Large Language Models in Informed Consent - Opportunities, Evidence, and Challenges

Rishabh Goel, B.A., B.S., Sammy Mustafa, M.S., Trevor J. Baker, M.S., and Barbara E. Bierer, M.D.
Abstract
Informed consent forms (ICFs) are foundational to ethical clinical research consent, yet they remain lengthy, cognitively demanding, and written at reading levels that are not comprehensible to most participants. Recent advances in artificial intelligence, particularly large language models (LLMs), offer new opportunities to improve clarity, comprehension, accessibility, and participant engagement throughout the consent process. In this narrative review, the authors map the emerging landscape of LLM applications for ICFs across seven domains: glossary generation, plain language revisions, visual aid generation, accessibility and document formatting, translation into other languages, teach-back and comprehension validation, and interactive chat-based consent. The authors conclude by outlining considerations for their proper usage and integration with research and ethical review frameworks.

Large Language Models in Informed Consent - Opportunities, Evidence, and Challenges