Michael Lewis is not interested in how or why people make mistakes.
This might be surprising, given the subject matter of his latest book. Going Infinite chronicles the rapid ascent of cryptocurrency magnate Sam Bankman-Fried and the spectacular collapse of his crypto exchange FTX and hedge fund Alameda Research upon the revelation that he had defrauded customers to the tune of eight billion dollars.
Had Lewis wanted to, he would have had an easy time contemplating the errors made in the run-up to FTX’s implosion — there are plenty to go around. There is misplaced trust and there are misplaced tokens; there are mistakes that compound and mistruths that spiral out of control; there are ideological gymnastics that serve as feeble cover for bad behavior. And there is the central mistake: nobody, Lewis included, noticed all this until it came crashing down.
Instead, Lewis is interested in Sam. Going Infinite is a riveting story exploring the psychology of an impulsive, chaotic, misanthropic genius and the path that leads him to catastrophic maximization. You will finish it in one sitting.
Going Infinite is not a book about mistakes. But the story of why people — smart people, savvy people, supposedly ethical people —make mistakes is both more interesting and more valuable than a profile of yet another fraudster. And Going Infinite does shed light on just how everybody in Sam’s orbit messed up so badly — once you read between the lines. Sam is the least interesting on this front, except insofar as his behavior shapes that of those around him. We are not ever going to be Sam. But we could be Caroline, or Nishad, or Natalie. Or even Michael Lewis. We could easily make the same mistakes they do.
I almost did. In January 2022, I decided to leave my job at Jane Street Capital to move to the Bahamas and take a job as a generalist at a new crypto firm funded by Sam Bankman-Fried. In the weeks that followed, I had three strokes of good luck:
a) I talked to a family friend, a lawyer familiar with financial fraud, who expressed alarm about various details of my new job. From our conversations, I made a list of a few dozen questions to investigate before committing.
b) I shared those questions with my new employers, believing they would be appreciated as valuable for our firm.
c) A few hours after sharing the questions, I was told not to come into work the next day; my skill set didn’t fulfill what the firm needed (indeed, I was missing the domain knowledge and operations experience required for my role, as I had only ever been a trader). The firm expressed concern that we were not on the same page in how formalized our plans needed to be. They wanted to be more on the side of “move fast and break things.”
And just like that, my plan of moving to the Bahamas and making an order of magnitude more money (and who knows how many more orders of magnitude down the line) collapsed.
In my brief encounters with the FTX world, I got a glimpse of an alternate reality where I would have had the opportunity to make catastrophic errors of judgment. I got to see other people in the FTX orbit proceed to actually make them. Not least among them: Michael Lewis himself. Lewis falls prey to many of the same types of errors his subjects made in his attempt to craft a compelling story. His resulting book is a demonstration of just how easy it is to do so, in the face of ambiguity, incentives, and access.
How did we miss this?
Nothing in Going Infinite is subtle. Lewis deals us heavy-handed metaphors, endless cliches, and contrived plot devices. Sam’s lair is the Dragon’s Hoard, lifted from his favorite video game Storybook Brawl. The entire architecture of the FTX offices is designed around a $250,000 tungsten cube — which then goes missing. Sam’s stuffed animal Manfred represents his need for emotional attachment.
The characters Lewis paints are not subtle. As he tells it, Sam is a caricature of himself, an impulsive and standoffish misfit who blabs openly and compromisingly to anyone expressing interest, regularly demonstrates how extraordinarily easy it is to steal from him, and spends most of his time playing video games. He lies pathologically, but mostly feels indifferent to the truth; he’ll say whatever is required to push past the person currently blocking his path, in a way that screams “I would definitely commit fraud.”
Every other character in Lewis’ story plays a one-dimensional role. FTX CTO Gary Wang is the strong silent programming genius. Alameda CEO Caroline Ellison is the insecure and jeopardized love interest with good intentions but terrible execution. FTX Director of Engineering Nishad Singh is the naive and chatty optimist who never seems to realize he should stop giving Michael Lewis such juicy quotes. FTX Head of Product Ramnik Arora just wants a job where he can walk to work.
The complete lack of corporate controls and financial responsibility is not subtle. “It was never clear where Alameda Research stopped and FTX started,” Lewis writes, describing the two entities that were supposed to be distinct but shared personnel, office space, and, in many cases (some of which were known to employees), financial holdings and expenditures. The book makes it clear how little regard Sam and others had for the rule of law and for following best practice: “The main job requirement [for the board of directors] is they don’t mind DocuSigning at three a.m.” (Sam), and “The law is what happens, not what is written” (Nishad). This is all despite the fact that Lewis’s narrative paints an extremely rosy picture of Sam, and tries to let the reader walk away with the impression that he never did anything worse than make a few unlucky trades and play a little loose with the books.
