Exploring ethical considerations in medical research: Harnessing pre-generated transformers for AI-powered ethics discussions

Abstract

INTRODUCTION: In medical research involving human subjects, ethical review is essential to protect individuals. However, concerns have been raised about variations in ethical review opinions and a decline in review quality. Adequately protecting human subjects requires multifaceted opinions from ethics committee members. Despite the need to increase the number of committee members, resources are limited. To address these challenges, we explored the use of a generative pre- learning transformer, an interactive artificial intelligence (AI) tool, to discuss ethical issues in medical research. METHODS: The generation AI used in the research used ChatGPT3.5, which has learned ethical guidelines from various countries worldwide. We requested the generative AI to provide insights on ethical considerations for virtual research involving individuals. The obtained answers were documented and verified by experts. RESULTS: The AI successfully highlighted considerations for informed consent regarding individuals with dementia and mental illness, as well as concerns about invasiveness in research. It also raised points about potential side effects of off-label drug use. However, it could not offer specific measures for psychological considerations or broader ethical issues, providing limited ethical insights. This limitation may be attributed to biased opinions resulting from machine learning optimization, preventing comprehensive identification of certain ethical issues. CONCLUSION: Although the validity of ethical opinions generated by the generative AI requires further examination, our findings suggest that this technology could be employed to prompt reviews and re-evaluate ethical concerns arising in research.

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