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Beyond ideals: why the (medical) AI industry needs to motivate behavioural change in line with fairness and transparency values, and how it can do it
AI & Society, Volume: 39, Pages: 2183 - 2199
Swansea University Author: Alice Liefgreen
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DOI (Published version): 10.1007/s00146-023-01684-3
Abstract
Artificial intelligence (AI) is increasingly relied upon by clinicians for making diagnostic and treatment decisions, playing an important role in imaging, diagnosis, risk analysis, lifestyle monitoring, and health information management. While research has identified biases in healthcare AI systems...
| Published in: | AI & Society |
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| ISSN: | 0951-5666 1435-5655 |
| Published: |
Springer Nature
2024
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa63376 |
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| Abstract: |
Artificial intelligence (AI) is increasingly relied upon by clinicians for making diagnostic and treatment decisions, playing an important role in imaging, diagnosis, risk analysis, lifestyle monitoring, and health information management. While research has identified biases in healthcare AI systems and proposed technical solutions to address these, we argue that effective solutions require human engagement. Furthermore, there is a lack of research on how to motivate the adoption of these solutions and promote investment in designing AI systems that align with values such as transparency and fairness from the outset. Drawing on insights from psychological theories, we assert the need to understand the values that underlie decisions made by individuals involved in creating and deploying AI systems. We describe how this understanding can be leveraged to increase engagement with de-biasing and fairness-enhancing practices within the AI healthcare industry, ultimately leading to sustained behavioral change via autonomy-supportive communication strategies rooted in motivational and social psychology theories. In developing these pathways to engagement, we consider the norms and needs that govern the AI healthcare domain, and we evaluate incentives for maintaining the status quo against economic, legal, and social incentives for behavior change in line with transparency and fairness values. |
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| Keywords: |
Artificial intelligence, Healthcare, Medicine, Fairness, Bias, Motivation, Behaviour change |
| College: |
Faculty of Humanities and Social Sciences |
| Funders: |
Wellcome Trust ( 223765/Z/21/Z), Alfred P. Sloan Foundation (G-2021-16779), Department of Health and Social Care, British Academy ( PF2\180114), Luminate Group, Miami Foundation |
| Start Page: |
2183 |
| End Page: |
2199 |