From a young age, it was clear that Leo Aschenbrenner was a genius. Born in Berlin to a pair of doctors, he graduated from Columbia as valedictorian at the age of 19. After brief stints at FTX and OpenAI , he published a viral essay, Situational Awareness , that took Silicon Valley by storm and launched a hedge fund of the same name.
As Theo Baker reported in The Atlantic , Aschenbrenner became known as the “Nostradamus of AI ,” delivering insight where others only offered confusion. “I can see how AGI will be built,” he wrote and, in just two years, his fund was up more than 1,000%. He seemed a bit cocky and more than a little eccentric, but you couldn’t argue with his results.
That is, until July of this year, when his fund crashed and it turned out the bets he was making were not only highly correlated, but also highly leveraged. After a fairly minor market correction, he was forced to sell his public stocks at fire-sale prices to Ken Griffin . This narrative, of hubris leading to comeuppance, seems to be constantly repeating itself in Silicon Valley .
A truth revealed
In Martin Heidegger’s influential essay, The Question Concerning Technology , he describes technology as “a way of revealing,” and gives the example of a hydroelectric dam. A dam doesn’t create the energy in the river, but it reveals that energy and channels it in a particular way—to turn a turbine and generate electricity.
When a new technology reveals new possibilities, there is initially a lot of confusion about how to channel them. Inevitably, those who can most confidently point the way forward have an advantage. They attract investors, get quoted in the business press and are invited to all the cool conferences. They win legions of fans and build huge followings on social media.
We saw this in earlier eras. Early web companies such as Webvan , eToys and MP3.com achieved huge valuations before crashing and burning. Enron was a very successful energy trader, before it tried to repeat that success in markets such as water and bandwidth. Every boom has its share of busts.
The problem wasn’t that those were bad ideas, necessarily. In fact, different versions of the same ideas ultimately became very successful. The problem is that all ideas are wrong in some way. Some are off by a little and some are off by a lot, but they’re all wrong. A leader’s job is to make the idea less wrong over time.
It seems pretty clear that a similar process is underway now with AI and research from the Federal Reserve Bank of St. Louis shows why. While AI is helping productivity soar for some tasks, like those related to computers and math, for most things it’s having far less impact. Those closest to the tasks experiencing a productivity boom can easily mistake their experience for a universal one, giving them a certainty the rest of us don’t share.
The halo effect
As much as we like ideas, we like success even better. Psychologists call this the halo effect , the tendency for an impression created in one area to influence our opinion in another. For example, when someone is physically attractive, we tend to infer other good qualities and when a company is successful, we tend to assume other good things about it as well.
In his book, also called The Halo Effect , Phil Rosenzweig explains how these perceptions can color our judgments. He points to the networking company Cisco during the dotcom boom. When it was flying high, it was said to have an unparalleled culture with happy people who worked long hours but loved every minute of it. When the market tanked, however, that same culture came to be seen as “cocksure” and “naive.”
A more recent example was DOGE , the Department of Government Efficiency spearheaded by Elon Musk . When Musk, the entrepreneur behind incredibly successful companies such as PayPal , Tesla and SpaceX , announced that he was spearheading a major effort to make the US government more efficient, many cheered. Clearly, if anybody could get control of the federal budget, it was him.
Yet Musk’s talents and methods proved ill-suited to the complexities of government, which he showed little ability to understand. The GAO found that most of DOGE’s claims of savings were incorrect or unsupported. A study published in The Lancet projected that if the cuts to USAID continue, they could result in more than 14 million additional deaths by 2030. The US federal deficit and debt have surged .
The halo effect is a long-established psychological phenomenon, but seems to loom much larger in the tech world. You don’t see Nobel laureates in other fields like Jennifer Doudna and Katalin Karikó , whose work in CRISPR and mRNA , respectively, has arguably had a larger impact than anything that has come out of Silicon Valley, trying to run the federal government or weighing in on foreign policy.
Group polarization, the purity spiral and the bust
Clearly, Aschenbrenner benefited from the halo effect. Those who were impressed by his essay and his performance at Columbia assumed that those skills would transfer to hedge fund investing, when clearly they did not. Whatever the merit of his ideas about artificial intelligence, he failed to understand fairly basic principles of risk management.
In The Righteous Mind , social psychologist Jonathan Haidt makes the point that many of our opinions are a product of our inclusion in a particular team and that seems to be part of the Aschenbrenner story as well. He was not only expressing views about technology, but also signaling a specific identity of techno-optimism that many found appealing.
Yet the urge to signal identity often leads to group polarization and “moral outbidding,” from which a purity spiral ensues. The most extreme views are proudly displayed, creating strong bonds of group identity. Inclusion on the team is no longer enough; people want to be star players, one-upping each other as they vie to demonstrate their commitment to the cause.
Before long, moderation is treated as weakness, dissent as betrayal and the group drifts toward positions few of its members would have embraced on their own. That, in a nutshell, leads to what George Soros calls reflexivity . As the urge to adopt the dominant narrative strengthens, skepticism is dismissed, leverage increases and prices stray further from reality. Eventually, the gap becomes unsustainable, the feedback loop reverses and the boom becomes a bust.
It appears that’s exactly what happened at the Situational Awareness fund.
Silicon valley needs a red team
As President Obama’s intelligence team was gathering evidence for Operation Neptune Spear , which resulted in the killing of Osama bin Laden, they became increasingly convinced that a high-value target lived in the Abbottabad, Pakistan compound. But they also realized that certainty can cloud judgment and the costs of miscalculation could possibly be devastating.
So rather than trying to build a greater consensus, the President did the opposite. He called for the forming of a red team , a separate group that hadn’t been involved in earlier deliberations, to review the evidence, check assumptions and look for alternative explanations. After reading its report, Obama felt he understood the risks and moved forward.
That’s what Silicon Valley needs now.
Look back on any boom-bust cycle and you’ll find a breakthrough insight at its core. Railroads did indeed transform the economy. The internet really did prove to be a transformative technology and artificial intelligence promises to be no less consequential. It is no wonder that so many of the smartest people in Silicon Valley are optimistic about its possibilities.
But we’ve seen this enough times before to know what comes. The problem is that as the boom expands, the marginal players begin to pile in and push values past their rational basis. Eventually, reality sets in, things come crashing down and an incredible amount of pain is inflicted until things gain traction again.
The crash at Leo Aschenbrenner’s Situational Awareness fund was a warning: in Silicon Valley, confidence is itself becoming a problem.
