All Models Are Wrong But Some Are Useful
Updated 2026-08-17
INTRODUCTION
English translation pending.
CORE DEFINITION
A statement about the epistemic status of models, made by the British statistician George E. P. Box. Its claim is twofold: no model can reproduce the full complexity of the world, so every model is inaccurate in the literal sense; and usefulness is a separate question from truth, because a deliberately simplified model can still support explanation, prediction and decisions. Box also insisted that the relevant question is not whether a model is true but whether it is illuminating and how far it can be trusted. The dictum is a standard of judgement, not a licence for sloppiness.
SCAFFOLDING EFFECT
Reduce cognitive load
- Model selection: Choose the model whose simplifications match your purpose rather than the most elaborate one available. - Sensitivity testing: Vary the key assumptions and see how far the conclusion moves before trusting it. - Communicating uncertainty: State explicitly which parts of reality the model ignores when presenting its output.
Anchor fast decisions
Simplification is what makes a model computable and interpretable: dropping detail is the very move that turns an intractable world into a tractable structure. But the same act of dropping detail guarantees that the model fails wherever the omitted factors dominate, which is why accuracy in one regime says nothing about another. Because the purpose determines which omissions are tolerable, evaluation must be relative to a use: a model adequate for ranking options may be useless for forecasting magnitudes, and the reverse.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- analogypkm.comhttps://analogypkm.com/experience/mental-models/zh/140_所有模型都是错的，但有些有用.htmlverified
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