Evidence map›Paper›PMID 37898550›Full record

ArticleJournal of medical ethics2024

Consent-GPT: is it ethical to delegate procedural consent to conversational AI?

Jemima Winifred Allen, Brian D Earp, Julian Koplin, Dominic Wilkinson

Open access · hybridAbstract read
In one paragraph

Article in Journal of medical ethics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
24.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 55 citations in OpenAlex.

  1. Digital bioethics: exploring an emerging field.Medicine, health care, and philosophy · 2026
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  6. IsAI & society · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 3 countries.

Jemima Winifred AllenFaculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, Victoria, Australia.ORCID 0000-0002-3950-9950
Brian D EarpOxford Uehiro Centre for Practical Ethics, Faculty of Philosophy, University of Oxford, Oxford, UK.
Julian KoplinMonash Bioethics Centre, Monash University, Melbourne, Victoria, Australia.
Dominic WilkinsonOxford Uehiro Centre for Practical Ethics, Faculty of Philosophy, University of Oxford, Oxford, UK dominic.wilkinson@philosophy.ox.ac.uk.ORCID 0000-0003-3958-8633
University of Oxford · GBMonash University · AUNational University of Singapore · SG

Funding

Wellcome TrustWellcome Trust 203132/Z/16/Z
6 · The paper itself

Abstract

Obtaining informed consent from patients prior to a medical or surgical procedure is a fundamental part of safe and ethical clinical practice. Currently, it is routine for a significant part of the consent process to be delegated to members of the clinical team not performing the procedure (eg, junior doctors). However, it is common for consent-taking delegates to lack sufficient time and clinical knowledge to adequately promote patient autonomy and informed decision-making. Such problems might be addressed in a number of ways. One possible solution to this clinical dilemma is through the use of conversational artificial intelligence using large language models (LLMs). There is considerable interest in the potential benefits of such models in medicine. For delegated procedural consent, LLM could improve patients' access to the relevant procedural information and therefore enhance informed decision-making.In this paper, we first outline a hypothetical example of delegation of consent to LLMs prior to surgery. We then discuss existing clinical guidelines for consent delegation and some of the ways in which current practice may fail to meet the ethical purposes of informed consent. We outline and discuss the ethical implications of delegating consent to LLMs in medicine concluding that at least in certain clinical situations, the benefits of LLMs potentially far outweigh those of current practices.

Indexed as

Artificial IntelligenceInformed ConsentCommunicationHumansEthics- MedicalInformation TechnologyInformed Consent

Identifiers

PMID37898550
PMCPMC10850653
OpenAlexW4388007286

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.