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ontological_fallacy
The ontological fallacy occurs when a model, map, theory, or abstraction is confused with the reality it represents. Conclusions are drawn as if the properties, limitations, and structure of the representation are properties of the thing itself. This is a fundamental category error: the model is an epistemological tool, not an ontological entity, and reasoning that collapses this distinction produces invalid inferences.
"According to the economic model, rational agents always maximise utility. Therefore, if someone doesn't maximise utility, they are behaving irrationally and their preferences should be corrected."
A psychologist insists: 'According to the five-factor personality model, everyone falls into measurable levels of openness, conscientiousness, and neuroticism. Since this patient doesn't fit the profile, the diagnosis must be wrong — the model is comprehensive and doesn't miss cases.'
A city planner argues: 'Our traffic simulation shows that removing that intersection reduces congestion by 12%. The model has spoken — we should demolish it immediately,' ignoring that the model omits pedestrian behaviour and local delivery routes.
Binary (yes/no) questions an LLM must answer to identify this aspect:
Does the argument treat a theoretical model, abstraction, or representation as if it were the actual reality it describes?
Type: binaryDoes the argument draw conclusions about reality based solely on properties of the model?
Type: binaryDoes the argument ignore the simplifications, assumptions, or boundaries inherent in the model?
Type: binaryThe ontological fallacy occurs when a model, map, theory, or abstraction is confused with the reality it represents. Conclusions are drawn as if the properties, limitations, and structure of the representation are properties of the thing itself. This is a fundamental category error: the model is an epistemological tool, not an ontological entity, and reasoning that collapses this distinction produces invalid inferences.
Models provide clean, tractable descriptions of messy realities. Once internalised, the model's simplicity and internal consistency make it psychologically easier to reason within the model than to grapple with the complex reality it approximates.
Explicitly distinguish between what the model predicts and what reality demonstrates. Identify the assumptions and simplifications built into the model, and ask whether the conclusion depends on those simplifications.
Widespread in economics (treating homo economicus as descriptive rather than normative), physics (confusing mathematical elegance with physical truth), psychology (treating diagnostic categories as natural kinds), and AI (treating model outputs as objective truths).
The fallacy of treating an abstract concept, model, or statistical construct as if it were a concrete thing with causal powers. This leads to confused reasoning where metaphors are taken literally and models are mistaken for reality.
Assuming cause-and-effect because events are correlated or sequential (post hoc ergo propter hoc).
Rejecting a practical solution because it is not perfect. Compares real options against an idealized, unrealistic standard and dismisses them for falling short.
Using a key term ambiguously – one meaning in premise, another in conclusion.
Use these tools to detect, analyze, or train this aspect.