Naturalistic and Expert Judgement

The previous paper in the Decision-Making Under Uncertainty series cast heuristics as sources of bias. This one puts the opposing case: that bounded, intuitive, rule-of-thumb reasoning is not a failure of rationality but an adaptation to a hard, uncertain world — and often the smarter choice. Herbert Simon establishes that real rationality is bounded by the limits of the mind and the constraints of information and time, and that people satisfice — searching until they find an option good enough — rather than optimise. Gary Klein shows that expert decisions rest on recognition, drawn from experience, rather than the weighing of options; Gerd Gigerenzer demonstrates that simple heuristics can outperform complex models when they are well matched to their environment.

Between them, the three reframe the Kahneman–Tversky critique rather than refute it: bias and expertise are two faces of the same cognitive machinery, and which one shows up depends on whether the environment supplies fast, regular feedback.

For the operator, the useful question is not is this a bias? but does this rule fit this environment? — trust intuition where feedback is fast and regular, and distrust it where it is not. The final paper in the series turns to the environments where feedback is poorest of all: forecasting the genuinely uncertain future.