Ensuring the benefits of AI in healthcare for all: Designing a Sustainable Platform for Public and Professional Stakeholder Engagement

日本和英国都在大力投资于国家项目，以加快医疗保健服务中人工智能的实施(1，2，3)。这项技术的明显好处包括通过使用软件和算法来识别人类观察不到的过于微妙的模式，并使用这些模式产生准确的洞察力并为更好的决策提供信息，从而提高效率和降低成本(4，5)。虽然人工智能在医疗保健中的使用有望带来变革，但其使用大型个人信息数据集在没有直接人类输入的情况下近似得出结论的能力，引发了对责任、透明度和问责制以及公众接受度的一些担忧(6，7)。人工智能在临床环境中的使用挑战了医疗保健提供的基础原则：患者对由专业行为准则管理的系统的信任；医疗保健的首要关切是保障福祉的信念，以及随后演变的法律和监管安全网(8)。专家报告指出了围绕人工智能使用的若干问题，例如：与获取临床数据有关的隐私问题；它可能如何影响人们了解如何做出有关决定的合法权利；以及由于数据库和算法隐含的偏见而可能对弱势群体造成的歧视(8，9)。在英国，人们已经表达了担忧，即人工智能公司访问公开生成的数据是否会侵蚀公众对国家医疗服务体系(NHS)的信任，潜在地危及对人工智能的广泛采用，并破坏医疗实践的基本原则(1)。出于这些原因，一些报告建议，患者和更广泛的公众将受到这些技术的最大影响，他们是人工智能未来发展的核心，并参与医疗保健软件的设计、实施和治理，作为共同设计过程的一部分(8)，将提高成功率并加强以患者为中心的护理。到目前为止，很少有研究关注公众对人工智能实施的担忧，或者不仅与患者接触，而且与医疗保健专业人员和更广泛的公众接触的最佳战略。需要的是一个接触平台，以支持与广泛的利益攸关方进行持续对话，因此人工智能的实施符合不断变化的公众关切，并造福于人类。这项研究将设在英国和日本率先使用人工智能系统的研究型医院，使我们能够确定持续对话和参与的有效模式，为未来在医疗保健中使用人工智能提供政策建议。我们将共同设计一个创新的研究计划，以征求包括患者和公众在内的利益相关者的意见：1)人工智能在治疗、诊断决策和精确医学中的当前和预期使用；2)利益相关者认为将影响医疗保健中人工智能采用和实施的问题；3)他们希望看到的参与机制、保障和监管控制的类型；以及4)如何开发一个参与平台，以解决信任、责任、问责和透明度问题，并影响规范实践。这将为两国提供洞察力，导致更好的持续公共对话，并为全球政策制定提供信息。

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.