Astral Codex Ten

Uber

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Uber

Article

Uber is a recurring brand in the Astral Codex Ten archive, appearing 8 times across 8 issues between August 30, 2021 and February 05, 2026. The archive places it in contexts such as “Uber infamously had a team of behavioral economists working on its product”; “mumbling thanks to your Uber driver”; “Proposition 22 (make it hard for Uber and Lyft to do gig employment)“. It most often appears alongside OpenAI, Twitter, effective altruism.

Metadata

  • Category: Brands
  • Mention count: 8
  • Issue count: 8
  • First seen: August 30, 2021
  • Last seen: February 05, 2026

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

On Hreha On Behavioral Economics
August 30, 2021 · Original source
And every time I order food from UberEats, I get a menu like this:
I find I usually click the third box on both. I want to tip generously, but giving the maximum possible tip seems profligate. Surely the third box is the right compromise. I recently noticed that this is insane. For a $35 meal, I’m giving GrubHub drivers $3 and UberEats drivers $7 for the same service (or maybe there’s some difference between their services which makes UberEats suggest the higher tip - but if there is, I don’t know about it and it doesn’t affect my decision). Again, this is Behavioral Economics 101 - in particular, one of the many biases lumped together under menu effects. Instead of being a rational economic actor who values food delivery at a certain price, I’m trying to be a third-box-of-four kind of guy. That means that whoever is in charge of this menu has lots of power over the specific dollar amount I give. Not infinite power - if the third box said $1000 I would notice and refuse. But enough power that “nudging” seems like a fair description. Nobody believes studies anymore, which is fair. I trust in a salvageable core of behavioral economics and “nudgenomics” because I can feel in my bones that they’re true for me and the people around me. Let’s move on to Hreha’s article and see if we can square it with my belief in a “salvageable core”. II. Yechaim’s Historical Detective Story Hreha writes: The biggest replication failures relate to the field's most important idea: loss aversion. To be honest, this was a finding that I lost faith in well before the most recent revelations (from 2018-2020). Why? Because I've run studies looking at its impact in the real world—especially in marketing campaigns. If you read anything about this body of research, you'll get the idea that losses are such powerful motivators that they'll turn otherwise uninterested customers into enthusiastic purchasers. The truth of the matter is that losses and benefits are equally effective in driving conversion. In fact, in many circumstances, losses are actually *worse* at driving results. Why? Because loss-focused messaging often comes across as gimmicky and spammy. It makes you, the advertiser, look desperate. It makes you seem untrustworthy, and trust is the foundation of sales, conversion, and retention. "So is loss aversion completely bogus?" Not quite. It turns out that loss aversion does exist, but only for large losses. This makes sense. We *should* be particularly wary of decisions that can wipe us out. That's not a so-called "cognitive bias". It's not irrational. In fact, it's completely sensical. If a decision can destroy you and/or your family, it's sane to be cautious. "So when did we discover that loss aversion exists only for large losses?" Well, actually, it looks like Kahneman and Tversky, winners of the Nobel Prize in Economics, knew about this unfortunate fact when they were developing Prospect Theory—their grand theory with loss aversion at its center. Unfortunately, the findings rebutting their view of loss aversion were carefully omitted from their papers, and other findings that went against their model were misrepresented so that they would instead support their pet theory. In short: any data that didn't fit Prospect Theory was dismissed or distorted. I don't know what you'd call this behavior... but it's not science. This shady behavior by the two titans of the field was brought to light in a paper published in 2018: "Acceptable Losses: The Debatable Origins of Loss Aversion". I encourage you to read the paper. It's shocking. This line from the abstract sums things up pretty well: "...the early studies of utility functions have shown that while very large losses are overweighted, smaller losses are often not. In addition, the findings of some of these studies have been systematically misrepresented to reflect loss aversion, though they did not find it." When the two biggest scientists in your field are accused of "systemic misrepresentation", you know you've got a serious problem. Which leads us to another paper, published in 2018, entitled "The Loss of Loss Aversion: Will It Loom Larger Than Its Gain?". The paper's authors did a comprehensive review of the loss aversion literature and came to the following conclusion: "current evidence does not support that losses, on balance, tend to be any more impactful than gains." Yikes. But given the questionable origins of the field, it's not surprising that its foundational finding is *also* dubious. If loss aversion can't be trusted, then no other idea in the field can be trusted. This argument relies on two papers - Yechaim’s Acceptable Losses and Gal & Rucker’s Loss Of Loss Aversion. Yechaim’s paper is a historical detective story. It looks at how Kahneman and Tversky first “discovered” and popularized the idea of loss aversion from earlier 1950s and 1960s research. It concludes they did a bad job summarizing this earlier research; looked at carefully, it doesn’t support the strong conclusions they drew. From one perspective, nobody should care about this. All the 1950s and 1960s research was terrible - one of the most important studies it discusses had n = 7. Since then, we’ve had much more rigorous studies of tens of thousands of people. All that hinges on Yechaim’s paper is whether Kahneman and Tversky were personally bad people. Hreha thinks they were. He calls their behavior “shady”, “shocking”, and says they “systematically misrepresented findings to support their pet theory…I don't know what you'd call this behavior... but it's not science.” Again, nothing important really hinges on this, but I feel like fighting about it, so let’s look deeper anyway. Here’s how Yechaim summarizes his accusation against K&T: In addition, the results of several studies seem to have been misrepresented by Fishburn and Kochenberger (1979) and Kahneman and Tversky (1979). Galenter and Pliner (1974) were wrongly cited as showing loss aversion, whereas, in fact, they did not observe an asymmetry in the pleasantness ratings of gains and losses. Likewise, in Green (1963), the results were argued to show loss aversion, even though this study did not involve any losses. In addition, the objective outcomes for some of the participants in Grayson (1960) were transformed by Fishburn and Kochenberger (1979) so as to better support a model assuming different curvatures for gains and losses (see Table 1). Finally, studies showing no loss aversion or suggesting aversion to large losses were not cited in Fishburn and Kochenberger (1979) or in Kahneman and Tversky (1979). Yechaim bases his argument on three sets of early studies of loss aversion: Galenter and Plinter (1974), Fishburn and Kochenberger’s review (1979) and miscellaneous others. —Galenter and Plinter— is actually really neat! It explores “cross-modal” perceptions of gains versus losses. That is, if you ask how much a certain loss hurt, people will probably just say something like “I dunno, a little?” and then it will be hard to turn that into a p-value. G&P solve this by making people listen to loud noises, and asking questions like “is the difference between how much loss A and loss B hurt greater or lesser than the difference between the volume of noise 1 and noise 2?” The idea is that the brain uses a bunch of weird non-numerical scales for everything, and we understand its weird-non-numerical scale for noise volume pretty well, and so maybe we can compare it to how people think about gains or losses. I don’t know why people in 1974 were doing anything this complicated instead of inventing the basic theory of loss aversion the way Kahneman and Tversky would five years later, but here we are. Anyway, Yechaim concludes that this study failed to find loss aversion: Summing up their findings, Galenter and Pliner (1974) reported as follows: “We now turn to the question of the possible asymmetry of the positive and negative limbs of the utility function. On the basis of intuition and anecdote, one would expect the negative limb of the utility function to decrease more sharply than the positive limb increases... what we have observed if anything is an asymmetry of much less magnitude than would have been expected ... the curvature of the function does not change in going from positive to negative” (p. 75). Thus, our search for the historical foundations of loss aversion turns into a dead end on this particular branch: Galenter and Pliner (1974) did not observe such an asymmetry; and their study was quoted erroneously [by Kahneman and Tversky]. I looked for the full text of Galenter and Pliner, but could not find it. I was however able to find the first two pages, including the abstract. The way Galenter and Pliner summarize their own research is: Cross-modality matching of hypothetical increments of money against loudness recover the previously