Meaningful Participation in AI-Mediated Clinical Trial Recruitment. - Subrahmanyam, Vishnu; Bailar, Melissa; Ostherr, Kirsten; Kostick-Quenet, Kristin Marie; McGuire, Amy L.; Alexander Neitzke-Spruill, Logan; Rahimzadeh, Vasiliki (American Journal of Bioethics, 2026)
This article examines the ethical dimensions of artificial intelligence (AI)-enabled clinical trial recruitment, focusing on how meaningful participation can be preserved within AI-mediated processes. It argues that while AI systems optimize recruitment by predicting eligible and efficient participants, this efficiency-driven approach risks marginalizing participants by reducing complex human experiences to enrollment and retention metrics. The authors propose that meaningful participation involves recognizing participants’ ongoing capacity to interpret and negotiate their involvement, addressing structural inequalities embedded in trial design, and ensuring participant agency over data use. They recommend ethical frameworks that incorporate support for retention-risk participants, transparency about AI use in recruitment, and mechanisms for participants to express concerns beyond standardized metrics, aiming to maintain the relational and human aspects of clinical trial participation.