CHAI - EPSRC AI Hub for Causality in Healthcare AI with Real Data

目前的AI范式充其量只能揭示模型输入和输出变量之间的相关性。这福尔斯不足以解决卫生和医疗保健挑战，在这些挑战中，了解干预措施和结果之间的因果关系是必要和可取的。此外，人工智能系统中的偏见和脆弱性也会出现，因为模型可能会从历史数据中提取不必要的虚假相关性，从而扩大现有的健康不平等。因果人工智能是解锁强大、负责任和值得信赖的人工智能的关键，也是转变早期预测、诊断和预防疾病等具有挑战性任务的关键。医疗保健人工智能与真实的数据的因果关系（CHAI）中心将汇集学术界，工业界，医疗保健和政策利益相关者，共同创建下一代世界领先的人工智能解决方案，可以预测干预措施的结果，并帮助选择个性化治疗，从而改变健康和医疗保健。CHAI Hub将开发新的方法来识别和解释复杂数据中的因果关系。该中心将由社区为社区建立，聚集来自英国各地的专家和利益相关者，以1）推动人工智能创新的界限; 2）开发尖端解决方案，推动资源受限的医疗保健系统迫切需要的效率; 3）巩固英国作为下一代人工智能超级大国的地位。异构和分布式环境（如医疗保健）中的数据复杂性加剧了偏见和脆弱性的风险，并带来了必须解决的额外挑战。现代临床研究需要混合结构化和非结构化数据源（例如患者健康记录和医学成像检查），当前AI无法有效集成这些数据源。必须解决当前人工智能技术中的这些差距，以便开发有助于更好地了解疾病机制、预测结果和估计治疗效果的算法。如果我们想确保在个性化决策中安全和负责任地使用AI，这一点很重要。因果AI有潜力从观察数据中挖掘新的见解，正式确定治疗效果，评估结果可能性，并估计“假设”情景。阐明因果原则对于实现国家人工智能战略至关重要，以确保人工智能在技术和临床上是安全的，透明的，公平的和可解释的。CHAI Hub将由人工智能，医疗保健和数据科学领域的强大企业组成的创始财团组成，遍布英国，采用中心辐射模型，具有地理覆盖范围和多样性。该中心将设在爱丁堡的贝叶斯中心（利用世界一流的人工智能专业知识，健康应用中的数据驱动创新，强大的健康数据生态系统，创业精神和翻译）。区域辐条将在曼彻斯特（通过数据科学与人工智能研究所和Pankhurst研究所提供人工智能方法和翻译方面的专业知识），伦敦（托管在KCL，也代表UCL和帝国理工学院，利用伦敦快速发展的人工智能生态系统）和埃克塞特（利用因果推理哲学和人工智能伦理学方面的优势）。该中心将为因果人工智能开发一个全英国多学科网络。通过与行业、政策制定者和其他利益相关者的广泛合作，我们将扩大该中心，在最需要的地方提供下一代因果人工智能。我们将共同努力，共同创造，超越共同构思和共同设计，共同实施，并在适当时共同评估，以确保适合目的的解决方案我们的计划将是灵活的，将嵌入值得信赖的，负责任的创新和环境可持续性考虑因素，将确保平等，多样性和包容性原则反映在所有活动中，并将确保通过CHAI产生的知识将在最初的60个月后继续对现实世界产生影响。

The current AI paradigm at best reveals correlations between model input and output variables. This falls short of addressing health and healthcare challenges where knowing the causal relationship between interventions and outcomes is necessary and desirable. In addition, biases and vulnerability in AI systems arise, as models may pick up unwanted, spurious correlations from historic data, resulting in the widening of already existing health inequalities. Causal AI is the key to unlock robust, responsible and trustworthy AI and transform challenging tasks such as early prediction, diagnosis and prevention of disease. The Causality in Healthcare AI with Real Data (CHAI) Hub will bring together academia, industry, healthcare, and policy stakeholders to co-create the next-generation of world-leading artificial intelligence solutions that can predict outcomes of interventions and help choose personalised treatments, thus transforming health and healthcare. The CHAI Hub will develop novel methods to identify and account for causal relationships in complex data. The Hub will be built by the community for the community, amassing experts and stakeholders from across the UK to 1) push the boundaries of AI innovation; 2) develop cutting-edge solutions that drive desperately needed efficiency in resource-constrained healthcare systems; and 3) cement the UK's standing as a next-gen AI superpower. The data complexity in heterogeneous and distributed environments such as healthcare exacerbates the risks of bias and vulnerability and introduces additional challenges that must be addressed. Modern clinical investigations need to mix structured and unstructured data sources (e.g. patient health records, and medical imaging exams) which current AI cannot integrate effectively. These gaps in current AI technology must be addressed in order to develop algorithms that can help to better understand disease mechanisms, predict outcomes and estimate the effects of treatments. This is important if we want to ensure the safe and responsible use of AI in personalised decision making.Causal AI has the potential to unearth novel insights from observational data, formalise treatment effects, assess outcome likelihood, and estimate 'what-if' scenarios. Incorporating causal principles is critical for delivering on the National AI Strategy to ensure that AI is technically and clinically safe, transparent, fair and explainable.The CHAI Hub will be formed by a founding consortium of powerhouses in AI, healthcare, and data science throughout the UK in a hub-spoke model with geographic reach and diversity. The hub will be based in Edinburgh's Bayes Centre (leveraging world-class expertise in AI, data-driven innovation in health applications, a robust health data ecosystem, entrepreneurship, and translation). Regional spokes will be in Manchester (expertise in both methods and translation of AI through the Institute for Data Science and AI, and Pankhurst Institute), London (hosted at KCL, representing also UCL and Imperial, leveraging London's rapidly growing AI ecosystem) and Exeter (leveraging strengths in philosophy of causal inference and ethics of AI).The hub will develop a UK-wide multidisciplinary network for causal AI. Through extended collaborations with industry, policymakers and other stakeholders, we will expand the hub to deliver next-gen causal AI where it is needed most. We will work together to co-create, moving beyond co-ideation and co-design, to co-implementation, and co-evaluation where appropriate to ensure fit-for-purpose solutions Our programme will be flexible, will embed trusted, responsible innovation and environmental sustainability considerations, will ensure that equality diversity and inclusion principles are reflected through all activities, and will ensure that knowledge generated through CHAI will continue to have real-world impact beyond the initial 60 months.