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.

Dementia affects 55 million people worldwide. With no accessible treatment, we need to identify ways to reduce people's risks of dementia and improve their experiences of living with dementia. People within our network will include individuals living with dementia, carers and family members, researchers, and people working for charities, health and social care services and industries. We have called this network "Sustainable Prevention, Innovation and INvolvement NETwork (SPIINNET)". We will aim to reduce risks and encourage early support in dementia, through innovative research and collaboration. We will deliver a programme of activities that will use and make connections between the experience, knowledge and resources of people across the network. These activities will include workshops where people can meet to design research projects together, training events, funding innovative ideas, meetings to raise awareness about dementia and prevention, and annual conferences to share our learning. We will work with early-stage researchers and community members, particularly engaging people and communities from diverse communities. We will bring together existing research evidence including "Big Data" resources for prevention of dementia, to be accessible for many different groups of people and to inform the network's activities. Our network model and focus will address the following objectives: Involve diverse communities, with different lived experiences, researchers and service providers. Understand how different experiences and cultures may affect people's actions to prevent dementia. Exchange knowledge between different groups of people to share understanding of dementia, prevention, resources, priorities and concerns. Innovate new ways of strengthening society, services and communities to reduce the risk of dementia within populations, and inspire individuals and families to engage in positive actions for change. Implement and widely evaluate innovations, especially for often-under reached groups, such as minority ethnic groups or people with disabilities. Sustain innovations by connecting resources, skills and learning through the network's activities. We will strive to reduce research waste, and to make our network sustainable beyond the first four years of funding. The above list represents four workstreams and each workstream will have a lead. We will have a Network Governance team with a management group, a Steering Committee and a Group of people with Lived Experience of dementia, including carers. The Lived Experience Group will be involved in decision-making and will help ensure that people who live with dementia are equally involved across the network. The network will hold a Flexible Fund of money where Network partners can apply for money to develop new research projects. The workshops, training events, meetings and annual conferences will be places for people to exchange knowledge, develop ideas together, to then also apply for funding to develop their ideas further. This application has been co-written by a group who are passionate about reducing the risk of dementia through innovative, creative, and collaborative research practices. We welcome the opportunity to create transformative change through the network described in this application.