Humanities Ethics Review Boards Strain Under Proliferation of Generative AI Research Tools

Research ethics committees across South African universities have introduced stringent audit measures for doctoral dissertations utilizing generative AI and automated language models. The widespread adoption of AI software for qualitative coding, interview transcription, and ethnographic literature synthesis has created complex ethical dilemmas, particularly regarding participant confidentiality, indigenous knowledge systems, and intellectual attribution. Under newly circulated institutional guidelines, SSH candidates must submit granular AI transparency statements detailing all external algorithmic tools used throughout data collection and manuscript preparation. While several computational humanities candidates have praised the productivity gains AI offers for managing vast multi-lingual datasets, supervisors warn of widespread algorithmic bias and hallucinations in non-Western historical and linguistic contexts. Furthermore, research boards caution that uncritical reliance on proprietary commercial models risks compromising sensitive field interviews, necessitating rigorous institutional training in ethical digital scholarship.