proposed exponent of the utility function for money within a few percent. Similar cross-modality matching experiments for decrements give a disutility exponent of 0.59, larger than the utility exponent for increments. This disutility exponent was checked by an additional cross-modality matching experiment against the disutility of drinking various concentrations of a bitter solution. The parameter estimated in this fashion was 0.63. If I understand the bolded part right, the abstract seems to be saying that they did find loss aversion! I was also able to find the Google Books listing for the book that the study was published in. Its summary is: Three experiments were conducted in which monetary increments and decrements were matched to either the loudness of a tone or the bitterness of various concentrations of sucrose octa-acetate. An additional experiment involving ratio estimates of monetary loss is also reported. Results confirm that the utility function for both monetary increments and decrements is a power function with exponents less than one. The data further suggest that the exponent of the disutility function is larger than that of the utility function, i.e., the rate of change of 'unhappiness' caused by monetary losses is greater than the comparable rate of 'happiness' produced by monetary gains. (Author). Again, the way the book is summarized (apparently by the author) says this study does prove loss aversion. Without being able to access the full study, I’m not sure what’s going on. Possibly the study found loss aversion, but it was less than expected? Still, I feel like Yechaim should have mentioned this. At the very least, it decreases Kahneman and Tversky’s crime from “lied about a study to support their pet theory” to “credulously believed the authors’ own summary of their results and didn’t dig deeper”. But also, why did the authors believe their study showed loss aversion? Why does Yechaim disagree? Without being able to access the full paper, I’m not sure. —Green 1963— is the second study that Yechaim accuses K&T of misrepresenting. Here’s how K&T cite this study in their paper: It is of interest that the main properties ascribed to the value function have been observed in a detailed analysis of von Neumann-Morgenstern utility functions for changes of wealth (Fishburn and Kochenberger [14]). The functions had been obtained from thirty decision makers in various fields of business, in five independent studies [5, 18, 19, 21, 40]. Most utility functions for gains were concave, most functions for losses were convex, and only three individuals exhibited risk aversion for both gains and losses. With a single exception, utility functions were considerably steeper for losses than for gains. Green 1963 is footnote 19. So K&T don’t even mention it by name. They mention it as one of several studies that a review article called Fishburn and Kochenberger analyzes. F&K are reviewing a bunch of studies of executives. In each study, a very small number of executives (usually about 5-10 per study) make a hypothetical business decision comparing gains and losses, for example: Suppose your company is being sued for patent infringement. Your lawyer’s best judgement is that your chances of winning the suit are 50–50; if you win, you will lose nothing, but if you lose, it will cost the company $1,000,000. Your opponent has offered to settle out of court for $200,000. Would you fight or settle? Then they ask the same question with a bunch of other numbers, and plot implied utility functions for each executive based on the answer. Green is one of these five studies, and it does superficially find loss aversion. But Fishburn and Kochenberger have done something weird. They argue that “loss” and “gain” aren’t necessarily objective, and usually correspond to “loss relative to some reference frame” (so far, so good). In order to figure out where the reference frame is, they assume that the neutral point is wherever “something unusual happens to the individual’s utility function” (F&K’s words). So they shift the zero point separating losses and gains to wherever the utility function looks most interesting! After doing this, they find “loss aversion”, ie the utility curve changes its slope at the transition between the loss side and the gain side. But since the transition was deliberately shifted to wherever the utility curve changed slope, this is almost tautological. It isn’t quite tautological: it’s interesting that most of the utility curves had a sharp transition zone, and it’s interesting that the transition was in the direction of loss-aversion rather than gain-seeking. But it’s tautological enough to be embarrassing. Still, this is Fishburn and Kochenberger’s embarrassment, not Kahneman and Tversky’s. And Fishburn and Kochenberger included this study in their review alongside several other studies that didn’t do this to the same degree. Kahneman and Tversky just cited the review article. I don’t think citing a review article that does weird things to a study really qualifies as “systematic misrepresentation.” I guess I’m having a hard time figuring out how angry to be, because everything about Fishburn and Kochenberger is terrible. The average study in F&K includes results from 5-10 executives. But the studies are pretty open about the fact that they interviewed more executives than this, threw away the ones who gave boring answers, and just published results from the interesting ones. Then they moved the axes to wherever looked most interesting. Then they used all this to draw sweeping generalizations about human behavior. Then F&K combined five studies that did this into a review article, without protesting any of it. And then K&T cited the review article, again without protesting. I have to imagine that all of this was normal by the standards of the time. I have looked up all these people and they were all esteemed scientists in their own day. And I believe the evidence shows K&T summarized F&K faithfully. Shouldn’t they have avoided citing F&K at all? Seems like the same kind of question as “Shouldn’t Pythagoras have published his theorem in a peer-reviewed journal, instead of moving to Italy, starting a cult, and exposing his thigh at the Olympic Games as part of a scheme to convince people he was the god Apollo?” Yes, but the past was a weird place. As best I can tell, K&T’s citation of G&P agrees with the authors’ own assessment of their results. Their citation of F&K agrees with the reviewers’ assessment and with a charitable reading of most of the studies involved, although those studies are terrible in many ways which are obvious to modern readers. I would urge people interested in the whodunit question to read Kahneman and Tversky’s original paper. I think it paints the picture of a team very interested in their own results and in theory, and citing other people only incidentally, and in accordance with the scientific standards of their time. I don’t feel a need to tar them as “misrepresenters”. III. Okay, But Is Loss Aversion Real? Remember, all that is about the personal deficiencies of Kahneman and Tversky. Realistically there have been hundreds of much better studies on loss aversion in the forty years since they wrote their article, so we should be looking at those. Here Hreha cites Gal & Rucker: The Loss Of Loss Aversion: Will It Loom Larger Than Its Gain? It’s a great 2018 paper that looks at recent evidence and concludes that loss aversion doesn’t exist. But it’s a very specific, interesting type of nonexistence, which I think the Hreha article fails to capture. G&R are happy to admit that in many, many cases, people behave in loss-averse ways, including most of the classic examples given by Kahneman and Tversky. They just think that this is because of other cognitive biases, not a specific cognitive bias called “loss aversion”. They especially emphasize Status Quo Bias and the Endowment Effect. Status Quo Bias is where you prefer inaction to action. Suppose you ask someone “Would you bet on a coin flip, where you get $60 if heads and lose $40 if tails?”. They say no. This deviates from rational expectations, and one way to think of this is loss aversion; the prospect of losing $40 feels “bigger” than the prospect of gaining $60. But another way to think of it is as a bias towards inaction - all else being equal, people prefer not to make bets, and you’d need a higher payoff to overcome their inertia. Endowment Effect is where you value something you already have more than something you don’t. Suppose someone would pay $5 to prevent their coffee mug from being taken away from them, but (in an alternative universe where they lack a coffee mug) would only pay $3 to buy one. You can think of this as loss aversion (the grief of losing a coffee mug feels “bigger” than the joy of gaining one). Or you can think of it as endowment (once you have the coffee mug, it’s yours and you feel like defending it). These are really fine distinctions; I had to read the section a few times before the difference between loss aversion and endowment effect really made sense to me. Kahneman and Tversky just sort of threw all all this stuff out and saw what stuck and didn’t necessarily try super hard to make sure none of the biases they discovered were entirely explainable as combinations of some of the others. G&R think maybe loss aversion is. They do some clever work setting up situations that test loss aversion but not status quo or endowment - for example, offering a risky bet vs. a safer bet. Here they find no evidence for loss aversion as a separate force from the other two biases. Somewhere in this process, they did an experiment where they gave participants a quarter minted in Denver and asked them if they wanted to exchange it for a quarter minted in Philadelphia. 