Summary: This article explores AI decision aids for clinical ethics with an academic and normative lens. It synthesizes case retrieval, policy summarization, stakeholder mapping and nursing roles in ethics deliberation.

Clinical ethics consultations require rapid synthesis of precedent, institutional policy and patient values. AI can surface relevant cases, summarize policies, and map stakeholders to support ethics committees and bedside nurses, but must not replace human moral reasoning.

Technically systems use retrieval augmented generation constrained by institutional policy corpora, case similarity metrics, and structured elicitation templates for patient values. Safety and governance require provenance, transparency, and human in the loop review. Validation is qualitative: usability with ethics committees, concordance with expert recommendations, and assessment of decision quality.

Guidance: For ethics teams and nursing leaders: use AI as a preparatory tool to surface relevant materials, require explicit human deliberation for recommendations, document provenance and rationale, train nurses in interpreting AI summaries, and include ethics oversight in procurement.

Conclusion: AI can accelerate ethics consultation preparation and broaden access to precedent when used transparently with human deliberation and governance.

Final Summary: AI ethics support retrieves cases and summarizes policy to aid human deliberation. Priorities: provenance, human oversight, training, and governance.

Useful Facts: AI surfaces precedent but cannot decide ethical questions; Provenance is essential for trust; Nurses play key roles in values elicitation; Governance prevents misuse; Qualitative validation guides adoption

Related Topics: bioethics | clinical governance | nursing leadership case retrieval; policy summarization; stakeholder mapping; provenance; human oversight