AI Expert Highlights Why Traders Lose Money!

Summary

Jason Shapiro (host) discusses an episode of the Diary of a CEO podcast featuring AI researcher Daniel Kokotailo, who previously worked at OpenAI and later founded the AI Futures Project. Kokotailo released “AI 2027” in April 2025.

Shapiro praises the interview as especially valuable because Kokotailo’s background is philosophy rather than computer science/physics. This leads the conversation to focus on how human psychology shapes outcomes.

Main Theme: Rationalization Destroys Clear Thinking (Especially in Trading)

Shapiro argues that rationalization—creating “logical” explanations to avoid admitting you’re wrong—is a major reason people (and traders) lose money. He frames rationalization as a way to:

• reduce emotional discomfort or guilt
• protect self-image (not looking stupid)
• make one’s actions seem reasonable to oneself and others

He highlights how this behavior appears most clearly in not cutting losses. Traders who miss major opportunities (such as “the biggest move possibly of our lifetime”) may rationalize their absence with narratives like: “It was a bubble”—even if that story is self-serving and incorrect in practice.

Shapiro emphasizes that the market doesn’t reward these psychological explanations: if you’re wrong, you’re wrong, and you lose money.

People Often Believe Their Own Rationalizations

Shapiro notes rationalization isn’t always conscious. People can genuinely come to believe what they need to believe, even when evidence contradicts them—similar to how political groups justify outcomes regardless of facts.

In trading, this mindset prevents learning and adaptation.

Applying It to Investing: Admit Being Wrong and Follow Process

Shapiro offers a practical solution: treat the ability to stop rationalizing as a behavioral skill you can recognize and correct.

• Use a defined process for trades.
• Include a specific point where you are proven wrong, usually tied to why you entered the trade.
• Use a predetermined exit rule (e.g., a stop-loss tied to the original thesis), so the trader acts without emotional back-and-forth.

He contrasts ideal trading rules (“ride winners, cut losses”) with why people fail to follow them—again returning to rationalization.

Shapiro also shares his approach: he says fewer than 40% of his trades are winners, but his returns are strong because his losers are small. He achieves this by admitting mistakes quickly and letting winners run.

Link to AI (Kokotailo’s Broader Argument)

Shapiro connects Kokotailo’s discussion of AI risk to the same psychology. People may enter dangerous AI races by rationalizing that they must participate to prevent worse outcomes by competitors—an “arms war” dynamic.

While Shapiro’s primary focus is trading, he argues the underlying psychology is the same.

Presenters / Contributors

• Jason Shapiro — video presenter/host
• Daniel Kokotailo — featured AI researcher interviewed on Diary of a CEO