Defining Ethical AI in Nursing: A Concept Analysis Grounded in Accountability, Explainability, Privacy, and Justice

Abstract

The rapid integration of artificial intelligence (AI) into nursing practice offered transformative potential to enhance clinical processes, improve patient outcomes, and optimize workflows. However, the ethical challenges posed by AI technologies have outpaced the development of corresponding nursing frameworks. This concept analysis articulates a contemporary definition of AI‐integrated nursing ethics and presents its defining attributes through Walker and Avant’s eight‐step analytical framework. The analysis identified four core attributes that align with the ethical principles of nursing and operational attributes of AI: (1) nurses must maintain responsibility for clinical decisions even when AI recommendations are involved; (2) a privacy impact assessment of AI systems should be conducted regularly to evaluate potential risks and continually enhance information protection; (3) nurses must be able to understand and communicate AI system recommendations and the reasoning processes; and (4) nurses must identify and address AI‐related bias to advocate for equitable care, while AI systems should be programmed to incorporate social and cultural aspects. Collectively, these attributes position AI‐integrated nursing ethics to enhance nurses’ ethical judgment and clinical expertise. The findings also emphasize the necessity of advancing nursing practice, research, policy, and education for responsible AI integration. Recommendations include developing evidence‐based guidelines, updating institutional explainability policies, integrating AI ethics into nursing curricula, and further research on bias mitigation. By addressing these areas, the nursing profession can ensure that AI integration aligns with its core ethical principles, enhancing patient care while preserving the integrity of nursing judgment.

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