[2603.20214] Beyond Detection: Governing GenAI in Academic Peer Review as a Sociotechnical Challenge

Computer Science > Computers and Society arXiv:2603.20214 (cs) [Submitted on 2 Mar 2026] Title:Beyond Detection: Governing GenAI in Academic Peer Review as a Sociotechnical Challenge Authors:Tatiana Chakravorti, Pranav Narayanan Venkit, Sourojit Ghosh, Sarah Rajtmajer View a PDF of the paper titled Beyond Detection: Governing GenAI in Academic Peer Review as a Sociotechnical Challenge, by Tatiana Chakravorti and 3 other authors View PDF HTML (experimental) Abstract:Generative AI tools are increasingly entering academic peer review workflows, raising questions about fairness, accountability, and the legitimacy of evaluative judgment. While these systems promise efficiency gains amid growing reviewer overload, their use introduces new sociotechnical risks. This paper presents a convergent mixed-method study combining discourse analysis of 448 social media posts with interviews with 14 area chairs and program chairs from leading AI and HCI conferences to examine how GenAI is discussed and experienced in peer review. Across both datasets, we find broad agreement that GenAI may be acceptable for limited supportive tasks, such as improving clarity or structuring feedback, but that core evaluative judgments, assessing novelty, contribution, and acceptance, should remain human responsibilities. At the same time, participants highlight concerns about epistemic harm, over-standardization, unclear responsibility, and adversarial risks such as prompt injection. User interviews reveal ...