Epistemic Drift and the Academic Boundary under AI-Mediated Judgment

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.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-05
DOI
https://doi.org/10.5281/zenodo.18489344
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Epistemic Drift and the Academic Boundary under AI-Mediated Judgment

Victoria Gavaza
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Epistemic Drift and the Academic Boundary under AI-Mediated Judgment

Victoria Gavaza
article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 67%
Ethics and Social Impacts of AI
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