Daniel Kahneman: Algorithms Make Better Decisions Than You

In this episode of The Knowledge Project, Shane Parrish interviews Nobel laureate Daniel Kahneman on decision-making, behavior, and intuition. Kahneman shares insights from his childhood, his work with Amos Tversky, and his research on happiness versus life satisfaction, noting that people often prioritize life satisfaction over moment-to-moment happiness. The conversation explores the difficulties of changing behavior, emphasizing the importance of situational factors and reducing restraining forces rather than increasing driving forces. Kahneman discusses the role of intuition in decision-making, advocating for delaying intuitive judgments by breaking down problems into separate dimensions and evaluating each independently. He also addresses the prevalence of noise in judgment and strategies for reducing it, such as using algorithms and frame of reference training. Finally, Kahneman reflects on the replication crisis in psychology, noting how it has changed his views on priming and the importance of caution when interpreting spectacular findings.