Should Artificial Intelligence be used to support clinical ethical decision-making? A systematic review of reasons.

Decision support systems, clinical Decision-making, artificial intelligence Ethics, Clinical Systematic review

Journal

BMC medical ethics
ISSN: 1472-6939
Titre abrégé: BMC Med Ethics
Pays: England
ID NLM: 101088680

Informations de publication

Date de publication:
06 07 2023
Historique:
received: 06 03 2023
accepted: 28 06 2023
medline: 10 7 2023
pubmed: 7 7 2023
entrez: 6 7 2023
Statut: epublish

Résumé

Healthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinical ethical decision-making. However, the use of such tools is controversial. This review aims to provide a comprehensive overview of the reasons given in the academic literature for and against their use. PubMed, Web of Science, Philpapers.org and Google Scholar were searched for all relevant publications. The resulting set of publications was title and abstract screened according to defined inclusion and exclusion criteria, resulting in 44 papers whose full texts were analysed using the Kuckartz method of qualitative text analysis. Artificial Intelligence might increase patient autonomy by improving the accuracy of predictions and allowing patients to receive their preferred treatment. It is thought to increase beneficence by providing reliable information, thereby, supporting surrogate decision-making. Some authors fear that reducing ethical decision-making to statistical correlations may limit autonomy. Others argue that AI may not be able to replicate the process of ethical deliberation because it lacks human characteristics. Concerns have been raised about issues of justice, as AI may replicate existing biases in the decision-making process. The prospective benefits of using AI in clinical ethical decision-making are manifold, but its development and use should be undertaken carefully to avoid ethical pitfalls. Several issues that are central to the discussion of Clinical Decision Support Systems, such as justice, explicability or human-machine interaction, have been neglected in the debate on AI for clinical ethics so far. This review is registered at Open Science Framework ( https://osf.io/wvcs9 ).

Sections du résumé

BACKGROUND
Healthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinical ethical decision-making. However, the use of such tools is controversial. This review aims to provide a comprehensive overview of the reasons given in the academic literature for and against their use.
METHODS
PubMed, Web of Science, Philpapers.org and Google Scholar were searched for all relevant publications. The resulting set of publications was title and abstract screened according to defined inclusion and exclusion criteria, resulting in 44 papers whose full texts were analysed using the Kuckartz method of qualitative text analysis.
RESULTS
Artificial Intelligence might increase patient autonomy by improving the accuracy of predictions and allowing patients to receive their preferred treatment. It is thought to increase beneficence by providing reliable information, thereby, supporting surrogate decision-making. Some authors fear that reducing ethical decision-making to statistical correlations may limit autonomy. Others argue that AI may not be able to replicate the process of ethical deliberation because it lacks human characteristics. Concerns have been raised about issues of justice, as AI may replicate existing biases in the decision-making process.
CONCLUSIONS
The prospective benefits of using AI in clinical ethical decision-making are manifold, but its development and use should be undertaken carefully to avoid ethical pitfalls. Several issues that are central to the discussion of Clinical Decision Support Systems, such as justice, explicability or human-machine interaction, have been neglected in the debate on AI for clinical ethics so far.
TRIAL REGISTRATION
This review is registered at Open Science Framework ( https://osf.io/wvcs9 ).

Identifiants

pubmed: 37415172
doi: 10.1186/s12910-023-00929-6
pii: 10.1186/s12910-023-00929-6
pmc: PMC10327319
doi:

Types de publication

Systematic Review Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

48

Informations de copyright

© 2023. The Author(s).

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Auteurs

Lasse Benzinger (L)

Institute for Ethics, History and Philosophy of Medicine, Hannover Medical School (MHH), Carl-Neuberg-Str. 1, 30625, Hannover, Germany. benzinger.lasse@mh-hannover.de.

Frank Ursin (F)

Institute for Ethics, History and Philosophy of Medicine, Hannover Medical School (MHH), Carl-Neuberg-Str. 1, 30625, Hannover, Germany.

Wolf-Tilo Balke (WT)

Institute for Information Systems, TU Braunschweig, Braunschweig, Germany.

Tim Kacprowski (T)

Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of Technische Universität Braunschweig and Hannover Medical School, Braunschweig, Germany.
Braunschweig Integrated Centre for Systems Biology (BRICS), TU Braunschweig, Braunschweig, Germany.

Sabine Salloch (S)

Institute for Ethics, History and Philosophy of Medicine, Hannover Medical School (MHH), Carl-Neuberg-Str. 1, 30625, Hannover, Germany.

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