Abstract
BackgroundMachine‐learning algorithms and big data analytics, popularly known as ‘artificial intelligence’ (AI), are being developed and taken up globally. Patient and public involvement (PPI) in the transition to AI‐assisted health care is essential for design justice based on diverse patient needs.ObjectiveTo inform the future development of PPI in AI‐assisted health care by exploring public engagement in the conceptualization, design, development, testing, implementation, use and evaluation of AI technologies for mental health.MethodsSystematic scoping review drawing on design justice principles, and (i) structured searches of Web of Science (all databases) and Ovid (MEDLINE, PsycINFO, Global Health and Embase); (ii) handsearching (reference and citation tracking); (iii) grey literature; and (iv) inductive thematic analysis, tested at a workshop with health researchers.ResultsThe review identified 144 articles that met inclusion criteria. Three main themes reflect the challenges and opportunities associated with PPI in AI‐assisted mental health care: (a) applications of AI technologies in mental health care; (b) ethics of public engagement in AI‐assisted care; and (c) public engagement in the planning, development, implementation, evaluation and diffusion of AI technologies.ConclusionThe new data‐rich health landscape creates multiple ethical issues and opportunities for the development of PPI in relation to AI technologies. Further research is needed to understand effective modes of public engagement in the context of AI technologies, to examine pressing ethical and safety issues and to develop new methods of PPI at every stage, from concept design to the final review of technology in practice. Principles of design justice can guide this agenda.
Highlights
Machine-learning algorithms and big data analytics will revolutionize contemporary health care
Despite the advantages of efficiency of scale and depth of computational power,3-5 concerns have been expressed by scientists, practitioners and broader publics about the systematic datafication of people's lives and their lived experiences of health and illness.6-10 It is unclear whether artificial intelligence’ (AI)-assisted health care always leads to better patient outcomes, whether it empowers and enables patients/service users, carers and their families, and whether patients or the public have a meaningful say over AI-assisted processes of care or design of such systems.11-13
This paper explores the issues from the perspective of ensuring that patient and public involvement is not overlooked in imaging and transitioning to AI-assisted health care
Summary
Machine-learning algorithms and big data analytics will revolutionize contemporary health care. Patient and public involvement (PPI) has become a principle for health-care providers and a field of practice and research. Patient and public involvement (PPI) in the transition to AI-assisted health care is essential for design justice based on diverse patient needs. Objective: To inform the future development of PPI in AI-assisted health care by exploring public engagement in the conceptualization, design, development, testing, implementation, use and evaluation of AI technologies for mental health. Further research is needed to understand effective modes of public engagement in the context of AI technologies, to examine pressing ethical and safety issues and to develop new methods of PPI at every stage, from concept design to the final review of technology in practice.
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