Algorithmic Opacity, Clinical Justification, and the Duty of Candour in AI-Assisted Care
Hanan Ibrahim, Zack Hudson · 2026
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Description
Hanan Ibrahim and Zack Hudson write a 2026 ethics analysis of a collision between black-box medical AI and British doctors' legal duty to be candid after harm. AI tools now support NHS triage, diagnosis, and risk scoring, and the best performers are neural networks no clinician can interrogate at the bedside. The authors build their argument on a vignette: a sepsis case misclassified with AI assistance, after which the care team must explain what happened.
Their distinction is between clinical uncertainty, which candour duties already handle, and structural opacity, which destroys traceability of why a recommendation appeared. A clinician who cannot reconstruct the reasoning cannot discharge the statutory Duty of Candour or their professional accountability. The authors argue interpretability should count as a safety requirement in high-risk settings, not an optional extra traded against predictive scores. Deploying opaque systems there carries a presumption of ethical impermissibility.
Catalog record
| CREATOR | Hanan Ibrahim, Zack Hudson |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 30 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |