AI Usage in Academic Writing: Perspectives of Stakeholders - Aliakbari, Mohammad; Barzan, Pooria; Allahveysi, Seyyed Pedram (AI and Tech in Behavioral and Social Sciences, 2026)
This qualitative study examines the complex attitudes, ethical considerations, and practical implications of integrating artificial intelligence (AI) in academic writing across key stakeholder groups, including university professors and students. Using semi-structured interviews with 40 participants (20 students and 20 faculty members) from diverse disciplines and institutional contexts, the research reveals divergent perspectives on AI’s role in academia. Faculty respondents expressed significant concerns about academic integrity, erosion of critical thinking, and the limitations of AI detection tools, which frequently misidentify human-written text as AI-generated. Conversely, students viewed AI as an essential productivity tool for overcoming writer’s block, refining ideas, and managing workload, though they acknowledged ethical ambiguities in its deployment. A critical tension emerged between AI’s perceived benefits—enhanced efficiency, personalized feedback, and accessibility—and its risks, including algorithmic bias, surveillance culture, and threats to student agency. Stakeholders agreed that institutional policies lag behind technological adoption, with current frameworks inadequately addressing transparency, data privacy, or equitable implementation. The study also identifies disciplinary variances: STEM educators favored AI for technical drafting, while humanities faculty emphasized its threat to authentic voice development. The findings advocate for a collaborative, multi-stakeholder approach to AI governance, emphasizing pedagogical redesign, ethical guidelines for explainable AI, and professional development to bridge digital literacy gaps. This research underscores the urgency of reimagining academic writing in the AI era, balancing innovation with the preservation of core educational values.