Beyond Detection: An Epistemic Limit of Purely Computational Misinformation Defense

Liza, Farhana Ferdousi (2026) Beyond Detection: An Epistemic Limit of Purely Computational Misinformation Defense. Companion Proceedings of the ACM Web Conference 2026. pp. 1-9. (In Press)

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Abstract

The dominant paradigm for countering misinformation prioritizes computational detection, classification, and automated fact-checking. This paper argues that such approaches rest on an unexamined epistemic assumption that human critical capacity remains stable and sufficient to interpret, verify, and govern algorithmic outputs. We identify a structural blind spot in this paradigm, particularly salient in educational settings, where increasing reliance on generative artificial intelligence risks eroding the very epistemic capacities required for effective human–AI collaboration. To make this claim precise, we develop an epistemic modal logic framework that demonstrates the insufficiency of purely computational defenses to guarantee critical understanding in human agents. We conclude that technical defenses are necessarily contingent on prior educational investment in human epistemic virtues, reframing misinformation defense as a problem of socio-cognitive-technical resilience rather than algorithmic optimization alone.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Health Computing Faculty of Science > Research Groups > Data Science and AI Faculty of Science > Research Groups > Cyber Intelligence and Networks
Depositing User:	LivePure Connector
Date Deposited:	25 Feb 2026 12:30
Last Modified:	26 Feb 2026 00:54
URI:	https://ueaeprints.uea.ac.uk/id/eprint/102055
DOI:	10.1145/3774905.3796493

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