Who Acts, Who Knows, Who Answers? A Corpus-Assisted Discourse Analysis of Agency, Epistemic Responsibility, and Accountability in Generative AI Higher Education Research

arXiv:2609.27184v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) is increasingly described in higher education as a tool, collaborator, evaluator, proxy, and infrastructure. These labels are not neutral: they shape who is seen as acting, knowing, and, crucially, being answerable when someone uses AI. This study examines how scholars distribute such responsibility across 366 English-language titles and abstracts published between November 2022 and 14 August 2026. A corpus-assisted discourse analysis combined frequency counts, five-word collocations, actor-predicate associations, obligation-clause coding, and heuristic analysis of passives, nominalisations, and reporting metonymies. The final corpus contained 91,405 tokens, drawn from 8,734 unique records screened after deduplication. AI was the most frequently named actor, appearing 2,050 times and entering 447 predicate associations, most involving action. Students, by contrast, were more often associated with knowing, judging, and verifying, yet no sentence ever made AI explicitly responsible. Responsibility fell largely on educators, institutions, and policy, or disappeared through passive and nominalised constructions. Even frequent phrases such as "responsible AI" and "responsible use" rarely identify who is accountable for what. The findings reveal a persistent gap between giving AI functional agency and assigning normative accountability.

Study reveals gap between AI agency and accountability

This study finds that generative AI is frequently attributed agency but not responsibility, which obscures accountability in higher education. The diffusion of responsibility to educators, institutions, or policy and the lack of clear AI accountability may create governance and ethical risks. However, it is an analysis of discourse rather than direct evidence of harm or benefit, so the dystopian impact is moderate and speculative.

This is a linguistic/discourse study about how researchers write about AI, not a direct claim about AI's societal effects. It implies a governance concern (accountability gaps) but is descriptive and meta-level, warranting a mild negative lean with low-moderate confidence.

The study reveals a concerning pattern in academic discourse where AI is frequently described as an actor while accountability is diffused or absent. This gap between AI's perceived agency and clear human responsibility suggests a systemic risk of harm, particularly in education. The findings are based on robust corpus analysis.

The study highlights a significant disconnect between the agency attributed to AI and the lack of clear accountability. This could lead to ethical and practical issues in higher education. The lack of explicit responsibility assigned to AI suggests potential risks in understanding and managing AI's role.

SOURCE     arXiv cs.CY (Computers and Society) (tier 1)
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DOCUMENT   4dd6bc36-4c2f-421f-9e95-490ac2c8a2e6
           https://arxiv.org/abs/2609.27184
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EVIDENCE   3 extracted excerpts
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MODEL RUN  5 runs, methodology 1.0.1
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SCORE      -61  (Adverse)
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CONFIDENCE 75%