Epistemic fallacy

Core claim: What we know (episteme) is confused with what exists (ontology) – specifically, the (false) assumption that “only what we have knowledge of exists”, or conversely that our body of knowledge fully and accurately reflects the whole of reality.

• The absence of knowledge or evidence for something is treated as evidence of its non-existence – e.g., “We have not found any evidence that life exists on other planets, therefore extraterrestrials do not exist”.
• Only what is measurable or knowable is regarded as real, whilst everything else is ignored or called into question (“epistemic reductionism”) – e.g., dismissing aspects of a business that cannot be captured by KPIs, or judging a war solely by quantitative metrics such as body count (“McNamara fallacy”).
• The limits of available knowledge or diagnostics are equated with the limits of reality – e.g., “We cannot find a cause for this, so there isn’t one” (as with medically unexplained symptoms).
• The argument presupposes that there can be no unknown unknowns – i.e., that everything that exists is already (or in principle would be) known to us.

• The term was coined by the British philosopher Roy Bhaskar in “A Realist Theory of Science” (1975) in a narrower sense: the reduction of being (ontology) to knowledge (epistemology), tied to his theory of critical realism. In modern usage it is broader: any fallacy in which knowledge is confused with existence.
• The underlying error is a failure to keep perception/measurability/knowledge and existence apart – a distinction humans learn very early (e.g., through peek-a-boo / object permanence) and can then fail to transfer to other fields.
• In many cases the epistemic fallacy is the underlying misconception behind the argument from ignorance.
• The history of science shows repeatedly that knowledge expands to include previously unknown realities (new continents, electromagnetism, atoms, giant squids) – so our body of knowledge can never be assumed to exhaust reality.

• The claim is explicitly about knowledge, not existence – e.g., “There is currently no evidence for X” or “As far as we know, X does not happen” – without concluding that X does not exist.
• Lack of evidence is used to withhold belief or call for more research (epistemic humility), not as proof of non-existence.
• The conclusion is explicitly framed as provisional and tied to the state of current knowledge, with the possibility of future discovery acknowledged.

• Argument from ignorance – specialised form of this fallacy: deducts that if there is no knowledge of something, it presumably does not exist or is not a concern. Ask: is the fallacy a rhetorical move that uses missing evidence to shut down a concern (→ argument from ignorance), or is the underlying error the conflation of knowledge with existence (→ epistemic)?
• Ontological fallacy – existence inferred merely from a word, definition, concept or even conceivability of a thing. Ask: is existence inferred from the availability of a term/concept (→ ontological), or from the absence of knowledge/evidence for it (→ epistemic)?
• Semiotic fallacy – a symbol, model, or metric is conflated with the thing it stands for. Ask: is the confusion between a representation and what it represents (→ semiotic), or between knowledge and existence (→ epistemic)?
• Intensional fallacy – in the form of the “masked man” argument, it can be regarded as a subtype of the epistemic fallacy (conclusions drawn from incomplete knowledge). Ask: is the error a substitution of co-referring terms (→ intensional), or a conflation of knowledge with existence (→ epistemic)?
• Denying the antecedent – many epistemic-fallacy arguments have the formal shape “If X existed, we would have evidence; we have no evidence → X does not exist”. Ask: is the error best captured by the formal misuse of a conditional (→ denying the antecedent), or by the underlying knowledge-existence confusion (→ epistemic)?

Input: “We have not yet found any evidence that life exists on other planets. We should therefore assume that extraterrestrials do not exist.”
Output: This confuses knowledge with existence. The absence of evidence to date is a statement about the limits of our current knowledge – not proof of non-existence. Science has repeatedly discovered previously unknown realities (new continents, atoms, giant squids), so “not yet known” cannot be turned into “does not exist”.

Input: “If it isn’t in the KPIs, it isn’t happening in the business. We can’t measure it, so it doesn’t matter.”
Output: This is “epistemic reductionism”: treating only what is measurable as real. A company’s long-term success also depends on hard-to-measure factors such as reputation or the trust of customers and employees. Ignoring them simply because they can’t be captured by figures confuses the limits of measurement with the limits of reality.

Input: “The X-rays and blood tests are all normal, so your pain must be imaginary.”
Output: The limits of available diagnostic knowledge are being equated with the limits of reality. “We cannot find a cause, so there isn’t one” is a prime example of the epistemic fallacy – a pattern that has historically led to dismissing conditions (chronic pain, mental health issues) that were later recognised.

Input (legitimate): “There is currently no evidence for extraterrestrial life, so we should be cautious about claims that there are.”
Output: This is a claim about the state of our knowledge and a call for caution – not an assertion that extraterrestrial life does not exist. As long as it is not turned into a claim about reality itself, it is a legitimate epistemic statement, not a fallacy.

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