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Epistemic Uncertainty as a book category gathers works about the limits of knowledge and how we reason and decide when information is incomplete, ambiguous, or contested. It spans philosophy and epistemology, history and sociology of science, statistics and probability, forecasting, risk and decision theory, and practical guides to inference and evidence. These books probe model error, measurement gaps, bias, and “unknown unknowns,” offering tools such as Bayesian reasoning, sensitivity and scenario analysis, and uncertainty quantification. The category features debates over expertise and misinformation, case studies from science, technology, medicine, policy, finance, and complex systems, and accessible narratives showing how knowledge is built, revised, and sometimes overturned; it may also include fiction that plays with unreliable narrators or ambiguous realities. Together, they equip readers to think clearly under uncertainty and make robust choices when certainty isn’t available.

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