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.

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Publication Details

Journal
AI and Ethics
Published
2026-08-24
DOI
https://doi.org/10.1007/s43681-026-01331-9
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Jiyoun Song, Aviv Y. Landau, Marsha Williamson, Robert Klitzman et al.
AI and Ethics
Artificial Intelligence in Healthcare and Education
article

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

Jiyoun Song, Aviv Y. Landau, Marsha Williamson, Robert Klitzman, Maxim Topaz, Bevin Cohen, Jingjing Shang
article en

Abstract

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.

AI and EthicsVol. 6(5)
Pace University (US), Columbia University (US), University of Pennsylvania (US), Philadelphia University (US), Icahn School of Medicine at Mount Sinai (US)
National Institute of Nursing Research
Peace, Justice and strong institutions
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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