Research Integrity and Academic Authority in the Age of Artificial Intelligence: From Discovery to Curation?
Simon Chesterman, Loy Hui Chieh

TL;DR
AI is transforming research practices, creating new challenges for integrity and authority, which universities can address by emphasizing judgment, transparency, and ethical oversight to maintain credibility in an AI-driven knowledge environment.
Contribution
This paper analyzes how AI impacts research integrity and academic authority, proposing strategies for universities to preserve credibility amidst proprietary and opaque AI systems.
Findings
AI accelerates discovery and reorganizes scholarly labor.
Generative models introduce epistemic vulnerabilities.
Universities can maintain authority through judgment, transparency, and ethical oversight.
Abstract
Artificial intelligence is reshaping the organization and practice of research in ways that extend far beyond gains in productivity. AI systems now accelerate discovery, reorganize scholarly labour, and mediate access to expanding scientific literatures. At the same time, generative models capable of producing text, images, and data at scale introduce new epistemic and institutional vulnerabilities. They exacerbate challenges of reproducibility, blur lines of authorship and accountability, and place unprecedented pressure on peer review and editorial systems. These risks coincide with a deeper political-economic shift: the centre of gravity in AI research has moved decisively from universities to private laboratories with privileged access to data, compute, and engineering talent. As frontier models become increasingly proprietary and opaque, universities face growing difficulty…
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Taxonomy
TopicsDigital Education and Society · Ethics and Social Impacts of AI · Academic Publishing and Open Access
