Xenoepistemologies

This book develops xenoepistemology, a new framework for understanding knowledge produced by systems whose operations exceed individual human surveyability. Automated theorem provers, protein-structure predictors, self-driving laboratories, large-scale simulations, and multimodal AI systems do more than accelerate scientific practice: they transform the conditions under which evidence, explanation, discovery, expertise, and trust are established. The book argues that epistemic legitimacy can no longer depend exclusively on human belief, understanding, or semantic access. Instead, knowledge produced within human-machine systems can be assessed through structural criteria such as reliability, robustness, counterfactual sensitivity, transfer across contexts, and independent validation. The relevant unit of epistemic analysis therefore shifts from the individual knower to the wider epistemic ecology in which humans, machines, institutions, infrastructures, and validation practices interact. Drawing on cases from mathematics, physics, chemistry, biology, climate science, astronomy, the social sciences, and the digital humanities, the book examines how artificial cognition is reorganizing disciplinary boundaries and scientific expertise. It introduces concepts including the meta-specialist, xenoepistemic proxemics, and the recognition regress, while also addressing peer review, authorship, patent law, platformized knowledge, and the concentration of epistemic infrastructure.The position defended is post-anthropocentric but not anti-human: human understanding remains indispensable in many contexts, but it is no longer the sole gatekeeper of epistemic legitimacy.