Evidence map›Paper›PMID 39022370›Full record

ArticleAsian bioethics review2024

Moving beyond Technical Issues to Stakeholder Involvement: Key Areas for Consideration in the Development of Human-Centred and Trusted AI in Healthcare.

Jane Kaye, Nisha Shah, Atsushi Kogetsu, Sarah Coy, Amelia Katirai, Machie Kuroda, Yan Li, Kazuto Kato, Beverley Anne Yamamoto

Abstract read
In one paragraph

Article in Asian bioethics review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jane KayeCentre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK.ORCID 0000-0002-7311-4725
Nisha ShahCentre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK.ORCID 0000-0002-1872-4598
Atsushi KogetsuDepartment of Biomedical Ethics and Public Policy, Graduate School of Medicine, Osaka University, Osaka, Japan.ORCID 0000-0002-0465-8163
Sarah CoyCentre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK.ORCID 0000-0003-2548-2045
Amelia KatiraiResearch Center on Ethical, Legal, and Social Issues, Osaka University, Osaka, Japan.ORCID 0000-0002-4698-1479
Machie KurodaDepartment of Biomedical Ethics and Public Policy, Graduate School of Medicine, Osaka University, Osaka, Japan.
Yan LiCenter for Global Initiatives, Osaka University, Osaka, Japan.ORCID 0000-0003-0909-4368
Kazuto KatoDepartment of Biomedical Ethics and Public Policy, Graduate School of Medicine, Osaka University, Osaka, Japan.ORCID 0000-0001-9006-9551
Beverley Anne YamamotoGraduate School of Human Sciences, Osaka University, Osaka, Japan.ORCID 0000-0003-1791-6827

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Discussion around the increasing use of AI in healthcare tends to focus on the technical aspects of the technology rather than the socio-technical issues associated with implementation. In this paper, we argue for the development of a sustained societal dialogue between stakeholders around the use of AI in healthcare. We contend that a more human-centred approach to AI implementation in healthcare is needed which is inclusive of the views of a range of stakeholders. We identify four key areas to support stakeholder involvement that would enhance the development, implementation, and evaluation of AI in healthcare leading to greater levels of trust. These are as follows: (1) aligning AI development practices with social values, (2) appropriate and proportionate involvement of stakeholders, (3) understanding the importance of building trust in AI, (4) embedding stakeholder-driven governance to support these activities.

Indexed as

AIGovernanceHealthHuman-centredTechnologyTrusted AI

Identifiers

PMID39022370
PMCPMC11250765

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.