Recruitment Inference Creep: Why AI in Clinical Trials Needs Auditable Ethical Limits. - Ruiz-Vanoye, Jorge A.; Díaz-Parra, Ocotlán; Aguilar-Ortiz, Jaime; Ruiz-Jaimes, Miguel A.; Toledo-Navarro, Yadira; Fuentes-Penna, Alejandro; Barrera-Cámara, Ricardo A.; Trejo-Macotela, Francisco Rafael (American Journal of Bioethics, 2026)
The article focuses on the ethical considerations of artificial intelligence (AI)-enabled recruitment in clinical research, emphasizing the distinction between AI systems that identify eligible participants and those that optimize the likelihood of participant enrollment. While AI can improve recruitment efficiency and accuracy, ethical concerns arise when AI shifts from eligibility detection to behavioral persuasion, potentially exploiting vulnerabilities before informed consent is obtained. The authors highlight the concept of "recruitment inference creep," where AI infers sensitive psychological or social traits to influence participation decisions, raising risks to deliberative autonomy. They advocate for institutional review boards (IRBs) to govern not only data access but also the scope of AI inferences and persuasive strategies, ensuring recruitment respects voluntary participation without manipulating prospective participants.