll just hire the best person. And those best people just all happen to be white. And I mean, it seems ridiculous. Especially now, it seems ridiculous, but you still run into this all the time.
A
So you're not hopeful? You don't think anything's really going to change?
B
No, I mean, I'd like to say I am. I hope I'm wrong, but if I'm honest, no, I'm medium hopeful.
C
Or these people who are misidentified by this. Okay, this is a kind of complicated point I'm trying to make, but it comes down to what you guys were saying. It's, like, easier to get hired and to be treated well if you have an African name than if you have. If you're an African American with a white slave name. There's more racism amongst those people. That's what I've been seeing in my data. And I think it's class. Right? The people that immigrate to the United States from Africa are very well educated. And it goes to. That's similar to the question of the Asians who come here do quite well. Guess what? The Asians that do quite well here are typically immigrants that have college education. They're very, very well educated. And that is the distinguishing feature. Anyway, I don't want to go too deep into it. I probably already went too deep. The last thing I'll say, though, is in terms of hopefulness, I am actually kind of ironically hopeful, even though I do a depressing thing almost every day, which is measure racism and algorithms, which is like, I actually think we could, if we wanted to build anti racist algorithms, and to the extent that hiring has become algorithmic, which is really quite a bit, this could actually help. But it would require us to just do it. The question is, does this protest movement that we've been seeing gathering steam and this acknowledgment and recognition of systemic racism, is that going to culminate in action at that level? I don't know, but I am more hopeful than I was a month ago.
D
Everyone listening needs to get Cathy to de racist their algorithms.
A
Anti racist their algorithms.
C
I would like to anti racism.
A
We don't want to just de racist them. We want to anti racism. So I want to segue into. Darren Walker of the Ford foundation came out with a very interesting announcement this week. He said, this is a time of emergency. This is a time when the charities we support need funding more than ever. We have historically just been handing out 5% of our endowment every year to those charities. It's not enough. We need to double the amount that we're giving them. Everyone. Yay. Good job, Darren. And then he added an extra little twist to this, which is, but we're not going to double the amount of our endowment that we give to those charities. Instead, we're going to go along to Morgan Stanley and Wells Fargo and ask them to issue bonds on our behalf. And then we're going to use the proceeds from those bonds and we're going to give them out to the charities we support. And that way, all of the money managers who look after 95% of our money, well, look after 100% of our money and are forced to cough up 5% of it every year to give out to charity, they get to continue to look after 100% of our money. And they don't, you know, and that's good, right? And there was actually, on the Ford foundation website, they used the F word, fiduciary, which really annoyed me, because I don't think they have any fiduciary responsibility to, you know, anyone to just hold their money rather than spend it. Anna, tell me. Tell me if this bond issue makes as little sense to you as it does to me.
B
I actually think it makes sense.
A
Oh, okay.
B
I do. I mean, look, you have. When you run an endowment. I know you disagree with this, Felix, and I think we've had this argument before, so. But we know when you run an endowment, ideally, you want to keep your principle growing because that's also what you earn money off of. And if you're constantly reducing your principal, like, at a certain point, that can put the endowment in jeopardy. That's how endowments work. Whether you disagree with it or not, that's how endowments work. And at a period of time where rates are really low and you can issue debt and then you can spend that money, and so then you can both grow the endowment, which then will kick off even more income, and you can still spend with this additional money you're getting. I don't really understand what's wrong with that.
D
I have some thoughts about what might be wrong with that. My first. I didn't actually realize that foundations, these big ones like Ford, with billions of dollars, they only give out 5% of their money every year. Like what? Like, I'm supposed to think the Ford foundation is, like, this very charitable giving, not for profit, like, good institution, but it's only spending a small, small sliver of what it has on all that good stuff and is actually paying all this money to, like, money managers and putting its money into venture capital and private equity. And, like, it just seems kind of icky to me. I don't understand why they wouldn't give more of their money.
B
Like, there is money left.
A
There is. There is.
B
Third point.
A
There is one exception.
D
They'll have money left. Like, I'm no genius, but I looked at the chart of how much money these endowments have made over the years, and you can't. You can't see me because you're not listening. You're only listening, and you're not watching the zoom. But, like, it's going up a lot. You know, how much money they're making and how much money they're giving away is staying very steady. And I think there's more they could have given away and still maintain their massive endowment. I think it's gone a little too conservative.
