Preventing Ethical Asymmetries: AI-Driven Decision-Aids for Prospective Participants in Clinical Research.
The article focuses on the ethical and practical challenges of using artificial intelligence (AI) in clinical trial recruitment, emphasizing the need to address informational and ethical asymmetries between researchers and potential participants. It highlights that while AI can improve recruitment e...
| Publicado en: | American Journal of Bioethics Vol. 26; no. 8; pp. 40 - 43 |
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| Autores principales: | , , , |
| Formato: | commentary Journal Article |
| Publicado: |
Taylor & Francis Ltd
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195895378&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195895378 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15265161 FKZ jtl: American Journal of Bioethics issn: 15265161 maglogo: N pubinfo: dt: Aug2026 vid: 26 iid: 8 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 195895378 195895378 195895378 10.1080/15265161.2026.2690930 195895378 ppf: 40 ppct: 3 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Preventing Ethical Asymmetries: AI-Driven Decision-Aids for Prospective Participants in Clinical Research. aug: au: Buchholz, Oliver Meier, Lukas J. Ranisch, Robert Salloch, Sabine affil: ETH Zurich sug: subj: Artificial Intelligence Utilization Patient Selection Clinical Research Clinical Trials Research Ethics Research Subject Recruitment Artificial Intelligence Ethical Issues Patient Participation Institutional Review Bioethics ab: The article focuses on the ethical and practical challenges of using artificial intelligence (AI) in clinical trial recruitment, emphasizing the need to address informational and ethical asymmetries between researchers and potential participants. It highlights that while AI can improve recruitment efficiency and trial matching, participants often lack sufficient knowledge about trials and AI tools, which may exacerbate existing disparities and hinder informed decision-making. The authors advocate for the development of independent, participant-centered AI tools that incorporate individuals’ values and preferences to support value-concordant trial matching and informed consent. They also stress that AI integration in recruitment should be accompanied by normative reflection to avoid reducing participants to mere data points and to ensure ethical alignment with participants’ interests. pubtype: Academic Journal doctype: commentary Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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