60% of people very reasonably didn’t care, but another 35% had grown attached to their Denver quarter, with only 5% actively seeking the novelty of Philadelphia. Psychology is weird. I understand why some people would summarize this paper as “loss aversion doesn’t exist”. But it’s very different from “power posing doesn’t exist” or “stereotype threat doesn’t exist”, where it was found that the effect people were trying to study just didn’t happen, and all the studies saying it did were because of p-hacking or publication bias or something. People are very often averse to losses. This paper just argues that this isn’t caused by a specific “loss aversion” force. It’s caused by other forces which are not exactly loss aversion. We could compare it to centrifugal force in physics: real, but not fundamental. Also, you can’t use this paper to argue that “behavioral economics is dead”. At best, the paper proves that loss aversion is better explained by other behavioral economic concepts. But you can’t get rid of behavioral econ entirely! The stuff you have to explain is still there! It’s just a question of which parts of behavioral econ you use to explain it. Complicating this even further is Mrkva et al, Loss Aversion Has Moderators, But Reports Of Its Death Are Greatly Exaggerated (h/t Alex Imas, who has a great Twitter thread about this). This is an even newer paper, 2019, which argues that Gal and Rucker are wrong, and loss aversion does have an independent existence as a real force. There are many things to like about this paper. Previous criticisms of loss aversion argue that most experiments are performed on undergrads, who are so poor that even small amounts of money might have unusual emotional meaning. Mrkva collects a sample of thousands of millionaires (!) and demonstrates that they show loss aversion for sums of money as small as $20. On the other hand, I’m not sure they’re quite as careful as G&R at ruling out every other possible bias (although I don’t have a great understanding of where the borders between biases are and I can’t say this for sure). The main point I want to make is that all the scientists in this debate seem smart, thoughtful, and impressive. This isn’t like social priming experiments where one person says a crazy thing, nobody ever replicates it at scale, and as soon as someone tries the whole thing collapses. These have been replicated hundreds of times, with the remaining arguments being complicated semantic and philosophical ones about how to distinguish one theory from a very slightly different theory. If that takes replicating your result on a sample of thousands of millionaires, people will gather a sample of thousands of millionaires and get busy on the replication. Just overall really impressive work. I don’t feel qualified to take a side in the G&R vs. Mkrva debate, but both teams make me really happy that there are smart and careful people considering these questions. And this is just a drop in the bucket. Alex Imas also links Replicating patterns of prospect theory for decision under risk, which says: Though substantial evidence supports prospect theory, many presumed canonical theories have drawn scrutiny for recent replication failures. In response, we directly test the original methods in a multinational study (n = 4,098 participants, 19 countries, 13 languages), adjusting only for current and local currencies while requiring all participants to respond to all items. The results replicated for 94% of items, with some attenuation. Twelve of 13 theoretical contrasts replicated, with 100% replication in some countries. Heterogeneity between countries and intra-individual variation highlight meaningful avenues for future theorizing and applications. We conclude that the empirical foundations for prospect theory replicate beyond any reasonable thresholds. Beyond any reasonable thresholds! IV. Do Nudges Work? or, How Small Is Small? Continuing through the Hreha article: For a number of years, I've been beating the anti-nudge drum. Since 2011, I've been running behavioral experiments in the wild, and have always been struck by how weak nudges tend to be. In my experience, nudges usually fail to have *any* recognizable impact at all. This is supported by a paper that was recently published by a couple of researchers from UC Berkeley. They looked at the results of 126 randomized controlled trials run by two "nudge units" here in the United States. I want you to guess how large of an impact these nudges had on average... 30%? 20%? 10%? 5%? 3%? 1.5%? 1%? 0%? If you said 1.5%, you'd be right (the actual number is 1.4%, but if I had written that out you would have chosen it because of its specificity). According to the academic papers these nudges were based upon, these nudges should have had an average impact of 8.7%. But, as you probably understand by now, behavioral economics is not a particularly trustworthy field. I actually emailed the authors of this paper, and they thought the ~1% effect size of these interventions was something to be applauded—especially if the intervention was cheap & easy. Unfortunately, no intervention is truly cheap or easy. Every single intervention requires, at the very minimum, administrative overhead. If you're going to do something, you need someone (or some system) to implement and keep track of it. If an intervention is only going to get you a 1% improvement, it's probably not even worth it. Uber infamously had a team of behavioral economists working on its product, trying to “nudge” people in the right direction. Relatedly, Uber makes $10 billion in yearly revenue. If they can “nudge” people to spend 1% more, that’s $100 million. That’s not much relative to revenue, but it’s a lot in absolute terms. In particular, it pays the salary of a lot of behavioral economists. If you can hire 10 behavioral economists for $100,000 a year and make $100 million, that’s $99 million in profit. Or what if you’re a government agency, trying to nudge people to do prosocial things? There are about 90 million eligible Americans who haven’t gotten their COVID vaccine, and although some of them are hard-core conspiracy theorists, others are just lazy or nervous or feel safe already. (source) Whoever decided on that grocery gift card scheme was nudging, whether or not they have an economics degree - and apparently they were pretty good at it. If some sort of behavioral econ campaign can convince 1.5% of those 90 million Americans to get their vaccines, that’s 1.4 million more vaccinations and, under reasonable assumptions, maybe a few thousand lives saved. Hreha says that: Every single intervention requires, at the very minimum, administrative overhead. If you're going to do something, you need someone (or some system) to implement and keep track of it. If an intervention is only going to get you a 1% improvement, it's probably not even worth it. This depends on scale! 1% of a small number isn’t worth it! 1% of a big number is very worth it, especially if that big number is a number of lives! A few caveats. First, a small number only matters if it’s real. It’s very easy to get spurious small effects, so much so that any time you see a small effect you should wonder if it’s real. I’m ready to be forgiving here because behavioral economics is so well-replicated and common-sensically true, but I wouldn’t blame anyone who steers clear. Second, Hreha says: To be honest, you can probably use your creativity to brainstorm an idea that will get you a 3-4% minimum gain, no behavioral economics "science" required. Which leads me to the final point I'd like to make: rules and generalizations are overrated. The reason that fields like behavioral economics are so seductive is because they promise people easy, cookie-cutter solutions to complicated problems. Figuring out how to increase sales of your product is hard. You need to figure out which variables are responsible for the lackluster interest. Is the price the issue? Is the product too hard to use? Is the design tacky? Is the sales organization incompetent? Is the refund/return policy lacking? etc. Exploring these questions can take months (or years) of hard work, and there's no guarantee that you'll succeed. If, however, a behavioral economist tells you that there are nudges that will increase your sales by 10%, 20%, or 30% without much effort on your part... Whoa. That's pretty cool. It's salvation. Thus, it's no surprise that governments and companies have spent hundreds of millions of dollars on behavioral "nudge" units. Unfortunately, as we've seen, these nudges are woefully ineffective. Specific problems require specific solutions. They don't require boilerplate solutions based on general principles that someone discovered by studying a bunch of 19 year old college students. However, the social sciences have done a good job of convincing people that general principles are better solutions for problems than creative, situation-specific solutions. In my experience, creative solutions that are tailor-made for the situation at hand *always* perform better than generic solutions based on one study or another. Hreha is a professional in this field, so presumably he’s right. Still, compare to medicine. A thoughtful doctor who tailors treatment to a particular patient sounds better (and is better) than one who says “Depression? Take this one all-purpose depression treatment which is the first thing I saw when