2021
DOI: 10.1177/20539517211065248
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Co-design and ethical artificial intelligence for health: An agenda for critical research and practice

Abstract: Applications of artificial intelligence/machine learning (AI/ML) in health care are dynamic and rapidly growing. One strategy for anticipating and addressing ethical challenges related to AI/ML for health care is patient and public involvement in the design of those technologies – often referred to as ‘co-design’. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, AI/ML introduces challenges to co-design that are often underappreci… Show more

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Cited by 32 publications
(10 citation statements)
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“…While they have taken shape in very different ways, participatory practices are sustained by the understanding that people directly or indirectly affected by emerging technologies (as consumers, patients, or citizens), should have a say on the development, use, or oversight of said technologies ( Hagendijk and Irwin, 2006 ; Felt and Fochler, 2008 ; Gottweis et al, 2008 ; Doubleday and Wynne, 2011 ; Braun and Könninger, 2018 ). In the case of AI, public participation is also referred to as “co-creation” or “co-design ( Donia and Shaw, 2021 ). Involving the public in the development and oversight of AI-based systems is expected to render the latter socially robust and acceptable.…”
Section: Resultsmentioning
confidence: 99%
“…While they have taken shape in very different ways, participatory practices are sustained by the understanding that people directly or indirectly affected by emerging technologies (as consumers, patients, or citizens), should have a say on the development, use, or oversight of said technologies ( Hagendijk and Irwin, 2006 ; Felt and Fochler, 2008 ; Gottweis et al, 2008 ; Doubleday and Wynne, 2011 ; Braun and Könninger, 2018 ). In the case of AI, public participation is also referred to as “co-creation” or “co-design ( Donia and Shaw, 2021 ). Involving the public in the development and oversight of AI-based systems is expected to render the latter socially robust and acceptable.…”
Section: Resultsmentioning
confidence: 99%
“…Although several articles have highlighted how AI might help address health care shortages in LMICs, a recurrent problem noted in the literature is the lack of consideration for the infrastructure and human resources necessary to implement these AI technologies. To support the use of digital technologies, and specifically AI, LMICs require both health care providers trained to use specific technologies and sufficient technological infrastructure, including buildings where the hardware can be housed and cables to carry digital signals leading to widespread and stable internet access; in other words, the performance of AI algorithms is intertwined with sociotechnical factors [ 156 , 157 ]. Although HICs may have existing technological infrastructure to implement AI technologies more readily, LMICs often lack such infrastructure [ 158 ].…”
Section: Resultsmentioning
confidence: 99%
“…A central tension of this this recent wave of "participatory" is whether these mechanisms should merely serve to aid in the refinement of relevant machine learning sytem or rather emphasize lived experience as a critical form of knowledge and employ experiential learning as a force for community empowerment and advance algorithmic equity [33,49] or ensure wider humanitarian or societal benefits [11,14]. The heavy influence of industry stakeholders calling for greater participation without resolving these tensions has led to concerns of 'participationwashing' and calls for a greater need to focus on broader social structures and uneven power asymmetries [17,80], as well as the limits of participation in specific applications, such as healthcare [27].…”
Section: The Emergence Of Participatory Aimentioning
confidence: 99%
“…A growing body of work has shown the different roles and formats that participation can take in the development of AI, including: new approaches to technical development in NLP in healthcare [27,68], in the development of alternative design toolkits and processes [49,61], and methods that range from structured interviews to citizens juries [6]. In these cases, participation is meant to move beyond individual opinion to center the values of inclusion, plurality, collective safety, and ownership, subsequently shifting the relationship from one of designer-and-user to one of co-designers and co-creators.…”
Section: Introductionmentioning
confidence: 99%