RECONCEPTUALIZING RESEARCH ETHICS IN THE AI ERA: A SYSTEMATIC REVIEW FRAMING GENAI AS AN EMERGING RISK
TL;DR
This systematic review explores qualitative research ethics by framing GenAI as a new vulnerability layered over traditional principles such as participant autonomy, non-maleficence, researcher positionality, and institutional oversight, and recommends targeted strategies tailored to each research context.
Abstract
Integrating Generative Artificial Intelligence (GenAI) into qualitative research offers new operational advantages but also raises important ethical concerns. Viewing GenAI in isolation risks oversimplifying research ethics as just technical compliance. This systematic review explores qualitative research ethics by framing GenAI as a new vulnerability layered over traditional principles such as participant autonomy, non-maleficence, researcher positionality, and institutional oversight. Analyzing 18 key studies from global, African, and East African sources using PRISMA guidelines, the review reveals how GenAI worsens existing structural inequalities. Global studies mainly address data privacy and algorithmic transparency, while African and East African research emphasize how LLMs amplify historical issues like digital neo-colonialism, cultural extraction, and the marginalization of indigenous languages. To manage these complex ethical challenges, we recommend targeted strategies tailored to each research context, including a Human-in-the-Loop (HITL) framework based on Afro-communitarian ethics (Ubuntu).