The lack of subtlety is a huge boon for Lewis. It makes Going Infinite an easy read. You may feel a twinge of embarrassment for the characters and toward the author for facilitating your voyeurism — but in this regard, at least, the book is accurate. Reading Going Infinite is aesthetically reminiscent of everything I saw of the FTX orbit, which at the time I described to friends as living in a trashy TV show with characters who were just a little too over-the-top to be believable. For all that he misses, Michael Lewis absolutely succeeds at capturing the vibes of Sam’s world.
What he does miss, however, is quite a bit. Lewis began researching and writing Going Infinite in Spring 2022; FTX collapsed in November 2022, and Going Infinite was published nearly a year later on October 3rd 2023, the first day of Sam’s criminal trial, in which Sam was found guilty of seven counts of fraud and conspiracy. As late as the final days of October 2022 you could have had “not the faintest sense that anything was amiss,” Lewis writes, and indeed he seemed not to have had any. Given all that we now know — that Lewis also came to know, with plenty of time to reflect and rewrite — there is a missing mood of introspection to his reporting. Lewis has a refrain throughout the book of “you don’t see what you’re not looking for.” He stops short of asking what he himself was and was not looking for.
Ambiguity obscures harm
Sam’s world thrived on ambiguity. The laws regulating cryptocurrency, where they existed at all, were indecipherable, full of open ends and contradictions. The value of any specific coin or token was hard to calculate and only loosely linked to its visible spot market price. The volatility and sheer size of Sam’s investments obscured how reckless they were. The potential for gargantuan returns in a new, untested business made it seem plausible that he was actually making financially wise investments. As a result, his impulsive and lavish PR stunts — like buying the naming rights to a stadium for tens of millions — didn’t tip people off to his recklessness or make them question his self-professed altruism.
In Sam’s world, there were no guardrails. Traditional finance is heavily regulated, with laws and norms to detect wrongdoing and protect against disaster. But the crypto industry had evolved at a faster pace than the regulations governing it, and the laws that did exist were treated lightly or intentionally skirted by many of the major players.
Most of the characters in Sam’s orbit were 20-somethings with little finance or legal background. Sam, who “thought grown-ups were pointless” and did his best to keep them at arm’s length, benefited from his employees’ inexperience. They ended up deferring to his comparative expertise, reinforcing the notion that the normal rules didn’t apply.
Those employees were compromised not only by their inexperience but also by their tangled relationships. They were far away from home and had no social life outside of work. A person’s coworker or boss was often also their friend, roommate, and romantic partner or prospect. Maintaining multiple types of relationships with the same person resulted in blurry lines and poor professional norms, and made it hard to notice inappropriate behavior.
When legal, professional, and personal obligations are ill-defined, it’s easy to avoid fulfilling them. Sam was a masterclass in how to leverage these ambiguities. He disdained job descriptions and org charts, which he claimed make employees substantially worse at their jobs. By eschewing titles and hierarchies, Sam gave cover for wildly variable compensation and job responsibilities among employees, who often didn’t figure out they were being comparatively underpaid until way too late.
Michael Lewis, when confronted with Sam’s ambiguities, makes the mistake of consistently giving him the benefit of the doubt. The opening chapter of Going Infinite presents a character who doesn’t so much lie as evade ever giving a firm answer. Lewis takes Sam at his literal word, insisting that he never explicitly lies, even as many of Sam’s claims throughout the book contradict one another.
The key tactic that works for Sam here is the language of probability. Sam constantly expresses beliefs as probability distributions, and this gives cover for his absurdly optimistic and self-serving claims. Lewis, enamored with a quirky nerd who sees the world in mathematical models, fails to ever investigate those models. A sharper Lewis would have evaluated Sam on his own terms, tracking his probabilities and interrogating how closely they aligned with reality. At a minimum, he should have pressed Sam on how he reached his probabilistic claims. When Sam asserts that the $4 million worth of Ripple that went missing in the early days of Alameda had an “80 percent chance” of eventually turning up, Lewis asks no further questions. With the hindsight of FTX’s collapse and the disastrous trades that precipitated it, Lewis’ failure to examine that 80 — or any of Sam’s probabilistic claims — is especially jarring.
