Moving beyond Technical Issues to Stakeholder Involvement: Key Areas for Consideration in the Development of Human-Centred and Trusted AI in Healthcare-Reference-Cited by-同舟云学术

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

Published:2024-06-21 Issue:3 Volume:16 Page:501-511
ISSN:1793-8759
Container-title:Asian Bioethics Review
language:en
Short-container-title:ABR

Author:

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

Abstract

AbstractDiscussion 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.

Funder

Japan Science and Technology Agency

Economic and Social Research Council

Japan Society for the Promotion of Science

Osaka University

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s41649-024-00300-w.pdf

Reference32 articles.

1. Adams, Scott J., Rachel Tang, and Paul Babyn. 2020. Patient perspectives and priorities regarding artificial intelligence in radiology: Opportunities for patient-centered radiology. Journal of the American College of Radiology 17 (8): 1034–1036. https://doi.org/10.1016/j.jacr.2020.01.007.

2. Ali, Omar, Wiem Abdelbaki, Anup Shrestha, Ersin Elbasi, Mohammad Abdallah Ali. Alryalat, and Yogesh K. Dwivedi. 2023. A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities. Journal of Innovation & Knowledge 8 (1): 100333. https://doi.org/10.1016/j.jik.2023.100333.

3. Andersen, Tariq Osman, Francisco Nunes, Lauren Wilcox, Enrico Coiera, and Yvonne Rogers. 2023. Introduction to the special issue on human-centred AI in healthcare: Challenges appearing in the wild. ACM Transactions on Computer-Human Interaction 30 (2): 12. https://doi.org/10.1145/3589961.

4. Banerjee, Soumya, Phil Alsop, Linda Jones, and Rudolf N. Cardinal. 2022. Patient and public involvement to build trust in artificial intelligence: A framework, tools, and case studies. Patterns 3 (6): 100506. https://doi.org/10.1016/j.patter.2022.100506.

5. Department of Health and Social Care. 2023. NHS constitution for England. https://www.gov.uk/government/publications/the-nhs-constitution-for-england/the-nhs-constitution-for-england. Accessed 8 Nov 2023.