Towards Ethical AI Adoption in Academic Research: Insights from a Systematic Literature Review

Abstract

Artificial intelligence (AI) is being increasingly integrated in academic research with notable improvement in efficiency while simultaneously raising ethical concerns such as bias, transparency, accountability, and integrity. While current studies examine these issues in isolation, there is a lack of unified research connecting everyday research practices, university policies, and AI‑ethics tools. To fill this gap, we aim to synthesize ethical challenges of AI-assisted research from scientific, institutional, and technical perspectives. By conducting a systematic literature review of 16 peer-reviewed studies using predefined selection criteria to identify trends, themes, and research gaps, it was found that publications on AI ethics have grown rapidly since 2023, largely linked to generative AI with key concerns clustered around bias, explainability, accountability, and data privacy. In contrast, research on higher education policy and practical ethics tools remains limited. The adoption of responsible AI in research will require stronger institutional policies, cross-disciplinary frameworks, and the creation of accessible and practical ethics tools.