Title: Ensuring the benefits of AI in healthcare for all: Designing a Sustainable Platform for Public and Professional Stakeholder Engagement
Funder: Economic and Social Research Council

Abstract: The central aim of this research is to identify effective strategies to support an engagement platform for Artificial Intelligence (AI) that can sustain dialogue and engagement between a range of stakeholders including patients and the public. This will stimulate the creation of an interdisciplinary, multi-sectoral, global ecosystem to support the implementation of AI in healthcare in Japan and the UK for the benefit of society. We will carry out an innovative programme of co-designed empirical research that will provide evidence for policy-making. There are four key objectives: 1. Identify Stakeholder Concerns We will address the current lack of knowledge on the issues concerning stakeholders regarding implementation of AI in healthcare and identify preferences for safeguards and regulatory controls. Key research questions: -What are the current and anticipated uses of AI in treatment, diagnostic decision-making and precision medicine? -What are the issues that different stakeholders perceive will influence the adoption and implementation of AI? -What safeguards and controls do stakeholders think would inspire public trust? 2. Engagement Strategies We will work with stakeholders to develop engagement strategies that build a platform for sustained dialogue as AI technology evolves over time, as one element of an effective ecosystem. Key questions: -How do different stakeholders want to be engaged with, asked about or involved in AI? -What experiences have stakeholders had of engagement and involvement in emerging technologies for healthcare? -How should different stakeholders be involved in co-development of a platform? -What engagement strategies would increase transparency, accountability and inclusion, and therefore inspire trust in AI in healthcare? -What resources are required to implement sustainable engagement strategies? 3. Innovative Research Strategy Following the recommendations of expert reports for user-centricity, our patient and public involvement panel (PPIP) will help steer and co-design the research. Given the longitudinal nature of the PPIP participation throughout the project, their involvement in co-design will be prospectively evaluated to understand the successes and challenges of this approach. The evaluation will investigate: -Barriers to recruitment of a representative PPIP -How does the PPIP need to be supported in the short/ long term? -Positive outcomes of PPIP involvement in co-design -Do stakeholders value the PPIP? The evaluation will provide an example of how co-design could be used in AI policy-making in different countries as a component of an ecosystem to support the implementation of AI. A core aspect of our approach is to use Q-Methodology to investigate stakeholder agreement to evidence-based statements about issues in AI and engagement/involvement strategies for these. The Q-Method is a suitable but under utilised method in digital health research, and not yet employed in AI in healthcare research or policy. 4. Contribution to Policy This research will promote interdisciplinary collaboration between researchers in Japan and the UK, and provide the evidence to support practical implementation of engagement strategies leading to policy recommendations, at a time when there is a rapid take up of AI in healthcare. While there are similarities in healthcare provision in each country, translation of AI into practice occurs against very different socio-cultural, political, ethical and economic backdrops. By comparing the two countries, we will generate valuable insights in how to develop a platform for dialogue and engagement involving a wide-range of stakeholders to inform global policy in AI. The research questions are: - What are the routes to lobby relevant policy makers in each jurisdiction? - Which organisations are working in this area, including patient/public organisations? - What are the key policy recommendations for future stakeholder engagement?

Lay abstract: Japan and the UK are both investing heavily in national programmes to accelerate the implementation of AI in healthcare delivery (1,2,3). The perceived benefits of this technology include increased efficiacy and cutting costs by using software and algorithms to 'identify patterns too subtle to be detected by human observation, and to use those patterns to generate accurate insights and inform better decision making (4,5). While the use of AI in healthcare promises to be transformative, its ability to approximate conclusions without direct human input using large datasets of personal information, raises a number of concerns about responsibility, transparency and accountability, and public acceptance (6,7). The use of AI in clinical settings challenges the principles that underpin healthcare delivery: the patient's trust in a system governed by professional codes of conduct; the belief that the primary concern of healthcare is to safeguard well-being, and the subsequent legal and regulatory safety nets that have evolved (8). Expert reports have identified a number of issues surrounding the use of AI, such as: privacy concerns associated with access to clinical data; how it might influence people's legal right to know how decisions about them are made; and the possibility of discrimination of vulnerable populations due to database and algorithm implicit biases (8,9). In the UK, concerns have already been expressed about whether access to publicly-generated data by AI companies might erode public trust in the National Health Service (NHS), potentially jeopardising wide-spread adoption of AI and undermining the basic tenets of healthcare practice (1). For these reasons, a number of reports have recommended that patients and wider public, who will be most impacted by these technologies, are central to the future development of AI and involved in the design, implementation and governance of software for healthcare, as part of a co-design process (8), that will improve success rates and enhance patient-centred care. To date, very few studies have focused on public concerns regarding AI implementation, or the best strategies for engaging not just with patients, but healthcare professionals and wider publics. What is needed is an engagement platform to support a sustained dialogue with a broad range of stakeholders, so the implementation of AI is in accordance with changing public concerns and for the benefit of humanity. This research will be situated in research hospitals in the UK and Japan that are pioneering the use of AI systems, to allow us to identify effective models for sustained dialogue and engagement that can inform policy recommendations for future use of AI in healthcare. We will co-design an innovative programme of research to elicit the views of stakeholders, including patients and the public regarding: 1) the current and anticipated use of AI in treatment, diagnostic decision-making and precision medicine 2) the issues that stakeholders perceive will influence the adoption and implementation of AI in healthcare; 3) the types of engagement mechanisms, safeguards and regulatory controls they would like to see in place; and 4) how to develop a platform for engagement that can address issues of trust, responsibility, accountability and transparency, and influence normative practice. This will provide insights for both countries, leading to better sustained public dialogue, as well as informing global policy-making.

Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES;8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: GENERIC HEALTH RELEVANCE