The branch of Effective Altruism that Sam ended up most invested in is also the one where impact is hardest to measure. The projects he supported via the FTX Foundation aimed to reduce existential risk to humankind from disease, artificial intelligence, nuclear war, and the like. But it is inherently difficult to measure small changes in the probability of global catastrophe (“No one actually knows what the odds of any of these things are,” Lewis writes), so these projects often had effects of unclear size and sign. Furthermore, many of the projects, such as talent searches and investments in promising individuals, were valued for their potential to compound over long periods, making their effects even harder to measure.
I write this with complicated feelings, as someone whose life is oriented around the reduction of existential risk, and having myself benefited from the money Sam poured lavishly into these endeavors. When what appears to be the highest value use of our time and money is hard to distinguish from a ponzi scheme, it’s especially incumbent upon us to not let ambiguity serve as a cover for self-indulgence. The temptation to justify limitless spending on ourselves is enormous, and requires constantly reexamining the motives that might bias our tradeoffs. Sam does not appear to have engaged in this introspection.
Incentive gradients run steep
Ambiguity and unfamiliarity might have been sufficient to explain how nobody noticed the deep rot in FTX land if Sam’s deception had been subtler or more strategic. But nothing about Sam was subtle. Rather, ambiguity worked to cover up the potential for harm because the people with any proximity to Sam’s bad behavior stood to benefit from allowing it to do so. You don’t see what you’re not looking for, and those caught up in Sam’s world were not especially looking for liabilities.
For FTX employees, the incentives not to question what was happening were overwhelmingly strong. There was so much money to be made. One might think that this would create an abundance mindset, where they could revel in having more opportunities, more choices, more resources. When I was briefly immersed in this world, though, I felt the opposite. Every small decision you made had implications to the tune of millions of dollars. Any time you did a good trade, you were thinking about why you didn’t do a better trade. And a lot of the best trades felt like they might disappear at any moment, so you had to make the most of your advantages while you could.
By April 2022, Caroline knew she wanted out. She felt unhappy, inadequate, and uncertain about whether things would get better. But she didn’t want to leave something so lucrative without giving it serious thought. She wrote: “I think it’s plausible that running Alameda is super high EV [expected value] and way higher than my next best option. I think I shouldn’t consider quitting Alameda until I’ve spent a lot of time thinking about alternative options and their EV.” Maybe if she’d had a lot of time to spend thinking through alternative options, Caroline would eventually have ended up leaving. But time was a scarce commodity; in the FTX orbit everything felt urgent.
A striking element of Going Infinite is how little agency Lewis attributes to any of the characters. You would think the people who abandoned their cushy trading or software engineering jobs to move to a foreign country and build a crypto exchange from scratch would be among the most proactive people in the world. But nobody seems to have been a decision-maker. Caroline acted out of insecurity and dread. Gary was simply implementing the algorithms he’d been told to. Even Sam, as a trader and as a utilitarian, is portrayed as just following the math to its natural conclusions. Here, Lewis picks up on something real. The book successfully captures the internal experiences of people warped by staggering financial incentives and artificial urgency — and implicitly absolves them of responsibility.
Even outside of crypto trades, there was plenty of money to be made in Sam’s world by extracting it from Sam himself. He walked around leaking money; if you happened to be in his proximity, you were likely to get some of it. He made negative expectancy investments — that is, likely money-losers — that were motivated by social or romantic considerations. For example, he kept his girlfriend Caroline in charge of Alameda Research despite the fact that, by her own admission, he disapproved of her job performance. His one childhood friend grew up to invent the video game Storybook Brawl; Sam then bought the game company, to achieve “ethical integration of gaming and crypto transactions” (none of this was subtle). He paid Shark Tank venture capitalist Kevin O’Leary $15 million for celebrity endorsements and a virtual lunch — his explanation for his choice of celebrity was “he came to us.” Coming to Sam was a great trading strategy.
A lot of Sam’s money flowed through whichever effective altruists caught Sam’s attention to whichever projects caught their attention. The influx of money into the EA world and the urgency with which Sam wanted people to spend it made it easy to siphon money off of the FTX machine if you hung around enough. “‘If you throw away a quarter of the money, that’s very sad,’ [Sam] said at one point, ‘but if it allows you to triple the effectiveness of the rest, that’s a win.’” By cultivating an approach to charity that involved throwing away millions of dollars, Sam incentivized people to stay near FTX to try and catch them.
