Vollständiger Abstract
Worum geht es in dieser Arbeit?
Abstract Health systems are adopting AI-powered tools faster than policy can address the implications for clinician liability. Nurses, as the largest healthcare profession and the most proximal clinicians to patients, must decide whether to accept, modify, or override AI-derived recommendations, often while managing competing cognitive demands. Yet the question of who bears responsibility when AI contributes to patient harm remains unresolved in policy and case law. At the 2025 American Medical Informatics Association Annual Symposium, a structured debate examined whether nurses should be held liable for AI-assisted clinical decisions. Proponents argued that professional ethics, existing tort precedent, and the nurse's role as human-in-the-loop require accountability. Opponents countered that AI opacity, unfair liability distribution, and limited nurse agency in AI procurement preclude fair responsibility assignment. Two reforms are essential: meaningful nurse engagement throughout the AI lifecycle and nursing-specific considerations in AI legislation and regulatory frameworks.
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Meghan Reading Turchioe, Ann Wieben, Carolyn Sun, Christina Baker, Benjamin J Galatzan
- Quelle
- Health Affairs Scholar
- Publikation
- 2026-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 2976-5390
- Zitationen
- 0 laut Crossref
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Zitierfähiger Nachweis
Meghan Reading Turchioe, Ann Wieben, Carolyn Sun, Christina Baker, Benjamin J Galatzan (2026). When Nurses Are Held Accountable for AI-Driven Clinical Decisions, They Must Be Engaged Early and Meaningfully. Health Affairs Scholar. https://doi.org/10.1093/haschl/qxag218
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