The ethics of non-explainable artificial intelligence: an overview for clinical nurses.

Abstract

Artificial intelligence (AI) is transforming healthcare by enhancing clinical decision-making, particularly in nursing, where it supports tasks such as diagnostics, risk assessments, and care planning. However, the integration of non-explainable AI (NXAI) - which operates without fully transparent, interpretable mechanisms - presents ethical challenges related to accountability, autonomy, and trust. While explainable AI (XAI) aligns well with nursing's bioethical principles by fostering transparency and patient trust, NXAI's complexity offers distinct advantages in predictive accuracy and efficiency. This article explores the ethical tensions between XAI and NXAI in nursing, advocating a balanced approach that emphasises outcome validation, shared accountability, and clear communication with patients. By focusing on patient-centred, ethically sound frameworks, it is argued that nurses can integrate NXAI into practice, addressing challenges and preserving core nursing values in a rapidly evolving digital landscape.