I wasn’t immune to the incentive gradient, either. After I was dismissed from the crypto hedge fund I’d planned to work for in February 2022, I kept my distance from EA for a few months, wary of what I perceived as wastefulness and superficiality in the slice of the community I had encountered. But by May, I needed a job, and it was not hard to see that the fastest path to prosperity in the Effective Altruism world included a pit stop in the Bahamas. So I bought a plane ticket to Nassau, and within two weeks of my trip I had a fantastic position at an exciting new nonprofit organization funded by the FTX Foundation.
I don’t know how to feel now about that plane ticket. On the one hand, the job I ended up in was a perfect fit. I was eminently qualified, and both I and the organization were substantially better off as a result of me joining. It introduced me to a community of earnest, introspective, devoted people, banded together to try to change the world for good, a community that I feel extraordinarily lucky to now call home.
On the other hand, I was a willing participant in a web of incentives that likely compromised my epistemics and ethics. Participating in it had such high expected value — first in dollar terms, when I planned to trade crypto, and then in impact-on-the-world terms, when I went in search of an altruistic job. It seemed absurd to keep my distance just because the “vibes felt off” in the world of FTX and EA (at that point, the two were interchangeable in my mind), with no concrete cause for concern or evidence of wrongdoing in my field of vision. But if the incentives hadn’t been so strong, would I have paid more attention to the suspicious feelings in my gut?
I think sometimes about the versions of me out there who would have held back from buying that plane ticket. There are alternate-universe-Rickis who smelled something rotten in FTX land and decided to stay away from that rot despite the enormous incentives not to. Those Rickis don’t end up in the Effective Altruism world. I think we would have benefited from having more of them around.
Selection effects filter out the whistleblowers — and tell a skewed story
In the aftermath of the FTX collapse, observers expressed bewilderment that nobody in Sam’s world had looked around at any point and said “Hey, we really ought to have an auditor.” Well, some people did — but they were way less likely to make it to week three of the job. They never ended up seeing the balance sheets, or gaining access to the codebase, or coming into contact with enough information to have direct evidence of wide-scale fraud.
A few people came pretty close. Lewis describes the early days of Alameda, when Sam was working with a group of effective altruists in the Bay area. And those EAs were really concerned about Sam’s behavior. They saw him as dishonest, manipulative, and reckless. They weren’t okay with a state of the world in which the firm didn’t know how much money it had, or where that money was, or what to do to prevent the problems that had caused it to go missing in the first place. Thus came The Schism: in April 2018, Sam’s entire management team and half his employees walked out the door.
As a result, the set of people who helped Sam rebuild Alameda were selected for some combination of lawlessness and naivete. The legal and ethical murkiness of Sam’s behavior was obvious to some people — the ones who got up and left. Those who remained or whom Sam hired thereafter were either more trusting of Sam, more comfortable getting entangled in ethically dubious endeavors, or simply kept out of the loop.
Similar selection effects determine the subjects of Going Infinite. Reading the book, one can’t help but wonder how all of these people were foolish enough to tell Michael Lewis everything. But “these people” are precisely selected for how much they blabbed. Naturally, he’s going to feature quotes from the people who talked to him, and not the people who didn’t. As a result, the book presents a picture where the most naive — or most overconfident — characters in Sam’s world play an outsized role.
Finance writer Patrick McKenzie points out on Twitter that even though strategic consulting firm M Group deserves much of the credit for Sam’s PR success, they merit just one paragraph. Meanwhile, more than a chapter goes to Natalie Tien (FTX Head of Public Relations, despite having zero prior PR experience). “Lewis would have you believe she single-handedly managed calendar, juggled magazine cover shoots, and put on conferences featuring e.g. Clinton,” he writes. That is, per McKenzie, the strategic communications consultancy was responsible for much of Sam’s media coverage but also knew better than to play a major role in the Michael Lewis expose of their client committing major fraud, and managed to finesse an outcome in which they dodge association with Sam. In other words, Michael Lewis screen time is not necessarily a great benchmark for the true importance of a character in the FTX story.
Another paragon of spotlight avoidance is Gabe, Sam’s younger brother and head of Guarding Against Pandemics, the PAC charged with distributing Sam’s political spending. Gabe’s name appears 14 times in the entire book. (In contrast, we have 90 mentions of Nishad.) The single quote Michael Lewis includes from Gabe is the equivalent of “Sam? Never heard of him. Maybe we lived in the same building once?”