A
It's clearly too conservative because if you look at the total amount of money in individual endowments like the Ford foundation, or even in endowments generally, well, it's even more striking that the amount of money just sitting invested, as you say, in venture capital funds, in private equity funds and hedge funds, has been growing and growing and growing at a huge rate at a time of great need. And the need generally for charitable interventions goes down over time rather than up over time. And that's a big case for front loading these things and giving away money now, because the total amount of money invested in charitable endowments is always going to go up, even if it's not in your charitable endowment. There is one interesting exception to the Ford foundation rule of only spending 5% of its money, which is if it gets to spend the money on itself, it did spend, I think, 6 or $700 million recently renovating its headquarters on 42nd street in New York so that they can find the money for quite easily. But what really strikes me here is the speed of decision making at endowments. It seems absolutely obvious to me if you look at the stated rationale from the Ford foundation and especially from the Hewlett foundation for not spending more money. Now, the stated rationale was always it doesn't make sense to sell our assets when they are depressed, when they've been beaten down by the economic crisis and the crash in financial markets. You don't want to sell low. You want to hold onto your assets for the long term and maybe borrow money to give away. Now, all of these arguments make perfect sense if you're in late March or early April when the stock market was down like 30% and make absolutely no sense right now when the stock market is near its all time high. And it seems obvious to me that what happened is that they all started talking about this in late March and early April and it takes so long for them to get around and actually do anything that they're only announcing it now. And now that they're announcing it, everyone's looking at them going, well, are you honestly saying that the stock market is so low right now that we shouldn't take losses by selling stocks and putting them to good causes? That doesn't make any sense. So there's definitely just a case here that things move very, very slowly in the foundation world and always have, though.
B
I would just say, I mean, if you have the option of. Yes, it is true that obviously the stock market has recovered Quite a bit. It's still obviously off of its February highs. So, look, if you're saying we can sell this asset now for less than we'd probably be able to sell it in the future, or we can take on debt and then we don't have to sell at a lower price and we can give the same amount of money away, I just don't understand why that's a problem. I think that that makes reasonable sense. And when you're figuring out, as an endowment, like, the risk you can take, what you're investing in, it's based on how much money you give out, because you're not supposed to be reducing the amount of principal. So if I'm giving out.
A
But doesn't taking on a billion dollar and liability effectively reduce your net worth? I don't understand why.
B
So the idea, it's just like any type of leverage, if you're earning a higher rate than what you are paying out on that debt, then that makes sense. Now, if you were. If you're paying a ton of money on that debt and you weren't gonna be able to earn that out in the return, then that wouldn't. So I understand that we probably have different ideas about what foundation shouldn't. How they should not use their money, and that's fine. But this particular solution to this problem, I think, is using the tools that are available now fairly well.
D
I just don't get foundations. Like, what. Why do people think these are these great storied institutions out there in the world doing good? Because you just scratch the surface and learn a little, and it becomes clear it's just like a big pile of money for very elite people to kind of sit on and pretend they're doing a lot of charity, but really they're not doing very much.
B
I mean, the reason that you invest, I mean, like, you.
D
What is the argument for these things?
B
So you have money and you invest the money so then that charity can continue in perpetuity and you can keep spending money on it.
D
But, like, the house is on fire now. Like, don't hoard the water.
B
And that's what they're doing with the.
C
Box, what they're doing with the bomb.
B
I mean, that's.
A
Kathy, come in here. We need the voice of reason.
C
I would just argue, to answer Emily's question, that the point of foundations, at least in theory, is, is not to make money. It's not like a pure money thing. The idea is to promote values. And the Ford foundation has a mission that is values driven. And they need the Money to promote them. But it's not about money. And that's the argument for why at a moment like this, they should go for it and borrow money and say, hey, we're going to take advantage. Because one of the Ford Foundation's things is racism. And I should, you know, full disclosure, the Ford foundation gave me a book party when my book part. When my book came out, because I was there at the intersection of racism and technology. And that's another one of their platforms. So I'm just making the point that the mission is not about money. We are sort of, it seems to me like we're making it overly, like, one dimensional by talking about the money aspect of the Ford Foundation. But the idea of foundations for good and for bad is to promote ideas and ideologies, not money. And that's why Ford foundation we might like, because we might agree with their mission. And then there's other foundations that we really, really hate because we disagree with their mission. Okay, but the thing I wanted to complain about, and I really only have one opinion because I haven't been following this very much, but I have been following the college stuff. A lot of is like, Harvard endowment. Sorry, we can't spend any money on any Covid related issues because our endowment is tied up at the moment. And it's like, that makes me kind of like, Emily, like, question the whole point of endowment. Like, aren't they supposed to be buffers for bad times? Like, what is going on with all these very rich colleges who are like, oh, we can't possibly hire people right now because Harvard has a hiring phase. Full disclosure, they were supposed to hire me and they didn't. But all the colleges are like, sorry, we can't do anything. And some of them are broke. It makes sense. But the ones that aren't broke are like, sorry, we can't use our endowment because they're all tied up in investments.
