Epistemic Drift and the Academic Boundary under AI-Mediated Judgment
Year: 2026
Type: article
Abstract: Academic disciplines provide the primary frameworks through which new technologies are interpreted, evaluated, and governed. Under AI-mediated language interaction, a distinct epistemic drift has emerged: judgment-shaping influence is distributed across scientific, technical, and humanistic domains, yet no single discipline fully claims or governs it. This paper identifies how disciplinary fragmentation obscures the epistemic object of AI-mediated judgment formation, leading to gaps in academic accountability without error or misconduct. Drawing on philosophy of science, judgment theory, human–AI interaction, and AI safety research, the paper argues that the challenge is not a lack of knowledge, but a misplacement of epistemic boundaries. Correcting this placement is a prerequisite for stable, non-moralised academic engagement with AI-mediated systems.
Author: Gavaza, Victoria
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7128027342
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