Developing the HAKI model as a conceptual framework for AI-assisted academic research

Abstract

The rapid adoption of artificial intelligence (AI) in academia has transformed knowledge production while raising critical questions regarding authorship, academic integrity, and ethical responsibility. Despite the growing integration of AI into research practices, there remains a lack of conceptual frameworks that clearly define the boundaries of ethical human–AI collaboration in academic research. Addressing this gap, the present study explores academics’ perceptions of AI through semi-structured interviews with 131 faculty members from Iranian and Canadian universities representing diverse academic disciplines. The interview data were analyzed using thematic analysis. The findings indicate that although AI enhances research efficiency and supports various stages of the research process, participants expressed significant concerns regarding algorithmic bias, academic integrity, transparency, and the potential erosion of scholarly voice and intellectual ownership. A dominant finding was the perceived need for a structured framework to guide the ethical integration of AI into academic research. In response, this study proposes the HAKI framework, a conceptual model that emphasizes human oversight, transparency, critical interpretation, and recursive verification to support responsible AI-assisted knowledge production. As a conceptual contribution, the HAKI framework is intended to provide a theoretical foundation for future empirical investigation rather than a validated operational model. The study further highlights the importance of institutional governance, ethical guidelines, and AI literacy initiatives to facilitate responsible AI adoption in higher education and scholarly research.