Ethics consultants’ perspectives on the use of artificial intelligence in ethical decision-making for patients incapacitated with no evident advance directives or surrogates: a qualitative study

Abstract

As artificial intelligence (AI) tools are increasingly integrated into healthcare settings, their application to ethically complex care decisions for patients who lack decision-making capacity and identifiable surrogates remains largely unexplored. This study explored ethics consultants’ perspectives on the use of artificial intelligence (AI) in ethical and clinical decision-making for patients who are incapacitated with no evident advance directives or surrogates (INEADS). We conducted a qualitative study using in-depth semi-structured interviews with 19 ethics consultants across nine U.S. states, analyzed using thematic analysis. Three themes were generated. Theme 1, Human Accountability as a Non-Negotiable Boundary, captured ethical concerns including clinician accountability, AI’s inability to capture individual context, and algorithmic bias risk. Theme 2, Designing AI That Reflects the Complexity of INEADS Care, identified requirements for high-quality training data, interdisciplinary development teams, and explainability. Theme 3, A Conditional and Constructive Vision for AI as Supportive Tool, described applications encompassing surrogate identification, goals-of-care facilitation, longitudinal decisional pattern review, and individualized prognostication. Participants framed AI as a resource to support rather than replace human moral judgment, raised concerns about algorithmic bias and institutional variation, and articulated a constructive vision grounded in prior natural language processing work identifying INEADS patients across care settings. Ethics consultants expressed conditional acceptance of AI in INEADS care when used to support, not replace, accountable human judgment. Findings highlight the need for equity-centered design, transparent communication of data limitations, interdisciplinary development, and ethics consultant involvement in validation before clinical implementation.