Autonomy, Trust, and Stewardship: Centering Participants in AI-Enabled Trial Matching. - Heidelberg, Melissa; Kultgen, Benjamin; Butler, Kelly K.; Bott, Nicholas T. (American Journal of Bioethics, 2026)
The article focuses on the ethical considerations and practical implications of using artificial intelligence (AI) as a tool for clinical research recruitment, specifically in trial matching and recruitment processes. It distinguishes between participant-to-trial matching, where individuals or clinicians seek relevant trials using AI tools, and trial-to-participant matching, where researchers or sponsors identify eligible participants through AI-enabled data analysis. The discussion emphasizes situating AI trial matching within a broader ecosystem involving data stewardship, institutional coordination, participant autonomy, and public trust, highlighting the importance of transparency, meaningful consent, fairness, and oversight. The article also notes the growing role of AI in accelerating trial enrollment, reducing costs, and potentially improving inclusivity in clinical research, while underscoring the need for responsible deployment aligned with bioethical principles and regulatory compliance.