REDEFINING ACADEMIC INTEGRITY IN THE AGE OF AI: CHALLENGES AND REMEDIES IN INDIAN HIGHER EDUCATION

Abstract

The rise of generative artificial intelligence (AI) has notably transformed higher education practices, raising complex issues around academic integrity, authorship, and ethical scholarship. Unlike previous digital tools, generative AI can independently generate academically credible texts, challenging traditional ideas of originality and student agency. This paper examines the evolution of the concept of academic integrity in AI-enabled learning, particularly within Indian higher education. Drawing on interdisciplinary perspectives from educational ethics, sociology, learning sciences, and AI studies, it analyses integrity-related dilemmas influenced by factors like large enrolments, exam-focused cultures, linguistic diversity, varying AI literacy, and socio-economic gaps. The research argues that current compliance-based integrity systems, mainly relying on plagiarism detection, are inadequate for handling AI-influenced academic work. Instead, it advocates for a learning-focused redefinition of integrity emphasizing transparency, epistemic responsibility, critical thinking, and demonstrable understanding. To support this, the paper suggests pedagogical and ethical strategies such as redesigning assessments to focus on reasoning and process, providing clear guidance on responsible AI use, developing critical AI literacy among faculty and students, and institutionalizing transparent AI-assisted academic practices. This work contributes to global discussions by highlighting AI-related integrity issues within the unique context of Indian higher education.