I typed ‘depression’ into UpToDate”. But you still need medical journals. Having some idea of general-purpose laws is what gives the people making creative solutions something to build upon. (also, at some point your customers might want to check your creative solution to see whether it actually gives a “3-4% minimum gain, no behavioral economics required”, and that would be at least vaguely study-shaped.) Third, everyone who said nudging had vast effects is still bad and wrong. Many of them were bad and wrong and making fortunes consulting for companies about how to implement the policies they were claiming were super-powerful. This is suspicious and we should lower our opinion of them accordingly. In a previous discussion of growth mindset, I wrote: Imagine I claimed our next-door neighbor was a billionaire oil sheik who kept thousands of boxes of gold and diamonds hidden in his basement. Later we meet the neighbor, and he is the manager of a small bookstore and has a salary 10% above the US average... Should we describe this as “we have confirmed the Wealthy Neighbor Hypothesis, though the effect size was smaller than expected”? Or as “I made up a completely crazy story, and in unrelated news there was an irrelevant deviation from literally-zero in the same space”? All the people talking about oil sheiks deserve to get asked some really uncomfortable questions. And a lot of these will be the most famous researchers - the Dan Arielys of the world - because of course the people who successfully hyped their results a lot are the ones the public knows about. Still, the neighbor seems like a neat guy, and maybe he’ll give you a job at his bookstore. V. Conclusion: Musings On The Identifiable Victim Effect I actually skipped the very beginning of Hreha’s article. I want to come back to it now. It begins: The last few years have been particularly bad for behavioral economics. A number of frequently cited findings have failed to replicate. Here are a couple of high profile examples: The Identifiable Victim Effect (featured in the workbooks I wrote with Dan Ariely and Kristen Berman in 2014)
Inline links: menu effects, Acceptable Losses: The Debatable Origins of Loss Aversion, The Loss of Loss Aversion: Will It Loom Larger Than Its Gain?, Acceptable Losses, Loss Of Loss Aversion, the first two pages, https://substackcdn.com/image/fetch/$s_!W80n!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F7f832933-e9a1-4cf2-ba32-e4bc11ce681c_830x624.png, Kahneman and Tversky’s original paper, https://substackcdn.com/image/fetch/$s_!2VLm!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F8c49b44a-8850-4ac8-9a88-3dd07718a648_397x305.png, Loss Aversion Has Moderators, But Reports Of Its Death Are Greatly Exaggerated, Alex Imas, Replicating patterns of prospect theory for decision under risk, They looked at the results of 126 randomized controlled trials, others, https://substackcdn.com/image/fetch/$s_!1gY_!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F5b127d7c-045a-4266-b515-a0e9201ce651_571x382.png, a previous discussion of growth mindset, the workbooks I wrote with Dan Ariely and Kristen Berman in 2014
Somewhere in this process, they did an experiment where they gave participants a quarter minted in Denver and asked them if they wanted to exchange it for a quarter minted in Philadelphia. 60% of people very reasonably didn’t care, but another 35% had grown attached to their Denver quarter, with only 5% actively seeking the novelty of Philadelphia. Psychology is weird. I understand why some people would summarize this paper as “loss aversion doesn’t exist”. But it’s very different from “power posing doesn’t exist” or “stereotype threat doesn’t exist”, where it was found that the effect people were trying to study just didn’t happen, and all the studies saying it did were because of p-hacking or publication bias or something. People are very often averse to losses. This paper just argues that this isn’t caused by a specific “loss aversion” force. It’s caused by other forces which are not exactly loss aversion. We could compare it to centrifugal force in physics: real, but not fundamental. Also, you can’t use this paper to argue that “behavioral economics is dead”. At best, the paper proves that loss aversion is better explained by other behavioral economic concepts. But you can’t get rid of behavioral econ entirely! The stuff you have to explain is still there! It’s just a question of which parts of behavioral econ you use to explain it. Complicating this even further is Mrkva et al, Loss Aversion Has Moderators, But Reports Of Its Death Are Greatly Exaggerated (h/t Alex Imas, who has a great Twitter thread about this). This is an even newer paper, 2019, which argues that Gal and Rucker are wrong, and loss aversion does have an independent existence as a real force. There are many things to like about this paper. Previous criticisms of loss aversion argue that most experiments are performed on undergrads, who are so poor that even small amounts of money might have unusual emotional meaning. Mrkva collects a sample of thousands of millionaires (!) and demonstrates that they show loss aversion for sums of money as small as $20. On the other hand, I’m not sure they’re quite as careful as G&R at ruling out every other possible bias (although I don’t have a great understanding of where the borders between biases are and I can’t say this for sure). The main point I want to make is that all the scientists in this debate seem smart, thoughtful, and impressive. This isn’t like social priming experiments where one person says a crazy thing, nobody ever replicates it at scale, and as soon as someone tries the whole thing collapses. These have been replicated hundreds of times, with the remaining arguments being complicated semantic and philosophical ones about how to distinguish one theory from a very slightly different theory. If that takes replicating your result on a sample of thousands of millionaires, people will gather a sample of thousands of millionaires and get busy on the replication. Just overall really impressive work. I don’t feel qualified to take a side in the G&R vs. Mkrva debate, but both teams make me really happy that there are smart and careful people considering these questions. And this is just a drop in the bucket. Alex Imas also links Replicating patterns of prospect theory for decision under risk, which says: Though substantial evidence supports prospect theory, many presumed canonical theories have drawn scrutiny for recent replication failures. In response, we directly test the original methods in a multinational study (n = 4,098 participants, 19 countries, 13 languages), adjusting only for current and local currencies while requiring all participants to respond to all items. The results replicated for 94% of items, with some attenuation. Twelve of 13 theoretical contrasts replicated, with 100% replication in some countries. Heterogeneity between countries and intra-individual variation highlight meaningful avenues for future theorizing and applications. We conclude that the empirical foundations for prospect theory replicate beyond any reasonable thresholds. Beyond any reasonable thresholds! IV. Do Nudges Work? or, How Small Is Small? Continuing through the Hreha article: For a number of years, I've been beating the anti-nudge drum. Since 2011, I've been running behavioral experiments in the wild, and have always been struck by how weak nudges tend to be. In my experience, nudges usually fail to have *any* recognizable impact at all. This is supported by a paper that was recently published by a couple of researchers from UC Berkeley. They looked at the results of 126 randomized controlled trials run by two "nudge units" here in the United States. I want you to guess how large of an impact these nudges had on average... 30%? 20%? 10%? 5%? 3%? 1.5%? 1%? 0%? If you said 1.5%, you'd be right (the actual number is 1.4%, but if I had written that out you would have chosen it because of its specificity). According to the academic papers these nudges were based upon, these nudges should have had an average impact of 8.7%. But, as you probably understand by now, behavioral economics is not a particularly trustworthy field. I actually emailed the authors of this paper, and they thought the ~1% effect size of these interventions was something to be applauded—especially if the intervention was cheap & easy. Unfortunately, no intervention is truly cheap or easy. Every single intervention requires, at the very minimum, administrative overhead. If you're going to do something, you need someone (or some system) to implement and keep track of it. If an intervention is only going to get you a 1% improvement, it's probably not even worth it. Uber infamously had a team of behavioral economists working on its product, trying to “nudge” people in the right direction. Relatedly, Uber makes $10 billion in yearly revenue. If they can “nudge” people to spend 1% more, that’s $100 million. That’s not much relative to revenue, but it’s a lot in absolute terms. In particular, it pays the salary of a lot of behavioral economists. If you can hire 10 behavioral economists for $100,000 a year and make $100 million, that’s $99 million in profit. Or what if you’re a government agency, trying to nudge people to do prosocial things? There are about 90 million eligible Americans who haven’t gotten their COVID vaccine, and although some of them are hard-core conspiracy theorists, others are just lazy or nervous or feel safe already. (source) Whoever decided on that grocery gift card scheme was nudging, whether or not they have an economics degree - and apparently they were pretty good at it. If some sort of behavioral econ campaign can convince 1.5% of those 90 million Americans to get their vaccines, that’s 1.4 million more vaccinations and, under reasonable assumptions, maybe a few thousand lives saved. Hreha says that: Every single intervention requires, at the very minimum, administrative overhead. If you're going to do something, you need someone (or some system) to implement and keep track of it. If an intervention is only going to get you a 1% improvement, it's probably not even worth it. This depends on scale! 