Embedded transparency in artificial intelligence: a prerequisite for equity and representation in AI-enabled clinical trials.
Where this comes from
- Record sourced from PubMed, PMID 42436283.
- Also identified by DOI 10.1038/s41746-026-02987-7 and PMC identifier 13356023.
- Licence recorded as CC BY-NC-ND.
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Abstract
Artificial intelligence is being embedded in clinical trial infrastructure, shaping who is identified, stratified, and analysed. Opaque models risk amplifying existing disparities in the evidence base. We argue that <i>embedded transparency</i>, the structural integration of <i>ex ante</i> interpretability, demographic auditability, documented uncertainty handling, and stakeholder-relative explanation, is a necessary, though not sufficient, condition for equitable AI-enabled trials, and propose governance recommendations actionable across regulatory regimes.