
Original summary · AI-drafted, human-published · added by Library
Michael Lewis tells the story of Daniel Kahneman and Amos Tversky, two Israeli psychologists whose decades-long collaboration overturned the assumption that human judgment is basically rational. Their work on heuristics, biases, and prospect theory reshaped economics, medicine, sports management, and policy, and it mattered because it gave the world a rigorous, testable account of how and why people predictably err.
Pick a finish date and Genius lays out the days — the plan shows today's target and keeps you honest.
Start a circle and share the code — everyone sees everyone's honest place in the book. Accountability, not leaderboards.
- Readers of behavioral economics who want the human story behind the theories - Managers and analysts who rely on expert judgment and want to know its limits - Anyone curious how a close intellectual friendship can produce ideas neither person could reach alone
Great intellectual breakthroughs sometimes require the friction of two profoundly different minds rather than the isolated brilliance of one.
Direct exposure to life-and-death decisions in the Israeli military gave both men early, personal evidence that confident expert judgment is often no better than a guess.
People estimate probability by how closely something resembles a familiar pattern, not by calculating actual odds, and this shortcut produces predictable, provable errors even in experts.
People judge how common or dangerous something is by how easily examples come to mind, which means memorable events distort risk perception far more than statistics do.
An arbitrary number introduced early in a decision process anchors later judgments even when the person consciously knows the number is meaningless.
People do not evaluate outcomes by their effect on total wealth but by whether they represent a gain or a loss relative to a reference point, and losses hurt roughly twice as much as equivalent gains please, which overturns the foundation of classical economic theory.
Biases discovered through simple laboratory questions carry measurable financial and human costs once applied to professional judgment in sports, medicine, and forecasting.
The mind spends enormous effort mentally rewriting events that already happened, and this backward-looking simulation shapes regret and blame more powerfully than the actual probability of what occurred.
Professional fame and unequal public credit can dissolve even the most productive scientific partnership, and the dissolution itself illustrates the very attribution biases the partners had spent years studying.
Recognition often arrives too late for the person who needed it most, which complicates any tidy story about scientific legacy and personal vindication.
Michael Lewis is an American journalist and author of Moneyball, The Big Short, and Liar's Poker. A former Salomon Brothers bond salesman turned financial writer, he specializes in narrative nonfiction that explains complex systems and ideas through the people who lived them.