1% of a small number isn’t worth it! 1% of a big number is very worth it, especially if that big number is a number of lives! A few caveats. First, a small number only matters if it’s real. It’s very easy to get spurious small effects, so much so that any time you see a small effect you should wonder if it’s real. I’m ready to be forgiving here because behavioral economics is so well-replicated and common-sensically true, but I wouldn’t blame anyone who steers clear. Second, Hreha says: To be honest, you can probably use your creativity to brainstorm an idea that will get you a 3-4% minimum gain, no behavioral economics "science" required. Which leads me to the final point I'd like to make: rules and generalizations are overrated. The reason that fields like behavioral economics are so seductive is because they promise people easy, cookie-cutter solutions to complicated problems. Figuring out how to increase sales of your product is hard. You need to figure out which variables are responsible for the lackluster interest. Is the price the issue? Is the product too hard to use? Is the design tacky? Is the sales organization incompetent? Is the refund/return policy lacking? etc. Exploring these questions can take months (or years) of hard work, and there's no guarantee that you'll succeed. If, however, a behavioral economist tells you that there are nudges that will increase your sales by 10%, 20%, or 30% without much effort on your part... Whoa. That's pretty cool. It's salvation. Thus, it's no surprise that governments and companies have spent hundreds of millions of dollars on behavioral "nudge" units. Unfortunately, as we've seen, these nudges are woefully ineffective. Specific problems require specific solutions. They don't require boilerplate solutions based on general principles that someone discovered by studying a bunch of 19 year old college students. However, the social sciences have done a good job of convincing people that general principles are better solutions for problems than creative, situation-specific solutions. In my experience, creative solutions that are tailor-made for the situation at hand *always* perform better than generic solutions based on one study or another. Hreha is a professional in this field, so presumably he’s right. Still, compare to medicine. A thoughtful doctor who tailors treatment to a particular patient sounds better (and is better) than one who says “Depression? Take this one all-purpose depression treatment which is the first thing I saw when I typed ‘depression’ into UpToDate”. But you still need medical journals. Having some idea of general-purpose laws is what gives the people making creative solutions something to build upon. (also, at some point your customers might want to check your creative solution to see whether it actually gives a “3-4% minimum gain, no behavioral economics required”, and that would be at least vaguely study-shaped.) Third, everyone who said nudging had vast effects is still bad and wrong. Many of them were bad and wrong and making fortunes consulting for companies about how to implement the policies they were claiming were super-powerful. This is suspicious and we should lower our opinion of them accordingly. In a previous discussion of growth mindset, I wrote: Imagine I claimed our next-door neighbor was a billionaire oil sheik who kept thousands of boxes of gold and diamonds hidden in his basement. Later we meet the neighbor, and he is the manager of a small bookstore and has a salary 10% above the US average... Should we describe this as “we have confirmed the Wealthy Neighbor Hypothesis, though the effect size was smaller than expected”? Or as “I made up a completely crazy story, and in unrelated news there was an irrelevant deviation from literally-zero in the same space”? All the people talking about oil sheiks deserve to get asked some really uncomfortable questions. And a lot of these will be the most famous researchers - the Dan Arielys of the world - because of course the people who successfully hyped their results a lot are the ones the public knows about. Still, the neighbor seems like a neat guy, and maybe he’ll give you a job at his bookstore. V. Conclusion: Musings On The Identifiable Victim Effect I actually skipped the very beginning of Hreha’s article. I want to come back to it now. It begins: The last few years have been particularly bad for behavioral economics. A number of frequently cited findings have failed to replicate. Here are a couple of high profile examples: The Identifiable Victim Effect (featured in the workbooks I wrote with Dan Ariely and Kristen Berman in 2014)
Inline links: Loss Aversion Has Moderators, But Reports Of Its Death Are Greatly Exaggerated, Alex Imas, Replicating patterns of prospect theory for decision under risk, They looked at the results of 126 randomized controlled trials, others, https://substackcdn.com/image/fetch/$s_!1gY_!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F5b127d7c-045a-4266-b515-a0e9201ce651_571x382.png, a previous discussion of growth mindset, the workbooks I wrote with Dan Ariely and Kristen Berman in 2014
Another Bay Area House Party
October 19, 2022 · Original source
Blaise Pascal said all human evil comes from inability to sit alone in a room. Your better nature - your rational soul - tells you that nothing good has ever come from attending large social events. But against that better nature stands the Devil, wielding a stick marked “FOMO”. If you don’t go to social events, maybe other people will go and have great times and live fuller lives than you. “As the dog returns to its vomit, so returns the fool to his folly”, says the Bible. And so you find yourself mumbling thanks to your Uber driver and crossing the threshold of another Bay Area house party.
My California Ballot 2022
November 04, 2022 · Original source
Until now, Proposition 22 (make it hard for Uber and Lyft to do gig employment) was the most expensive proposition in California history. But it looks like Proposition 27 is going to beat 22 for this heavily-contested title. It lets out-of-state companies provide online sports betting in California if they bribe some Indian tribe that has gambling rights to say the Indian tribe supports them.
Inline links: Proposition 27 is going to beat 22
This got me thinking: I make fun of Gavin Newsom a lot. I say he has no characteristics except good hair and the ability to pander to every interest group the exact right amount. But Newsom is favored as the Democratic nominee in 2024 if Biden chooses not to run again. Why? Usually people who become a major party candidate for President have some positive quality that has helped them get that far. Donald Trump is a master showman and figured out how to tap a vein of populist anger no one else could. Joe Biden has folksy charm and 75,000 years of experience in the Senate. Hillary Clinton had stratospheric name recognition and the support of the Democrats’ best political machine. If Gavin Newsom becomes President, or even a nominee, to what will we attribute this? I have lived in his state for four years now and I am baffled. He is a mystery, a gaping void where a candidate statement and photo should be, certain of victory with no explanation.
Inline links: make fun of Gavin Newsom
Links For July 2023
July 06, 2023 · Original source
30: Claim: At the exact right time, when the stars align, a couple traveling NYC → Boston can get better prices with an Uber than an Amtrak. This has never been true when I’ve checked it (as I type this, it’s $650 by Uber vs. $320 by train), and some people report that most Uber drivers refuse to make a 4-hour drive no matter what the app says. Still, it’s funny that it ever works at all.
Inline links: can get better prices
Highlights From The Comments On Elon Musk
September 18, 2023 · Original source
The Boring Company Las Vegas system is tunnelling a ~14 ft diameter tunnel that can fit 1 lane of car traffic, and it's light on some safety features like ventilation, exit walkways, or fire suppression systems. It will use Tesla cars, driven by Tesla employees. In my view this is basically an underground Uber system, but it will probably have more expensive fares to regain the capital costs of building the tunnel (Boring Company is paying for the tunnels, and casinos are paying for the stations, they do NOT have funding from City of Las Vegas AFAIK). But this expensive Uber system is exciting??
My Left Kidney
October 27, 2023 · Original source
As I left the Uber, I saw with horror the growing wet spot around my crotch. “It’s not urine!”, I almost blurted to the driver, before considering that 1) this would just call attention to it and 2) it was urine. “It’s not my urine,” was my brain’s next proposal - but no, that was also false. “It is urine, and it is mine, but just because it’s pooling around my crotch doesn’t mean I peed myself; that’s just a coincidence!” That one would have been true, but by the time I thought of it he had driven away.
