Evidence map›Paper›PMID 38983845›Full record

ArticleJAMIA open2024

Evaluating ChatGPT's moral competence in health care-related ethical problems.

Ahmed A Rashid, Ryan A Skelly, Carlos A Valdes, Pruthvi P Patel, Lauren B Solberg, Christopher R Giordano, François Modave

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Article in JAMIA open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ahmed A RashidDepartment of Anesthesiology, University of Florida College of Medicine, Gainesville, FL 32608, United States.
Ryan A SkellyDepartment of Anesthesiology, University of Florida College of Medicine, Gainesville, FL 32608, United States.
Carlos A ValdesDepartment of Surgery, University of Florida College of Medicine, Gainesville, FL 32608, United States.
Pruthvi P PatelDepartment of Research, Alabama College of Osteopathic Medicine, Dothan, AL 36303, United States.
Lauren B SolbergDepartment of Community Health and Family Medicine, University of Florida College of Medicine, Gainesville, FL 32608, United States.
Christopher R GiordanoDepartment of Anesthesiology, University of Florida College of Medicine, Gainesville, FL 32608, United States.
François ModaveDepartment of Anesthesiology, University of Florida College of Medicine, Gainesville, FL 32608, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Artificial intelligence tools such as Chat Generative Pre-trained Transformer (ChatGPT) have been used for many health care-related applications; however, there is a lack of research on their capabilities for evaluating morally and/or ethically complex medical decisions. The objective of this study was to assess the moral competence of ChatGPT. Materials and methods: This cross-sectional study was performed between May 2023 and July 2023 using scenarios from the Moral Competence Test (MCT). Numerical responses were collected from ChatGPT 3.5 and 4.0 to assess individual and overall stage scores, including C-index and overall moral stage preference. Descriptive analysis and 2-sided Student's Results: A total of 100 iterations of the MCT were performed and moral preference was found to be higher in the latter Kohlberg-derived arguments. ChatGPT 4.0 was found to have a higher overall moral stage preference (2.325 versus 1.755) when compared to ChatGPT 3.5. ChatGPT 4.0 was also found to have a statistically higher C-index score in comparison to ChatGPT 3.5 (29.03 ± 11.10 versus 19.32 ± 10.95, Discussion: ChatGPT 3.5 and 4.0 trended towards higher moral preference for the latter stages of Kohlberg's theory for both dilemmas with C-indices suggesting medium moral competence. However, both models showed moderate variation in C-index scores indicating inconsistency and further training is recommended. Conclusion: ChatGPT demonstrates medium moral competence and can evaluate arguments based on Kohlberg's theory of moral development. These findings suggest that future revisions of ChatGPT and other large language models could assist physicians in the decision-making process when encountering complex ethical scenarios.

Indexed as

artificial intelligenceclinical decision-makingethicsjudgementmorals

Identifiers

PMID38983845
PMCPMC11233145

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.