Ken Griffin on AI:

Ken Griffin: Let me share a few thoughts on this. First, over the last few months, there has been a step-change function in the productivity of the AI toolkit. It is profoundly more powerful than it was just nine months ago. At Citadel, that has allowed us to unleash a much broader array of use cases, and it has been really interesting to watch.

To be blunt, work that we would usually assign to people with Master’s degrees and PhDs in finance—taking them weeks or months—is being done by agentic AI over the course of hours or days.

“These are not mid-tier white-collar jobs. These are extraordinarily high-skilled jobs being automated by agentic AI.”

I went home one Friday actually quite depressed by this, because you can see how dramatic the impact on society is going to be. When you witness it within your own four walls—when you see work that used to take man-years being completed in days or weeks—it’s eye-opening.

When it comes to software engineering, a 15% to 25% productivity boost just makes you think, “Thank God, I can get more software written now.” There’s no shortage of code we need to write, so every step-change there is just a win. But when you see high-level research being done by AI engines, it is a completely different story.

Ken Griffin: Big picture, everybody is entering a world where certain forms of work will suddenly be managed by AI systems in ways we hadn’t previously anticipated. This means companies and our workforce need to be incredibly flexible and resilient.

One of the reasons students come to Stanford is to learn a specific body of knowledge, but more importantly, to learn how to learn. That will be forever critical over the journey of your career. I tell all of our new hires: “You think you just finished business school or college and the journey of learning is over? You have just started.” Everything you’ve been taught thus far matters only if it taught you how to learn. Career success will be defined by whether or not you are a lifelong learner, and AI makes that reality all the more important.

Ken Griffin: I don’t know where we’re going to be in 20 years with respect to AI. What I do know is that American entrepreneurs are remarkably talented at using new technologies to create new lines of commerce, innovate, and grow.

Ultimately, it’s a race between job destruction—which will happen at some clip—and job creation, which will hopefully happen at a faster clip.

Of note, the competitive moats that large companies have traditionally depended upon are going to be filled in with AI tools. The ability for small companies to take on incumbents will be higher than ever. For entrepreneurs, this is practically a fantasy land.

Why study history?

Ben Felix: That’s good. To start with the first question here, can you talk to us about why it’s important to study financial market history when thinking about the future?

Elroy Dimson: It’s extremely difficult to think about the future without knowing where you’ve come from. It’s an integral part of a journey. If you don’t know where the journey started, you can’t start thinking about where you’re going to end up.

China shock 2.0:

There is no doubt that Germany and its neighbors in central Europe have been hit harder than most other major European economies by the second China shock.

Germany exported more to China in the past (2.5 percent of German GDP, once upon a time), which made it more vulnerable to being squeezed out of the Chinese market.

Germany, Czechia, Slovakia, and Hungary specialized in the production of internal combustion engine cars, and thus were more exposed to China’s remarkable emergence as the biggest auto exporter the world has ever known.

A quick aside: China’s net passenger car exports are likely to top 10 million cars this year—out of a global market excluding China of 60-65 million cars). That is Japan or Germany on steroids.*

The Economist magazine on AI’s potential to kill jobs:

This dystopian possibility is behind Silicon Valley’s admonitions that state intervention, and perhaps a universal basic income, will be necessary. That remains a long way off, if it ever happens. But governments may have to act sooner, for you do not need a cataclysm to stoke popular fury. Perhaps 2m Americans lost their jobs between 1999 and 2011 owing to China’s entry into the global trading system. That is no worse than a typical month’s lay-offs in America’s churning labour market. Yet the “China shock” helped propel Donald Trump to office and led to the highest tariffs since the 1930s.

The white-collar employees threatened by AI have more political and social clout than factory workers hurt by Chinese competition. Even a small number of lay-offs could provoke a backlash against the technology; furious opposition to new data centres is a hint of what may be to come. Severe disruption to the security and status of many people could lead to widespread unrest, even revolution.