A
I think the big picture is exactly the same, which is that the people in charge of the endowments, they all have this point of view, which is that their job is to effectively protect the endowment at all costs. And Anna expresses this point of view very eloquently and explains why they have these arguments. They trot out on a regular basis explaining why, no, they can't spend their endowment. The whole point is the endowment has to go up, it can't go down. And the people who benefit from that ultimately are the people in charge of the endowment. And those people are invariably white, Darren Walker notwithstanding. And certainly the people who invest the money who are literally fiduciaries and putting that money into private equity and venture capital and hedge funds and all of that. All those money managers are largely rich and white and beneficiaries of systemic racism. And that disconnect, I think is much more glaring right now than it ever has been before.
B
I'll agree with that.
A
Okay, so let's have a numbers round. Emily, do you have a number?
D
I do. My number is 159,206. That is the dollar amount, the cost of one year at Columbia's master to a master's in data journalism. Can you just repeat again?
A
159,000 for a one year course in journalism.
D
Journalism, which is not a thriving industry, we can tell you.
A
And it's actually more.
D
I was like, oh, when I saw the number, I was like, oh, maybe It's. Well, it's 104,818 for tuition. And then they estimate living costs at $45,000.
C
Emily, which program is this?
D
Data Journalism Masters?
C
I asked because I actually started a data journalism program at Columbia, but it's not mine. It's not mine. Happy, but mine is probably almost as bad.
A
One of the big problems with this particular program is that it actually costs substantially more than if you just did a one year data science degree at Columbia, which would make you just as employable in journalism. I can assure you that all the people in journalism who want data science people are like, just give me the data science. I don't care if you have a little veneer of journalism added to your degree, but would also give you a whole bunch of options of managing to support yourself if you can't get a job in journalism, as is quite likely in the current environment.
D
Yeah, that's good advice. And also tuition prices like this for journalism perpetuate what we were talking about earlier, what Felix was what we were all saying that, you know, the price of entry. They hire people expecting them not to need the money, basically. And so this kind of.
C
I'll just say one thing about, about this since I am very well acquainted with the master's programs at Columbia.
D
Sorry.
C
Most of them are cash cows for Chinese kids of rich Chinese parents. And so what I find fascinating is like, what's going to happen with that entire industry? Do you know how much of higher education is paid for by Chinese parents? Like not just Colombia, but definitely Colombia. And I'm wondering if that's going to be. Is that over now that Covid. I don't know, but maybe the immigration laws are changing. There's all sorts of moving parts right now and I'm really curious to see what's going to happen.
B
That's really interesting. I know Australia is having issues with that right now because the Chinese government is essentially telling Chinese students not to go to Australia and they're obviously massive percentage of students in Australian universities are Chinese.
A
Cathy, do you have a number?
C
I have a number which is three. And it's the number of the top five huge tech companies that have recently stopped selling facial recognition to cops. We were going to talk about this as a topic and we decided we didn't have time because we had so many topics this week. But I was like, we're going to talk about facial recognition. Somehow IBM, Microsoft and Amazon have all promised to stop selling facial recognition to police for at least a year. I think Amazon, just a year and the rest may be forever. I think this is a good thing. I think in fact, we simply shouldn't use facial recognition at all in high stakes situations until we have a better understanding of what the rules are. I went to a congressional committee meeting about this a while ago and it was really moving. And one of the people that was testifying to Congress was a police chief who was begging Congress to set rules around its use because he was basically like, yes, do we use them? Do we use facial recognition? Absolutely. Because these vendors are coming around to us promising that they're perfect and wonderful and we don't know better and we don't know what the rules are. So every police department that uses it is using it differently and it's not okay. So it's a really big deal that the vendors themselves are clamping down on it, but we need the federal government. I mean, I say that not holding my breath, but we need actual guidance.
A
So a technical question, which I don't know if you can answer or not, are these SaaS contracts where they can say, oh yeah, we aren't selling you this anymore, so your contract for facial recognition is no longer active and you can't use it? Or are they just saying, we're not going to sell new contracts to new customers?
C
That's a really good question. I don't know. I mean, I'm not a lawyer, I'm not a contract lawyer, but if it were a contact lawyer working for one of the big tech companies, there would have been a clause about this.
