The first time I came across The Art of Thinking Clearly was when a well-known sports news anchor in my country (Adel Ferdosipour) translated it into Persian. It was widely promoted on social media, and a lot of people were talking about it. But I never read the translation—and in hindsight, I’m glad I didn’t. Persian is a beautiful language for literature and poetry, but when it comes to scientific and analytical writing, it doesn’t always capture the precision and nuance of the original text. English, in my opinion, is the best language for these topics, and reading books like this in their original form makes a real difference.
One of the things I noticed while reading was how much of the book’s insights come from the world of financial markets. That really resonated with me because I’ve personally experienced many of these biases while dealing with high-pressure financial decisions. The emotions, the second-guessing, the overconfidence—it’s all part of the trading world. And if there’s one clear takeaway, it’s that human thinking is not naturally suited for rational decision-making in finance. We react emotionally to gains and losses, we follow the crowd when we shouldn’t, and we fall into predictable patterns of irrational behavior. The book, also, sheds light on how we make decisions when faced with uncertainty—and how often we get it wrong. We rely too much on intuition, misjudge risks, and let emotions cloud our thinking. Concepts like loss aversion, overconfidence, and the gambler’s fallacy show why predicting outcomes is harder than we think.
At the same time, I’ve always been interested in looking at these biases through the lens of System Dynamics. Many of them don’t just exist in isolation but are reinforced by feedback loops and systemic patterns. I’ve often thought about modeling some of these biases to better understand how they scale beyond individuals and influence larger systems like markets, organizations, and even policy decisions. That’s something I’d like to explore further in the future.
Of course, with 99 different biases covered in the book, it’s impossible to reflect on each one in detail. But many of them can be grouped into broader categories—social influences, probability errors, and behavioral traps—and they all show up in real life in ways we don’t always recognize. What I appreciate most about this book is that it doesn’t just describe these biases, it makes you more aware of how they play out in your own decisions. And once you see them, you can’t unsee them.