A participatory approach to deploy responsible artificial intelligence for diabetes prediction and prevention

Artificial intelligence (AI) technologies have the potential to improve healthcare and public health. Although there has been success in AI for research uses, little progress has been made in implementing health-related AI technologies in health systems. Responsible AI for health systems requires engagement and co-design with health system partners, policymakers, and the community. Deploying responsible AI requires engaging stakeholders, particularly those affected by the technology. This commentary presents the importance of participatory approaches for responsible AI implementation. In this commentary, we discuss the planned use of participatory approaches to responsibly deploying validated machine learning models, with a specific case example of diabetes prediction models that can address the challenge of preventing and managing diabetes in a health system.. The participatory methods engage policy-, provider-, and community-level actors to deploy and implement the AI diabetes tools, inform how AI is implemented in health settings, and overcome common deployment barriers. The future of AI in health settings rests on fine-tuning these practices to enable trust, acceptability, and oversight of these technologies to be deeply established in health systems.

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Publication Details

Journal
Digital Health
Published
2025-05-01
DOI
https://doi.org/10.1177/20552076251358541
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31

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article

A participatory approach to deploy responsible artificial intelligence for diabetes prediction and prevention

Remziye Zaim, Ijeoma Uchenna Itanyi, Kathy Kornas, Victoria Chui et al.
2 citations
Digital Health
Artificial Intelligence in Healthcare and Education
1.31
article

A participatory approach to deploy responsible artificial intelligence for diabetes prediction and prevention

Remziye Zaim, Ijeoma Uchenna Itanyi, Kathy Kornas, Victoria Chui, Laura C. Rosella, Ibukun‐Oluwa Omolade Abejirinde, Lorraine Lucille Lipscombe, James Shaw, Shion Guha, Jennifer Gibson
article en
2 citations

Abstract

Artificial intelligence (AI) technologies have the potential to improve healthcare and public health. Although there has been success in AI for research uses, little progress has been made in implementing health-related AI technologies in health systems. Responsible AI for health systems requires engagement and co-design with health system partners, policymakers, and the community. Deploying responsible AI requires engaging stakeholders, particularly those affected by the technology. This commentary presents the importance of participatory approaches for responsible AI implementation. In this commentary, we discuss the planned use of participatory approaches to responsibly deploying validated machine learning models, with a specific case example of diabetes prediction models that can address the challenge of preventing and managing diabetes in a health system.. The participatory methods engage policy-, provider-, and community-level actors to deploy and implement the AI diabetes tools, inform how AI is implemented in health settings, and overcome common deployment barriers. The future of AI in health settings rests on fine-tuning these practices to enable trust, acceptability, and oversight of these technologies to be deeply established in health systems.

Digital HealthVol. 11
University of Toronto (CA), Trillium Health Centre (CA), Women's College Hospital (CA), Public Health Ontario (CA)
Canadian Institute for Advanced Research
Partnerships for the goals
Openalex Percentile: Top 15%
Artificial Intelligence in Healthcare and Education
1.31
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