1. Development of Application-Specific Large Language Models to Facilitate Research Ethics Review
- Author
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Mann, Sebastian Porsdam, Jiehao, Joel Seah, Latham, Stephen R., Savulescu, Julian, Aboy, Mateo, and Earp, Brian D.
- Subjects
Computer Science - Computation and Language ,Computer Science - Computers and Society - Abstract
Institutional review boards (IRBs) play a crucial role in ensuring the ethical conduct of human subjects research, but face challenges including inconsistency, delays, and inefficiencies. We propose the development and implementation of application-specific large language models (LLMs) to facilitate IRB review processes. These IRB-specific LLMs would be fine-tuned on IRB-specific literature and institutional datasets, and equipped with retrieval capabilities to access up-to-date, context-relevant information. We outline potential applications, including pre-review screening, preliminary analysis, consistency checking, and decision support. While addressing concerns about accuracy, context sensitivity, and human oversight, we acknowledge remaining challenges such as over-reliance on AI and the need for transparency. By enhancing the efficiency and quality of ethical review while maintaining human judgment in critical decisions, IRB-specific LLMs offer a promising tool to improve research oversight. We call for pilot studies to evaluate the feasibility and impact of this approach., Comment: 11 pages, 0 figures
- Published
- 2025