This isn’t controlling for selection bias - but neither was my uncle’s anecdotal observation. So although it does make me slightly nervous, I’m not going to treat it as actionable evidence. Still, my girlfriend ending up begging me not to donate, and I caved. But we broke up in 2019. The next few years were bumpy, but by 2022 my life was in a more stable place and I started thinking about kidneys again. By then I was married. I discussed the risks with my wife and she decided to let me go ahead. So in early November 2022, for the second time, I sent a form to the University of California San Francisco Medical Center saying I wanted to donate a kidney. IV. Something else happened that month. On November 11, FTX fell apart and was revealed as a giant scam. Suddenly everyone hated effective altruists. Publications that had been feting us a few months before pivoted to saying they knew we were evil all along. I practiced rehearsing the words “I have never donated to charity, and if I did, I certainly wouldn’t care whether it was effective or not”. But during the flurry of intakes, screenings, and evaluations that UCSF gave me that month, the doctors asked “so what made you want to donate?” And I hadn’t rehearsed an answer to this one, so I blurted out “Have you heard of effective altruism?” I expected the worst. But the usual response was “Oh! Those people! Great, no further explanation needed.” When everyone else abandoned us, the organ banks still thought of us as those nice people who were always giving them free kidneys. We were giving them a lot of free kidneys. When I talked to my family and non-EA friends about wanting to donate, the usual reaction was “You want to what?!” and then trying to convince me this was unfair to my wife or my potential future children or whatever. When I talked to my EA friends, the reaction was at least “Cool!”. But pretty often it was “Oh yeah, I donated two years ago, want to see my scar?” Most people don’t do interesting things unless they’re in a community where those things have been normalized. I was blessed with a community where this was so normal that I could read a Vox article about it and not vomit it back out. This is surprising, because kidney donation is only medium effective, as far as altruisms go4. The average donation buys the recipient about 5 - 7 extra years of life (beyond the counterfactual of dialysis). It also improves quality of life from about 70% of the healthy average to about 90%. Non-directed kidney donations can also help the organ bank solve allocation problems around matching donors and recipients of different blood types. Most sources say that an average donated kidney creates a “chain” of about five other donations, but most of these other donations would have happened anyway; the value over counterfactual is about 0.5 to 1 extra transplant completed before the intended recipient dies from waiting too long. So in total, a donation produces about 10 - 20 extra quality-adjusted life years. This is great - my grandfather died of kidney disease, and 10 - 20 more years with him would have meant a lot. But it only costs about $5,000 - $10,000 to produce this many QALYs through bog-standard effective altruist interventions, like buying mosquito nets for malarial regions in Africa. In a Philosophy 101 Thought Experiment sense, if you’re going to miss a lot of work recovering from your surgery, you might as well skip the surgery, do the work, and donate the extra money to Against Malaria Foundation instead5. Obviously this kind of thing is why everyone hates effective altruists. People got so mad at some British EAs who used donor money to “buy a castle”. I read the Brits’ arguments: they’d been running lots of conferences with policy-makers, researchers, etc; those conferences have gone really well and produced some of the systemic change everyone keeps wanting. But conference venues kept ripping them off, having a nice venue of their own would be cheaper in the long run, and after looking at many options, the “castle” was the cheapest. Their math checked out, and I believe them when they say this was the most effective use for that money. For their work, they got a million sneering thinkpieces on how “EA just takes people’s money to buy castles, then sit in them wearing crowns and waving scepters and laughing at poor people”. I respect the British organizers’ willingness to sacrifice their reputation on the altar of doing what was actually good instead of just good-looking. I worry that people use suffering as a heuristic for goodness. Mother Teresa becomes a hero because living with lepers in the Calcutta slums sounds horrible - so anyone who does it must be really charitable (regardless of whether or not the lepers get helped). Owning a castle is the opposite of suffering - it sounds great - therefore it is fake charity (no matter how much good you do with the castle). This heuristic isn’t terrible. If you’re suffering for your charity, then it must seem important to you, and you’re obviously not doing it for personal gain. If you do charity in a way that benefits you (like gets you a castle), then the personal gain aspect starts looking suspicious. The problem is the people who elevate it from a suspicion to an automatic condemnation. It seems like such a natural thing to do. And it encourages people to be masochists, sacrificing themselves pointlessly in photogenic ways, instead of thinking about what will actually help others. But getting back to the point: kidney donation has an unusually high ratio of photogenic suffering to altruistic gains. So why do EAs keep doing it? I can’t speak for anyone else, but I’ll speak for myself. It starts with wanting, just once, do a good thing that will make people like you more instead of less. It would be morally fraught to do this with money, since any money you spent on improving your self-image would be denied to the people in malarial regions of Africa who need it the most. But it’s not like there’s anything else you can do with that spare kidney. Still, it’s not just about that. All of this calculating and funging takes a psychic toll. Your brain uses the same emotional heuristics as everyone else’s. No matter how contrarian you pretend to be, deep down it’s hard to make your emotions track what you know is right and not what the rest of the world is telling you. The last Guardian opinion columnist who must be defeated is the Guardian opinion columnist inside your own heart. You want to do just one good thing that you’ll feel unreservedly good about, and where you know somebody’s going to be directly happy at the end of it in a way that doesn’t depend on a giant rickety tower of assumptions. Dylan Matthews wrote: As I’m no doubt the first person to notice, being an adult is hard. You are consistently faced with choices — about your career, about your friendships, about your romantic life, about your family — that have deep moral consequences, and even when you try the best you can, you’re going to get a lot of those choices wrong. And you more often than not won’t know if you got them wrong or right. Maybe you should’ve picked another job, where you could do more good. Maybe you should’ve gone to grad school. Maybe you shouldn’t have moved to a new city. So I was selfishly, deeply gratified to have made at least one choice in my life that I know beyond a shadow of a doubt was the right one. …and it really resonated. Everything else I try to do, there’s a little voice inside of me which says “Maybe the haters are right, maybe you’re stupid, maybe you’re just doing the easy things. Maybe you’re no good after all, maybe you’ll never be able to figure any of this out. Maybe you should just give up.” The Talmud is very clear: that voice is called the evil inclination, and it dwells in the left kidney. There is only one way to shut it off forever. I was ready. V. You might not be a masochist. But hospitals are sadists. They want to hear you beg. After I submitted the donation form, I was evaluated by a horde of indistinguishable women. They all had titles like “Transplant Coordinator”, “Financial Coordinator”, and “Patient Care Representative”. Several were social workers; one was a psychiatrist. They would see me through a buggy version of Zoom that caused various parts of their body to suddenly turn into the UCSF logo, and they all had questions like “Are you sure you want to do this?” and “Are you going to regret this later?” and “Is anyone pressuring you to do this?” and “Are you sure you want to do this?” After clearing that gauntlet came the tests. Blood tests - I think I must have given between 20 and 50 vials of blood throughout the screening process. Urine tests - both the normal kind where you pee in a cup, and a more involved kind where you have to store all your urine for 24 hours in a big jug, then take it to the lab. “Urinate into a jug” ought to be the easiest thing in the world, but some of the labs have overly complicated jugs that I, with my mere MD, couldn’t always get right - hence my experience accidentally pouring urine on myself in an Uber. Then came the big guns. Echocardiogram. MRI. One of my urine tests was slightly off, so I also got a nuclear kidney scan, where they injected radioactive liquid in me and monitored how long it took to come out the other end (I remember asking a friend “Can I use your bathroom? My urine might be slightly radioactive today, but it shouldn’t be enough to matter.”) Finally, five months after I originally applied, I got a phone call from the Transplant Coordinator. The test results were in, and . . . I had been rejected because I’d had mild childhood OCD. This was something I’d mentioned offhandedly during one of the psych evaluations. As a child, I used to touch objects in odd patterns that only made sense to me. I got diagnosed with OCD, put on SSRIs for a while, finally did therapy at age 15, hadn’t had any problems since. I still go back on SSRIs sometimes when I’m really stressed, and will grudgingly admit to the occasional odd-pattern-touching when no one’s looking. But