After class this morning one of my regulars told me she was going to visit her friend, who was sitting in the ICU with a 36 y/o who has lived with severe cerebral palsy his entire life. She said it clearly and only once. "Both of his parents died from COVID 5 years ago." Her friend was the godmother, so she took him in. Then almost in the same breath she said, "He recently came down with the FLU, and started vomiting, and because of his cerebral palsy he aspirated and developed pneumonia and sepsis.” I stood there in my sweaty teaching clothes and watched a window open in her eyes to a deeper connection. Those eyes suddenly filled heavy with tears. She wiped at them with the heel of her hand, then again, and again. The tears opened a brief, clear window past the word "flu" she kept using and through to the deeper reality of what had already taken his parents. She kept talking through that reality though, voice catching. "The whole situation is so sad. The poor guy never had a chance once the vomiting started, because he can't swallow with the cerebral palsy." I thought the next wipe of her hand might come with the real name of what had already taken both of his parents, and has now returned inside that ICU, knocking hard on the door for their son. The tears kept coming, steady and moved by the story she was telling me. It was the kind of crying that starts once something deeper has already been understood, and the mind is only beginning to catch up. The word "flu" stayed where she left it, hanging suspended between us. She never reached back for it, and did not say that word again. This is the part that still bothers me. It is not the denial exactly. It is how denial and recognition can live within the same person at the same time. She could say Covid when it belonged to the past, to the two already gone and buried. She could not say it in the present, while the same thing returned for their son, as if the first deaths had only been the beginning. The word stayed buried with them. What she would not speak came out of her eyes instead. This is the shape of the world now. The outline of what remains is still felt on a deep subconscious knowing, and a softer word is offered in its place, so the crying can continue without having to confess what the eyes already know.

There’s only one other time I’ve seen the market this complacent in the face of an imminent, systemic risk. And I’m having déjà vu, because the risk around AI related cybersecurity has the same shape and setup as the pandemic risk in early 2020. Though it’s arguably worse. Bearish market calls are a dime a dozen. But my threshold for making a public bearish call is extremely high. I’ve only done it once before…Feb 2020, weeks before the market fell 35% in a month. By early Feb 2020 it was already clear to anyone paying attention that COVID was going to be a global pandemic. We had access to a lot of experts, and they were unanimous in their belief that a global pandemic was inevitable. And yet the public and the market treated it like another Ebola or SARS headline. When I warned people to prepare, I was told that we couldn’t have a global pandemic in this day and age. Today, people have the same difficulty imagining that the internet could become unusable. It’s so fundamental to how we live that its continued functioning is treated as a given. In 2020, the market didn’t discount this risk until the evidence hit them right in the face. So the adjustment was violent and nearly instant. In modern markets big tops are typically a process. They don’t tend to crash from all time highs. Economic data slows, breadth narrows, credit widens, etc. The market takes the signal piece by piece and distributes over months. But this one fell out of a clear sky, because an exogenous shock doesn't have to generate those kinds of signals in advance. Quantitative models are good at extrapolating signals that have paid off in the past. That has increasingly become the backbone of financial markets, as well as betting and prediction markets. You can model a football game, or the weather based on data. But if a novel risk hasn’t shown up in the signals a model tracks, it doesn’t just estimate the odds poorly, it may not represent the risk at all. That’s why the market could sit at an ATH high in Feb 2020, with a catastrophe weeks away. And its why the market currently sitting near an ATH doesn’t give me much reassurance. For a legible, datable risk it can discount ahead of time. It bids up vol into an election or a Fed meeting. But it struggles to price a novel exogenous tail because it has no reference class and no event date. It stays silent, right up until the repricing. Today the cyber experts agree on the direction the way the epidemiologists did in February 2020. AI cyber capabilities now pose a risk to our entire digital system. And every day we get more evidence that we are nearing a tipping point. Our economy and livelihoods run on that system. The tail risk is a collapse, and its fatter than the market is pricing. I believe serious disruption is now a foregone conclusion, and only the magnitude and timing are still in question. The market may wake up to this risk because of a single event that impacts the public in a visceral way, but that won’t be the underlying problem. That’ll just make it clear that the rules have changed. This is a paradigm shift in what attackers can do and how many systems they can target. And like in 2020, the market can recognize the most obvious exposures without grasping how far the damage could spread. In the weeks before the 2020 crash the market did lightly discount the most direct, first order pandemic trades. The cruise lines, the airlines, a handful of others. But the fallout was never going to be contained to those names. You can argue that the market is already discounting some risk, as the AI related trade has come under strain, credit markets are tightening, and there are other red flags under the hood. It’s hard to differentiate how much of that is due to cyber risks (and its second order implications), rather than fears over capex sustainability, large capital needs, valuations, etc. but the important point is that the market as a whole is still not pricing the scale of the risk. Since the market tends not to slowly discount this type of risk, it means you can’t wait for confirmation. The opportunity is to position before the market recognizes what’s already qualitatively visible to experts. Which is what worked in February 2020. But this isn’t an argument for fatalism, because the setup gives us an opportunity. Protection against an unpriced tail costs very little, because no one is bidding it. If the event never comes, you’re out a small premium. If it comes, you get paid from an undiscounted base, which is where the largest repricings in history come from. That asymmetry means you only have to notice that the price of the insurance is cheap relative to the payoff. I should say that the risk to this strategy is timing. A cheap convex bet is cheap per unit time but if that event takes longer then you can get eaten up by the carry. I think the timing of the market realization has now approached the point where my own qualitative analysis suggests that it is appropriate to take steps to protect your portfolio. But explaining the reasoning behind that assessment would take pages. This isn’t financial advice. You should decide for yourself. I’m just making my own thoughts and logic public for anyone who cares how I am thinking at the moment. I've never hoped more that I'm wrong.

🚨 To protect humans over the next few years, we'll need to RETHINK the economy, labor rules, the tax system, and social incentives. Governments should immediately start planning: - Human-only job categories - Layoff limitations - Comprehensive reskilling programs - Career-transition assistance - AI deployment taxes - Universal Basic Income - Mental health support - AI-funded essential services - AI productivity dividends - 'Minimum human interaction' rights - Special funds for human-made products - And more. It worries me that most governments seem reluctant to start these discussions. I guess they're afraid of public backlash. The train has already left the station, and doing nothing will be worse for society. Pretending the problem isn't there will not make it disappear. The only places I have seen seriously discussing this are California, China, Singapore, and South Korea. It also bothers me that AI labs and tech companies are not pushing these discussions more actively. They know it's coming, and they know very well how bad it will be without proactive organization. These preparation policies should start being implemented NOW. I'll write more about it in my newsletter.