A
My number is 1 billion, which is the number of dollars that Hertz wants to try to raise on the stock market, which is my favorite story of the week. And I love this so much. Hertz of course, is in bankruptcy. The value of the stock is going to go to zero. The equity will be wiped out. There's really no doubt about that. But what that has meant is that it has turned the stock into this gambling vehicle for the WallStreetBets crowd. And there's all manner of crazy stuff. People buying, people selling, people shorting options, the whole thing, which it's like the perfect vehicle for that because there's no value there. So it's just a bet on what other people are going to buy and sell but itself. And it's literally a vehicle. It's cars. Hertz itself is looking at this and saying, hey, our stock is trading at like 2, 3, 4, $5 a share. We need a lot of money because we're insolvent. So we should just sell a bunch of stock since it's going to zero anyway. No one's going to care about being diluted. We'll just sell a bunch of stock and give it to the creditors. I love this story so much.
B
No, for Hertz, I'm like, dude, why wouldn't you? It's like if you have to get dip financing, then you have all these covenants and things you can do and can't do. Just sell stock to idiots. That's a much better plan. That seems like my number is $200 million. So this is a number that comes from an article about one of a recurring character on Slate Money, Joe Low, an article that none of us could make heads or tails of, which is why we didn't talk about it on the show. But what I seem to have somewhat figured out is that it appears that Joe Low, involved in the 1MDB scandal with Malaysia and Goldman Sachs, was basically able to, through these kind of Kuwaiti banks and companies, launder money from China that he then used to pay off his legal bills related to what he did in Malaysia, which is just one more example of Jho Low being a real figure for our time. Representative figure for our time.
A
So Bradley Hope, who wrote the book about the Billion Dollar Whale book we had him on, is an excellent book and makes much more sense than this article has a new book out about Mohammed Bin Sultan. And so maybe we should try and get him on or something and we can ambush him with some more Jho Low questions. Can you explain this? Because we couldn't make it. But I think that's it for us this week. Unless you are, and if you are, thank you very much, a Slate plus member, we are going to talk about. Kathy, what's the Sleep plus topic.
C
I think it's an orgasm algorithm.
A
Orgasms.
C
Yes.
A
We are going to talk about orgasms.
C
And I'm going to use my sultry.
A
Voice if that's okay with me, whether we can monetize orgasms. This is going to be a very special Cathy o' Neill easter egg for those fans who have you said you.
C
Couldn'T remember last time I was here? I'll remind you that it was last time there was a technology sex toy.
B
On the market that I needed to.
C
Talk about on Slate Night. We can't have sex robots. Yes.
A
Sex robots. So, yeah, so this is, this is Kathy o' Neill's wheelhouse. Clearly we're going to talk about that on Slate plus, but otherwise, thank you for listening to Slate Money. We'll have another very, very special guest on next week, the one and only Stephanie Kelton. We have had so many requests via email, slatemoney.com from you guys to talk about Modern Monetary Theory, MMT, what it means. It is happening, people. Stephanie Kelton has a new book out. It's called the Deficit Myth. It's surprisingly readable. It is one of the most readable economics books I have come across in a very, very long time. So we are going to be talking to her about MMT and she can explain it all to us and we will understand. Thank you to Jessamy Molly for producing this glorious show and we will talk to you next week on Sleep Money.
This week, the Slate Money team—Felix Salmon, Anna Szymanski, and Emily Peck—are joined by returning guest Cathy O’Neil, mathematician and author, for a packed discussion on the pandemic’s data modeling, the credibility crisis in science, institutional reckonings on racism, and a charitable bombshell from the Ford Foundation. The episode moves deftly from technical to societal questions, tackling both the triumphs and failures of COVID-19 modeling, how structural inequalities drive pandemic outcomes, and whether recent high-profile resignations represent real change.
[00:46–11:55]
Initial Context: Cathy O’Neil shares a nuanced verdict on epidemiological models, noting that while "modelers have done pretty well," their warnings and caveats "were ignored" and that created a disastrous feedback loop with the public and media.
Assumptions Drive Outcomes: Early, dire death estimates (e.g., 2.2 million) reflected what would happen if behaviors didn't change. The models did provoke behavior change—which ironically made future models look wrong and eroded public trust.
It’s Not Over: O’Neil cautions against judging outcomes too early, highlighting that true evaluation must wait until "we have herd immunity" (vaccine or otherwise).
Muddled Messaging: The panel debates whether modelers or the media are to blame for public confusion, ultimately agreeing both shoulder responsibility. O’Neil proposes a focus on "R," or the virus reproduction number, rather than death tolls.
R and Measurement: Cathy clarifies commonly misunderstood terms:
Media and Simplification: The difficulty of communicating statistical uncertainty leads to public fatigue, misunderstanding, and even ammo for anti-science movements.