it’s nothing anyone would know about if I didn’t tell them! It was mild even at age 15, and it’s been close-to-nonexistent for the past twenty years! Now I’m a successful psychiatrist who owns his own psychiatry practice and helps other people with the condition! I told them all this. They didn’t care. I asked them if there was anything I could do. They said maybe I could go to therapy for six months, then apply again. I asked them what kind of therapy was indicated for mild OCD that’s been in remission for twenty years. They sounded kind of surprised to learn there were different types of therapy and said whatever, just talk to someone or something. I asked them how frequent they thought the therapy needed to be. They sounded kind of surprised to learn that therapy could have different frequencies, and said, you know, therapy, the thing where you talk to someone. I asked them if they actually knew anything about OCD, psychotherapy, or mental health in general, or if they had just vaguely heard rumors that some people were bad and crazy and shouldn’t be allowed to make their own decisions, and that a ritual called “therapy” could absolve one of this impurity. They responded as politely as possible under the circumstances, but didn’t change their mind. I wasn’t going to waste an hour a week for six months, and spend thousands of dollars of my own extremely-not-reimbursed-by-UCSF money, to see a randomly-selected therapist for a condition I’d gotten over twenty years ago, just so I could apply again and get rejected a second time. This was one of the most infuriating and humiliating things that’s ever happened to me. We throw around a lot of terms like “stigma” and “paternalism”, and I’ve worked with patients who have dealt with all these issues (it’s UCSF in particular a surprising amount of the time!). But I was still surprised how much it hurt when it happened to me. Being denied the right to control your own body because of some meaningless diagnosis on a chart somewhere is surprisingly frustrating, even compared to things that should objectively be worse. I thought I was going to be able to do a good deed that I’d been fantasizing about for years, and some jerk administrator torpedoed my dreams because I had once, long ago, had mild mental health issues. So I gave up. I spent the next few weeks unleashing torrents of anti-UCSF abuse at anyone who would listen. This turned out to be very productive! When I was unleashing a torrent of anti-UCSF abuse to Josh Morrison of WaitlistZero, he asked if I’d tried other hospitals. I hadn’t. I’d assumed they were all in cahoots. But Josh said no, each hospital had their own evaluation process. Weill Cornell, a hospital in NYC, was one of the best transplant centers in the country, and had a reputation for fair and thoughtful pre-donor screening. Why didn’t I talk to them? NYC was far away, and I hate to travel, but I was just angry enough to accept. At this point I’d forgotten whatever good altruistic motivations I might have originally had and was fueled entirely by spite. Getting my kidney taken out somewhere else felt like it would be a sort of victory over UCSF. So I went for it. Cornell was lovely. They tried to do as much of the process as they could via Californian intermediaries, so that I only had to fly to New York twice. Their psychiatrist evaluated me, listened to me explain my weak history of OCD, then treated me like a reasonable adult who tells the truth and can handle his own medical decisions. They were concerned that I sometimes self-prescribed Lexapro to deal with anxiety. But we agreed on a compromise: I found another psychiatrist, let her give me the exact same prescription of Lexapro at a much higher cost to my insurance, and that resolved the problem. So in late September 2023 - ten months after I started the process - I finally got fully cleared to donate, surgery set for October 12. VI. I knew, in theory, that anaesthetics existed. Still, it’s weird. One moment you’re lying on a table in the OR, steeling yourself up for one of the big ordeals of your life. The next, you’re in a bed in the recovery room, feeling fine. The operation - this thing you’ve been thinking about and dreading for months - exists only as a lacuna in your memory. Not even some kind of fancy lacuna, where you remember the darkness closing in on you beforehand, or have to claw yourself back into consciousness afterwards. The most ordinary of lacunas, like a good night sleep. There was no pain, not at first. The painkillers and nerve blocks lasted about a day after the surgery. By the time they wore off, it was more of a dull ache. The hospital offered me Tylenol, and I wanted to protest - really? Tylenol? After major surgery? But the Tylenol worked. Some people will have small complications (I am a doctor, pretty jaded, and my definition of “small” may be different from yours). Dylan Matthews wrote about an issue where his scrotum briefly inflated like a balloon (probably this is one of the ones that doesn’t feel small when it’s happening to you). I missed out on that particular pleasure, but got others in exchange. I had an unusually hard time with the catheter - the nurse taking it out frowned and said the team that put it in had “gone too deep”, as if my urinary tract was the f@#king Mines of Moria - but that was fifteen seconds of intense pain. Then a week afterwards, just when I thought I’d recovered fully, I got bowled over by a UTI which knocked me out for a few days. But overall, I was surprised by the speed and ease of my recovery. A few hours after the surgery, I walked a few steps. After a day, I got the catheter out and could urinate normally again. After two days, I was eating “SmartGel”, a food substitute that has mysteriously failed to catch on outside of the immobilized-hospital-patient market. After three, I was out of the hospital. After four, I started easing myself back into (remote) work. After a week, I flew cross-country. . . . and then I got the UTI. If this section sounds schizophrenic, it’s because it’s a compromise between an original draft where I said nothing went wrong and it was amazing, and a later draft written after a haze of bladder pain. Just don’t develop complications, that’s my advice. Still, I recently heard from the surgeon that my recipient’s side of the surgery was a success, that my kidney was in them and going fine - and that put things back into perspective. To a first approximation, compared to the inherent gravity of taking an organ out of one person and putting it in a second person and saving their life - it was all easy and everything went well. When I look back on this in a decade, I’ll remember it as everything being easy and going well. Even now, with some lingering bladder pain, modern medicine still feels like a miracle. VII. In polls, 25 - 50% of Americans say they would donate a kidney to a stranger in need. This sentence fascinates me because of the hanging “would”. Would, if what? A natural reading is “would if someone needs it”. But there are 100,000 strangers on the waiting list for kidney transplants. Between 5,000 and 40,000 people die each year for lack of sufficient kidneys to transplant. Someone definitely needs it. Yet only about 200 people (0.0001%) donate kidneys to strangers per year. Why the gap between 25-50% and 0.0001%? Some of you will suspect respondents are lying to look good. But these are anonymous surveys. Lying to themselves to feel good, then? Maybe. But I think about myself at age 20, a young philosophy major studying utilitarianism. If someone had asked me a hypothetical about whether I would donate a kidney to a stranger in need, I probably would have said yes. Then I would have continued going about my business, never thinking of it as a thing real-life people could do. Part of this would have been logistics. I wouldn’t have known where to start. Do you need to have special contacts in the surgery industry? Seek out a would-be recipient on your own? Where would you find them? But more of it would have been psychological: it just wasn’t something that the people I knew did, and it would be weird and alienating for me to be the only one. This is going to be the preachy “and you should donate too!” section you were dreading all along, but I’m not going to make a lot of positive arguments. If 90% of the people who answer yes on those surveys are lying to feel good, then only 3 - 5% really want to donate. But bringing the donation rate from 0.0001% of people to 3 - 5% of people would solve the kidney shortage many times over. The point isn’t to drag anti-donation-extremists kicking and screaming to the operating table. The point is to reach the people who already want to do it, and make them feel comfortable starting the process. 