Building Trustworthy AI: The Role of Patient and Public Involvement in Healthcare AI Development

AI is helping researchers make great strides in healthcare. However, there is a trust deficit in AI when applied to critical areas like healthcare. Hence communicating the beneficial medical applications of AI and engaging the public with healthcare AI research is critical. One way to achieve this is by getting the community involved in co-designing better AI systems in healthcare projects. We argue that AI algorithms for healthcare should be co-designed with patients and healthcare workers, so that they are useful and trustworthy. We suggest a roadmap for this collaborative approach in AI model building. This will involve actively including patients with lived experience of a disease, as well as creating a research advisory group to walk patients through the process of AI model building. We suggest formulating and scoping a problem, and then generating a hypothesis that patients and scientists agree on. The road to building trustworthy AI systems may become easier if all stakeholders are involved in co-creating AI models.

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Publication Details

Journal
Proceedings of the AAAI Symposium Series
Published
2024-11-08
DOI
https://doi.org/10.1609/aaaiss.v4i1.31811
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.12
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article

Building Trustworthy AI: The Role of Patient and Public Involvement in Healthcare AI Development

Soumya Banerjee
1 citations
Proceedings of the AAAI Symposium Series
Artificial Intelligence in Healthcare and Education
0.12
article

Building Trustworthy AI: The Role of Patient and Public Involvement in Healthcare AI Development

Soumya Banerjee
article en
1 citations

Abstract

AI is helping researchers make great strides in healthcare. However, there is a trust deficit in AI when applied to critical areas like healthcare. Hence communicating the beneficial medical applications of AI and engaging the public with healthcare AI research is critical. One way to achieve this is by getting the community involved in co-designing better AI systems in healthcare projects. We argue that AI algorithms for healthcare should be co-designed with patients and healthcare workers, so that they are useful and trustworthy. We suggest a roadmap for this collaborative approach in AI model building. This will involve actively including patients with lived experience of a disease, as well as creating a research advisory group to walk patients through the process of AI model building. We suggest formulating and scoping a problem, and then generating a hypothesis that patients and scientists agree on. The road to building trustworthy AI systems may become easier if all stakeholders are involved in co-creating AI models.

Proceedings of the AAAI Symposium SeriesVol. 4(1)
University of Cambridge (GB)
Partnerships for the goals
Openalex Percentile: Top 47%
Artificial Intelligence in Healthcare and Education
0.12
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