Even among the major characters in the book, those who keep their mouths shut end up looking a lot better than their coworkers. Lewis would have you think that CTO Gary’s entire personality is persistent silence and solitude. In one scene shortly after FTX’s collapse, Nishad and Sam argue about throwing each other under the bus as Gary watches in silence. “It was as if he had made an expected value calculation of whatever he might say,” Lewis writes, “and decided that words still did not pay.” The real Gary isn’t as chronically silent as Lewis would have you believe. He’s capable of speaking when it pays to do so; at Sam’s trial in October 2023, Gary testified eloquently and successfully. He just knew better than to talk to Michael Lewis.
Despite having worked on Wall Street and made a career out of writing about finance, Lewis’s treatment of cryptocurrency is surprisingly superficial. After less than one paragraph discussing Bitcoin, Lewis cuts to a footnote: “That’s it for crypto explanations for the moment, as that’s about all that Sam Bankman-Fried knew about crypto, or for that matter needed to know, to trade billions of dollars worth of it.” His subjects’ ignorance and crypto’s complexity ought to have compelled him toward making more of an effort to understand and explain what’s going on with crypto. Instead, he leaves a blind spot for himself and his readers.
Lewis ends up relying uncritically on his subjects’ accounts of anything technical. As a result, he offers high level takeaways that leave out key context or rely on faulty math. Lewis narrates Nishad’s description of the effective altruist investors in Alameda in its early days:
In their financial dealings with each other, the effective altruists were more ruthless than Russian oligarchs. [Alameda’s effective altruist] investors were charging them a rate of interest of 50 percent. ‘It wasn’t a normal loan,’ said Nishad. ‘It was a shark loan.’ In what was meant to be a collaborative enterprise, Sam had refused to share any equity with anyone. And now all these unprofitable effective altruist [employee]s were demanding to be paid millions to quit — and doing whatever they could to trash Sam’s reputation with the outside world until they got their money.
By adopting Nishad’s framing of loan-shark interest rates, Lewis paints a picture of the effective altruist investors as overly aggressive and greedy. But presenting these investments as extortionate loans ignores that typical hedge fund investors (structured as limited partnership interests) commonly receive rates of 80% of the profits.
Thus, the investors here in Alameda were getting less of the profits (50%, not 80%) and Alameda management was getting more (50%, not 20%) than in the typical private equity investment. There are important differences between debt and equity investments that make this 80% an imperfect comparison point — for example, interest on debt is owed regardless of fund performance, while carried interest is only applied to profits. Because debt can be structured to be equity-like, and equity can be structured to be debt-like, an exact comparison cannot be made without the details of these loans, which Lewis does not provide. Eliding the details of the specific debt structuring that early Alameda used and omitting to explain the usual fee structure for private equity investments allows Lewis to paint a very harsh picture of Alameda’s investors, and by contrast a much rosier picture of Nishad and Sam.
Nishad, a software engineer in his 20s with no finance background prior to FTX, might not have known enough about standard hedge fund structuring to make reasonable comparisons. He may have genuinely believed (whether because of Sam’s influence or his own assumptions) that the EA investor terms were unfair. Michael Lewis, on the other hand, should really know better.
In other places in the book, we see Lewis present similarly confused technical explanations that end up giving a more favorable view of Sam than is warranted. He tells a story from Sam’s early years at Jane Street Capital. Interns were encouraged to hone their trading skills by making bets with each other for real money, with individual daily losses capped at $100. At one point, Sam entered a bet with fellow intern “Asher Mellman” on the maximum intern dollar loss that day, with Sam profiting as that value exceeded $65.
To drive up losses, Sam offered other interns $1 to engage in coin flips with him for nearly $100 each, maximizing how much of Asher’s money — and dignity — he could extract. He went through four such coin flips, winning the first three, such that those interns lost nearly $100 each and Asher owed Sam the maximum amount from their bet. Later, Sam got in trouble with his managers (“‘They said the second coin flip was already one too many,’ said Sam”), and concluded dismissively that Jane Street thought he should have been more sensitive to his fellow interns’ emotions.
But if you dig down into the math in the story, several of Sam’s coin flips actually turn out to have been negative expected value for him.
After Sam’s first coin flip against another intern, the maximum intern loss of (approximately) $100 had been achieved, and Sam’s additional flips wouldn’t have extracted more money from Asher — by then, he was just giving out a free $1 in expected value to other interns. While Lewis would have us see Sam as a nimble Bayesian, we see him spot a succesful coin flip, and then continue flipping, without stopping to recalculate whether his trades were still any good.