[11:55–17:16]
Comparative Success: Differences in COVID-19 trajectories worldwide are attributed to structural and cultural realities—autocracy (China), trust in government (Singapore, Germany, NZ, Sweden), or the lack of both (US).
Inequality and Racism: Cathy emphasizes that structural inequality and racism drive disproportionate pandemic impacts—outbreaks cluster in nursing homes, prisons, low-wage worker neighborhoods. This is mirrored in Singapore’s guest worker dorm outbreaks.
Policy and Politics: Emily Peck connects policies that deprioritized COVID response as soon as disparities became clear, especially impacting Black Americans.
Cynicism and Irresponsibility: Discussion turns to Trump’s rally plans, which require waivers from attendees, revealing an apparent disregard for his own supporters’ safety.
[17:19–30:21]
Rapid Resignations: As protests roil the country, corporate America—especially media and fashion—sees swift, high-profile resignations tied to racism: NYT’s op-ed head, Bon Appétit’s EIC, Refinery29’s founder, discussions about Anna Wintour (Vogue).
Systemic Problems: Real change, Anna and Emily argue, goes beyond ousting "bad apples." Media’s hiring practices, reliance on credentials and networks, and underpaying entry-level roles all sustain racial and class homogeneity.
Cause for Optimism? Trevor Noah’s rise after Jon Stewart and Alexis Ohanian stepping down from Reddit are cited as positive succession examples, but the consensus is that leadership changes alone won't solve systemic barriers.
Shifts in Public Attitudes: Felix highlights polling data showing "public opinion has changed faster on this issue than on virtually any other"—even those stepping down "are saying, yeah, I'm kind of racist. I shouldn't be here."
Persistence of Inequality in Power Sectors: Media changes are visible, but Emily wonders if finance and consulting will experience similar reckonings—or whether such industries are more resistant thanks to insidious, "hardwired" racism.
Meritocracy Myth: Anna points out the enduring myth that “the best person” will rise, while Cathy adds that U.S.-born Black Americans are dramatically underrepresented even relative to Black immigrants from Africa, which is also a reflection of educational privilege.
Algorithmic Hope: Despite her daily work uncovering "racism in algorithms," Cathy is "more hopeful than I was a month ago," suggesting anti-racist hiring algorithms are possible—if organizations commit to it.
[30:28–42:19]
Announcement Recap: Felix describes the Ford Foundation’s decision to issue bonds—rather than draw down its endowment—to increase current charity outflows during the crisis. He sharply criticizes the move as catering to money managers who "continue to look after 100% of our money."
Debate: Anna defends the approach as "how endowments work," protecting principal to ensure perpetual giving, while Emily decries the small 5% payout, calling it "kind of icky" that so little is disbursed yearly.
Timing and Conservatism: Felix argues foundations use market timing excuses to avoid spending, and that crises like this call for front-loading charity, especially since market values have rebounded.
Endowment Purpose: Cathy reframes the discussion, reminding that foundations’ missions are values-driven, not primarily about money, but agrees college endowments’ reluctance to support COVID responses "kind of makes me...question the whole point of endowment."
Systemic Self-Interest: Felix concludes that the people benefiting from massive, ever-growing endowments are those managing them—"invariably white...beneficiaries of systemic racism."
On COVID Modelers and the Public:
"People got so sick of hearing 2.2 million, no, 60,000, no, 500,000, no, 100,000..."
— Cathy O’Neil [04:06]
On Racism as a Causal Factor in Pandemics:
"I would claim that inequality and racism and mass incarceration are, in fact, causal factors for pandemics."
— Cathy O’Neil [14:18]
On the “New Normal” in Corporate Accountability:
"It's amazing...even the people who are stepping down, who are accused of being racist, are saying, yeah, I'm kind of racist. I shouldn't be here."
— Felix Salmon [24:27]
On Endowment Logic:
"But, like, the house is on fire now. Like, don't hoard the water."
— Emily Peck [38:47]
On Algorithmic Change:
"If we wanted to build anti-racist algorithms...this could actually help. But it would require us to just do it."
— Cathy O’Neil [30:09]
The conversation is lively, skeptical, and at times irreverent, with honest disagreement and a throughline of pointed critique about institutional responses to crisis and justice. Cathy's technical clarity grounds the early pandemic modeling discussion, while Felix often brings an acerbic, witty framing to financial topics. Emily’s and Anna’s contributions deepen the analysis on both gender and equity issues.
This summary captures the rich, multidisciplinary conversation and is a resource for listeners seeking to quickly absorb the episode’s key arguments, stories, and moments.