Welcome to the Deep Dive: this episode explores why simple mental shortcuts — fast and frugal heuristics — can outperform complex statistical models in noisy, uncertain environments. We examine vivid case studies (like Kalahari Bushman trackers and an emergency-room triage that beats a 19-variable algorithm), theoretical tools (bias–variance trade-off, the recognition heuristic), and evolutionary accounts (error management theory and ecological rationality).

Key points: heuristics are often adaptive features, not flaws; ecological fit determines success; asymmetric error costs shape biases; and simple rules can be more robust than complex models in large, uncertain “real-world” problems.

The episode closes with practical guidance: a seven-step, toolbox-style approach to choosing the right heuristic for the right task, when to trust intuition versus when to apply formal analysis, and how to design decision environments that let simple rules work effectively.