Meaningful Participation in AI-Mediated Clinical Trial Recruitment.

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 participa...

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Publicado en:American Journal of Bioethics Vol. 26; no. 8; pp. 56 - 60
Autores principales: Subrahmanyam, Vishnu, Bailar, Melissa, Ostherr, Kirsten, Kostick-Quenet, Kristin Marie, McGuire, Amy L., Alexander Neitzke-Spruill, Logan, Rahimzadeh, Vasiliki
Formato: commentary Journal Article
Publicado: Taylor & Francis Ltd Aug2026
Acceso en línea:Ver este registro en EBSCOhost
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          Subrahmanyam, Vishnu
          Bailar, Melissa
          Ostherr, Kirsten
          Kostick-Quenet, Kristin Marie
          McGuire, Amy L.
          Alexander Neitzke-Spruill, Logan
          Rahimzadeh, Vasiliki
        affil: The University of Texas Medical Branch at Galveston
      sug:
        subj:
          Clinical Trials Ethical Issues
          Research Subject Recruitment Ethical Issues
          Patient Selection Ethical Issues
          Artificial Intelligence Ethical Issues
          Patient Participation
          Research Ethics
          Research Subject Retention
      ab: 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.
      pubtype: Academic Journal
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        commentary
        Journal Article
      ougenre: Article
    language: English
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