Blunders, Patterns, and Predictability: What n‑Gram Models Teach Us About Human Chess
Chess engines are very good at telling you what a player should do. That is not the same as predicting what the player will do. Anyone who has watched a beginner hang a queen, an intermediate player force a dubious attack, or a strong player choose a quiet positional squeeze already knows the difference. Optimality is one question. Human behavior is another. Most AI systems enjoy pretending those two questions are basically cousins. They are not. One is about the board. The other is about the person touching the pieces. ...