20-year-old me was in that category. The process of making him feel comfortable involved fifteen years of meeting people who already done it. During residency, I met a fellow student doctor who had donated. Later, I got involved in effective altruism, and learned that movement leader Alexander Berger - a guy who can easily direct millions of dollars at whatever cause he wants - had donated his personal kidney as well. Some online friends. Some people I met at conferences. And Dylan Matthews, who I kept crossing paths with (most recently at the Manifest journalism panel). After enough of these people, it no longer felt like something that nobody does, and then I felt like I had psychological permission to do it. (obviously saints can do good things without needing psychological permission first, but not everyone has to be in that category, and I found it easier to get the psychological permission than to self-modify into a saint6.) So I’m mostly not going to argue besides saying: this is a thing I did, it’s a thing hundreds of other people do each year, getting started is as simple as filling out a form, and if it works for you, you should go for it7. When I woke up in the recovery room after surgery, I felt great. Amazing. Content, peaceful, proud of myself. Mostly this was because I was on enough opioids to supply a San Francisco homeless encampment for a month. But probably some of it was also the warm glow of having made a difference or something. That could be you! VIII. The ten of you who will listen to this and donate are great. That brings the kidney shortage down from 40,000 to 39,990/year. Everyone knows we need a systemic solution, and everyone knows what that solution will eventually have to be: financial compensation for kidney donors. But so far they haven’t been able to get together enough of a coalition to overcome the usual cabal of evil bioethicists who thwart every medical advance. My kidney donation “mentor”8 Ned Brooks is starting a new push - the Coalition To Modify NOTA - which proposes a $100,000 refundable tax credit - $10,000 per year for 10 years - for kidney donors. There would be a waiting period and you’d have to get evaluated first, so junkies couldn’t walk in off the street and get $100K to spend on fentanyl. No intermediate company would “profit” off the transaction, and rich people wouldn’t be able to pay directly to jump in line. It would be the same kidney donation system we have now, except the donors get $100,000 back after saving the government $1MM+. (the libertarian in me would normally prefer a free market, but “avoid taxes by selling your organs” also has a certain libertarian appeal) This came up often when I talked to other donors. They all had various motivations, but one of the things they cared about was being able to advocate for these kinds of systemic changes more effectively. I personally have been wanting to push this in an essay here for a while, but it seemed hypocritical to play up the desperate kidney shortage while I still had two kidneys. Now I can support NOTA modification whole-heartedly . . . full-throatedly? . . . it’s weird how many of these adverbs involve claims to still have all of your organs. This is also one of the answers to the question I asked in section IV: how do you balance acts of heroic altruism that everyone will love you for vs. acts of boring autistic altruism that will make everyone hate you, but which will accomplish more good in the end?) Coalition To Modify NOTA is full of previous living kidney donors, who are using the moral clout and recognition they’ve gotten to get attention and change the system in an unglamorous way. I find this an admirable way of squaring the circle: do the flashy heroic things to gain social capital, then spend the social capital on whatever’s ultimately most important. If you get one takeaway from this, let it be that those guys who bought the castle were good guys. Two takeaways, and it’s that plus modify NOTA. Three takeaways, and you should feel permission to (if you want) donate a kidney. You can sign up here.9 Feel free to email me at scott@slatestarcodex.com if you have questions about the process. 1Further perspective: I’m 38, which gives me a 2/million total chance of dying per day. So the likelihood that I would die during my kidney operation equals the likelihood that I would die during a randomly chosen two months of everyday life. 2Maybe, kind of. Our knowledge of how radiation causes cancer comes primarily from Hiroshima and Nagasaki; we can follow survivors who were one mile, two miles, etc, from the center of the blast, calculate how much radiation exposure they sustained, and see how much cancer they got years later. But by the time we’re dealing with CAT scan levels of radiation, cancer levels are so close to background that it’s hard to adjust for possible confounders. So the first scientists to study the problem just drew a line through their high-radiation data points and extended it to the low radiation levels - ie if 1 Sievert caused one thousand extra cancers, probably 1 milli-Sievert would cause one extra cancer. This is called the Linear Dose No Threshold (LDNT) model, and has become a subject of intense and acrimonious debate. Some people think that at some very small dose, radiation stops being bad for you at all. Other people think maybe at low enough doses radiation is good for you - see this claim that the atomic bomb “elongated lifespan” in survivors far enough away from the blast. If this were true, CTs probably wouldn’t increase cancer risk at all. I didn’t consider myself knowledgeable enough to take a firm position, and I noticed eminent scientists on both sides, so I am using the more cautious estimate here. 3I told them I had an aunt who died of radiation-induced cancer. It’s true, but I feel grubby for bringing her into this; I thought doctors would be more likely to listen to an emotional story than cold logic. 4EAs have been debating the exact effectiveness of kidney donations for a long time. You can find good skeptical arguments by Jeff Kaufman and Derek Shiller, and good arguments in favor by Alexander Berger and Tom Ash. 5Outside of Philosophy 101 thought experiments, there’s a nonprofit that will often reimburse you for lost wages from your donation. 6Self-modifying into a person who can act boldly without social permission is a more general solution and has many other advantages. But the long version involves living a full life of accumulating moral wisdom, and the short version starts with removing guardrails that are there for good reasons. 7But here are some practical points you might not already appreciate: You shouldn’t have to pay much money. If, like me, you need to travel (eg to New York), kidney related charities will reimburse your travel costs (in theory, I haven’t yet proven this, and a few costs were illegible and I decided not to submit them).
Inline links: bumpy, 4, 5 - 7 extra years of life, improves quality of life, creates a “chain”, $5,000 - $10,000, 5, sacrifice their reputation on the altar of doing what was actually good instead of just good-looking, WaitlistZero, https://substackcdn.com/image/fetch/$s_!7c71!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F08cf5218-6398-4dfb-91a3-d5fc7989b754_765x642.png, polls, 5,000, 40,000, Manifest journalism panel, 6, filling out a form, 7, usual, 8, the, here, 9, 1, 2, Linear Dose No Threshold, this claim, 3, 4, Jeff Kaufman, Derek Shiller, Alexander Berger, Tom Ash, 5, 6, 7
Links For January 2025
January 17, 2025 · Original source
This is especially surprising because A16Z is famous for going all in on crypto early. But during the 2015 - 2018 period, Bitcoin - the absolute dumbest and most obvious crypto bet - went up 2,000%. So how is performance this bad even possible? The Twitter thread speculates that just as Uber used to happily lose money on every ride in order to gain market share, A16Z is happily losing money on every investment in order to gain VC market share. But ride-sharing is a natural monopoly; how will A16Z prevent competitors from entering venture capital? And why should people give it any market share at all if it can’t make them money? Maybe their pitch could be that you’ll make less money, but it will be uncorrelated with the regular stock market? But is that true? Aren’t tech startups pretty cyclical? Also, I wonder if this was framed to their LPs as “yeah we’ll definitely lose your money for the first ten years, but eventually it’ll all work out”. They must be the most trusting people in the world.
Links For February 2026
February 05, 2026 · Original source
9: @abio: “DC has a rideshare app called Empower that charges 20-40% less than Uber. (Drivers like it too because they keep 100% of the fare)...DC is trying to shut it down because of liability insurance. DC law requires $1 million per ride. The $1 million requirement isn’t sized to typical accidents. When $100,000 is the limit available for an insurance claim, 96% of personal auto claims settle below $100,000...Empower can offer $7 rides partly because it circumvents the mandate. DC is shutting it down for exactly that reason.”
Inline links: @abio:
42: An AI Generated Reddit Post Fooled Half The Internet. Someone claiming to be a software engineer at a food delivery company (maybe DoorDash or UberEats) talked about all the evil tricks they used to exploit drivers and customers. But on closer inspection, their story fell apart and they didn’t work for a company like this at all. I’m surprised by the arc of this story, not because the original post was convincing (it wasn’t), but because I assumed DoorDash and UberEats did things approximately this evil, but everyone acted like the fake leak was shocking (including real DoorDash and UberEats employees). Also, it’s pretty funny that in a world where everyone is worried about fake AI-generated photos and videos, the record for most successful deceptive AI-generated content is still ordinary text.
Inline links: An AI Generated Reddit Post Fooled Half The Internet
48: Also from Changing Lanes: Whatever Happened To The Uber Bezzle? A couple years ago, everyone in tech journalism was writing about Uber was a “bezzle”, a made-to-order Cory Doctorow coinage which meant it was a giant obvious Ponzi scheme that would finally reveal the entire tech industry as an emperor without clothes when it inevitably collapsed. Now Uber is doing better than ever and making billions in profits. So what happened? Obviously they stopped subsidizing their rides and raised prices until revenue > cost, but how come the bezzlers thought they couldn’t do that, and why were they wrong? Andrew says the bezzle thesis had assumed that the government would crack down on the gig economy (it didn’t; Uber had good lobbyists and voters liked cheap foods and rides), and that there would be an infinite number of would-be competitors moving in to take market share as soon as Uber raised prices (there weren’t; Uber bullied everyone except Lyft out of the market, and Lyft and Uber would rather play nicely together than compete each other down to zero marginal profit). Oh well, I’m sure tech journalists are right about everything else being a giant Ponzi scheme that will inevitably collapse and reveal the entire tech industry to be an emperor without clothes.
Inline links: Whatever Happened To The Uber Bezzle?