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Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare

Adriane Chapman Orcid Logo, Chloe L Harrison Orcid Logo, Caroline Jones Orcid Logo, James Thornton Orcid Logo, Rose Worley, Jeremy C. Wyatt Orcid Logo

Companion Proceedings of the ACM on Web Conference 2024

Swansea University Authors: Caroline Jones Orcid Logo, Rose Worley

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DOI (Published version): 10.1145/3589335.3651455

Abstract

As AI systems are built and deployed to support mental health services, it is imperative to fully understand the stakeholder acceptability of such systems so that these concerns can be taken into account in system design. As such, we undertook a consultation with staff (therapists) and service-users...

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Published in: Companion Proceedings of the ACM on Web Conference 2024
ISBN: 979-8-4007-0172-6 979-8-4007-0172-6
Published: New York, NY, USA ACM 2024
URI: https://cronfa.swan.ac.uk/Record/cronfa65841
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first_indexed 2024-04-09T10:03:42Z
last_indexed 2024-04-09T10:03:42Z
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spelling v2 65841 2024-03-14 Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare 8201817d55a832f7c23f406402904a2b 0000-0001-7632-9468 Caroline Jones Caroline Jones true false fac9768e1addd9d6b13e5dcb896a4458 Rose Worley Rose Worley true false 2024-03-14 HRCL As AI systems are built and deployed to support mental health services, it is imperative to fully understand the stakeholder acceptability of such systems so that these concerns can be taken into account in system design. As such, we undertook a consultation with staff (therapists) and service-users at Adferiad Recovery (a large mental health charity). The aim was to capture insights about their understanding of trust, and different trust factors for AI in mental health care. Surveys, interviews and focus groups were conducted with service users and therapists. Key takeaways for computer scientists and the developers of AI systems are presented. Conference Paper/Proceeding/Abstract Companion Proceedings of the ACM on Web Conference 2024 ACM New York, NY, USA 979-8-4007-0172-6 979-8-4007-0172-6 AI, Mental Health, Accessibility, Equity 13 5 2024 2024-05-13 10.1145/3589335.3651455 COLLEGE NANME Hillary Rodham Clinton Law School COLLEGE CODE HRCL Swansea University Not Required British Academy and Leverhulme Trust, NIHR Southampton Biomedical Research Centre (SG2122\210037) 2024-06-06T16:35:34.8337802 2024-03-14T14:42:06.9017044 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Adriane Chapman 0000-0002-3814-2587 1 Chloe L Harrison 0000-0003-0134-633x 2 Caroline Jones 0000-0001-7632-9468 3 James Thornton 0000-0001-7847-5696 4 Rose Worley 5 Jeremy C. Wyatt 0000-0001-7008-1473 6
title Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare
spellingShingle Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare
Caroline Jones
Rose Worley
title_short Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare
title_full Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare
title_fullStr Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare
title_full_unstemmed Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare
title_sort Sociotechnical Considerations for Accessibility and Equity in AI for Healthcare
author_id_str_mv 8201817d55a832f7c23f406402904a2b
fac9768e1addd9d6b13e5dcb896a4458
author_id_fullname_str_mv 8201817d55a832f7c23f406402904a2b_***_Caroline Jones
fac9768e1addd9d6b13e5dcb896a4458_***_Rose Worley
author Caroline Jones
Rose Worley
author2 Adriane Chapman
Chloe L Harrison
Caroline Jones
James Thornton
Rose Worley
Jeremy C. Wyatt
format Conference Paper/Proceeding/Abstract
container_title Companion Proceedings of the ACM on Web Conference 2024
publishDate 2024
institution Swansea University
isbn 979-8-4007-0172-6
979-8-4007-0172-6
doi_str_mv 10.1145/3589335.3651455
publisher ACM
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
document_store_str 0
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description As AI systems are built and deployed to support mental health services, it is imperative to fully understand the stakeholder acceptability of such systems so that these concerns can be taken into account in system design. As such, we undertook a consultation with staff (therapists) and service-users at Adferiad Recovery (a large mental health charity). The aim was to capture insights about their understanding of trust, and different trust factors for AI in mental health care. Surveys, interviews and focus groups were conducted with service users and therapists. Key takeaways for computer scientists and the developers of AI systems are presented.
published_date 2024-05-13T16:35:34Z
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score 11.012678

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