Sam’s managers chastised him for his inability to treat his fellow interns with dignity. I would not be surprised if they also chastised him for doing reckless, negative expectancy trades and Sam simply heard what he wanted to hear, ignored the rest, and went away with exactly the wrong lessons. But the more interesting mistake is Michael Lewis’s indiscriminate reporting of a narrative that doesn’t pass the financial fundamentals smell test, and instead reads like a story constructed from a mishmash of trading tales, optimized to convey the vibes of the Jane Street internship trading floor (which it successfully does) at the expense of getting the details right.
By uncritically passing on (his recollection of) Sam’s narrative, Lewis paints a portrait of Sam as singularly motivated by doing the EV-maximizing thing despite the social and emotional costs inflicted on others. But the real Sam in this story is not taking a hit to his reputation in order to maximize expectancy; he’s carelessly burning expectancy in the process of cultivating a reputation for punishing and humiliating his competition. By aggressively asserting an image of himself as a ruthless maximizer, he succeeds at convincing Lewis of it as well.
Lewis isn’t the only one who made these mistakes. The characters, narrative, and thrill of experiencing a life in the far tails of normal human experience caused everyone involved — myself included — to overlook the technical details. FTX’s story beguiled not just those inside it, but also investors, journalists, Congress, and countless spectators. A closer eye calculating the flow of money or the expected value of Sam’s trading strategies might have noticed some red flags, but the social and interpersonal dynamics around were just way more captivating.
How can we do better?
At the risk of implying that this advice is anywhere close to exhaustive or sufficient, here are some possible takeaways.
Notice when you’re confused. Pay attention to that confusion, and seek out answers. If the people you ask don’t know the answers, that’s a sign you need to know more, not less.
When there are ambiguities, push for specifics. Make the range of possible outcomes intelligible. If seeking clarification gets you fired, that’s evidence of rot underneath. In trader terms, this is called adverse selection — if your counterparty won’t specify a price within a broad range, the true price is more likely to be at the lower end of the range than at the higher end. If the underlying facts reflected well on them, they’d be more inclined to provide more information when you push for it. Get things in writing; ask for binding commitments, and don’t trust that other players in a zero-sum environment will have your best interests at heart.
Get a pair of outside eyes — ones that aren’t subject to the same set of incentives that you are. If you can, get someone who does have experiences relevant to the situation at hand. Talk to people whose backgrounds, motivations, and ways of moving through the world are not highly correlated with your own. My Wall Street lawyer friend didn’t have precise probabilistic models, but he did have years of working on Bernie Madoff and other fraud lawsuits, and heuristics he’d developed about how fraud plays out.
External advisors, regulatory bodies, and even lay observers can offer perspectives that are not cloaked by the day-to-day incentives and tunnel-vision of a high-stakes, highly-cohesive work environment.
I still remember a conversation with a homeless friend of mine whose immediate reaction to my work adventures in January 2022 was, “Oh yeah, this is definitely fraud. There is no way these people are not committing fraud.”
Put yourself in environments where the incentive gradient flows in a direction you endorse. The current will be stronger than your ability to row against it. Surround yourself with people who make you a better version of yourself, who push you to be honest and scrupulous and just and kind.
Finally, if you do manage to avoid getting caught in a moral morass, your work is not done. A mix of caution and luck helped me avoid playing a major role in the FTX story. But my own clean hands didn’t prevent harm from happening. We need structural supports and coordination mechanisms — laws, corporate controls, societal norms — to reduce harm. As individuals, we have power to influence those laws, controls, and norms. We can reward transparency and truth seeking, call for expert oversight for actions with elusive and high variance outcomes, and cultivate reverence for institutional and inherited wisdom.
Some of the mistakes of the FTX story are epistemic mistakes, failures of reasoning due to insufficient background and clarity. Some are ethical mistakes, willingness to take on risks to others of unknown size and probability. Some are mistakes of agency and access, where those who might have caught and reported problems were kept far away from the problems and thus never had the power to report. None of them happen in a vacuum. Our epistemics, incentives, and access all influence one another, and those influences are often invisible to us. Mistakes are adaptive, fulfill our self interest, and get made most consequentially by those least likely to interrogate them.
In Going Infinite, Michael Lewis is not interested in how or why people make mistakes. By default, we won’t be either.