AI and Machine Learning often address challenges that are relatively monolithic in nature: determine the safest route for an autonomous car; translate a document from English to French; analyse a medical image to detect a cancer; answer questions about a difficult topic. These kinds of challenge are very important and worthwhile targets for AI research. However, an alternative set of challenges exist that are more *collective* in nature and that unfold in *real time*: - help minimise the impact of a pandemic sweeping through a population of people by informing the coordination of local and national testing, social distancing and vaccination interventions; - predict and then monitor the extent and severity of an extreme weather event using multiple real-time physical and social data streams; - anticipate and prevent a stock market crash caused by the interactions between many automated trading agents each following its own trading algorithm; - derive city-wide patterns of changing mobility from high-frequency time series data and use these patterns to drive city planning decisions that maximise liveability and sustainability in the future city; - assist populations of people with type 2 diabetes to avoid acute episodes and hospitalisation by identifying patterns in their pooled disease trajectories while preserving their privacy and anonymity. Developing AI systems for these types of problem presents unique challenges: extracting reliable and informative patterns from multiple overlapping and interacting data streams; identifying and controlling for inherent biases within the data; determining the local interventions that can allow smart agents to influence collective systems in a positive way; developing privacy preserving machine learning and advancing ethical best practices for collective AI; embedding novel machine learning and AI in portals, devices and tools that can be used transparently and successfully by different types of user. The AI for Collective Intelligence (AI4CI) Hub will address these challenges for AI in the context of critically important real world use cases (cities, pandemics, health care, environment and finance) working with key stakeholder partners from each sector. In addition to significantly advancing applied AI research for collective intelligence, the AI4CI Hub will also work to build *community* in this research area, linking together academic research groups across the UK with each other and with key industry, government and public sector organisations, and to build *capability* by developing and releasing open access training materials, tools, demonstrator systems and best practice guidance, and by supporting the career development of early and mid-career researchers both within academia and beyond. The AI for Collective Intelligence Hub will be a centre of gravity for a nation-wide research effort applying new AI to collective systems.

The ACORN network's mission is to bridge the gap that currently exists between the research in universities and the need of the financial services industry, its consumers and the regulator. ACORN wants to grow to well over 100 primary partners and 1000 associated partners, offering an inclusive, diverse and responsible research culture. Based on regional presence in Wales, Scotland, North-East England and London, it will harmonize technological know-how across regions and connect regional partners to nation-wide efforts. Real-life challenges in financial services are complex, combining responding to technology innovation with business ethics, green/environmental considerations and scarcity in the talent pipeline. This presents FS with wicked problems, which the industry cannot ignore, and which require people and researchers from across disciplines to come together. ACORN aims to address wicked problems in FS that are associated with innovation in technology, mathematics and sciences. ACORN provides a number of mechanisms to succeed in this mission. Central to ACORN's working is its 'commissioning framework', which provides the funding mechanisms for five types of collaborative projects between academia and partners. ACORN offers seed project funding, which aims to explore technological, mathematical and scientific solutions for real-life challenges in FS, prioritised through co-design sandpits. It then offers funding for larger multi-disciplinary feasibility projects, which may build on the seed projects, and expand to consider 'wicked' multi-disciplinary research problems. In parallel, ACORN offers funding for agile projects, which can be of any type, e.g., horizon scanning, population survey, a software prototype or a machine learning application. These have predetermined IP arrangements, so that they can be organised in agile manner and can start at any time for the duration of ACORN. Additionally, impact projects are offered to take any of the research projects further (e.g., to influence policy makers, or initiate commercialisation), and education/engagement projects allow to grow the FS talent pool and address the talent pipeline. To support researchers and partners in these project, ACORN establishes a number of services the community can use. The co-design service and the corporate digital responsibility service help researchers to consider these aspects in their proposals. The secure data vault, the shared code base, the experimentation sandbox and template IP arrangements are available to improve research, its impact and to lower collaboration barriers. We name the network ACORN, to signify that collaborations as majestic as an oak tree can grow from humble beginnings.

The Centre's themes align with the 'Towards A Data Driven Future' and 'Enabling Intelligence' priority areas, meeting the needs identified by UKRI to provide a highly skilled - and in demand - workforce focused on ensuring positive, human-centred benefits accrued from innovations in data driven and intelligence-based systems. The Centre has a distinct and methodologically challenging "people-first" perspective: unlike an application-orientated approach (where techniques are applied to neatly or simplistically defined problems, sometimes called "solutionism"), this lens will ensure that intense, multi-faceted and iterative explorations of the needs, capabilities and values of people, and wider societal views, challenge and disrupt computational science. In a world of big data and artificial intelligence, the precious smallness of real individuals with their values and aspirations are easily overlooked. Even though the impact of data-driven approaches and intelligence are only beginning to be felt at a human scale, there are already signs of concern over what these will mean for life, with governments and others worldwide addressing implications for education, jobs, safety and indeed even what is unique in being human. Sociologists, economists and policy makers of course have a role in ensuring positive outcomes for people and society of data-driven and intelligence systems; but, computational scientists have a pivotal duty too. Our viewpoint, then, will always see the human as a first-class citizen in the future physical-digital world, not perceiving themselves as outwitted, devalued or marginalised by the expanding capabilities of machine computation, automation and communication. Swansea and the wider region of Wales is a place and community where new understandings of data science and machine intelligence are being formed within four challenging contexts defined in the Internet Coast City Deal: Life Science and Well-being; Smart Manufacturing; Smart and Sustainable Energy; and Economic Acceleration. Studies commissioned by the City Deal and BEIS evidence the science and innovation strengths in Swansea and region in these areas and indicate how transformational investments in these areas will be for the region and the UK. Our Centre will, then, immerse cohorts in these contexts to challenge them methodologically and scientifically. The use of data-driven and intelligence systems in each of the four contexts gives rise to security, privacy and wider ethical, legal, governance and regulatory issues and our Centre also has a cross-cutting theme to train students to understand, accommodate and shape current and future developments in these regards. Cohort members will work to consider how the Centre's challenge themes direct and drive their thinking about data and intelligence, benefitting from both the multidisciplinary team that have built strong research agendas and connections with each of the contexts and the rich set of stakeholders that are our Centre has assembled. Importantly, a process of pivoting between challenge themes will be applied: insights, methods and challenges from one theme and its research projects will be tested and extended in others with the aim of enriching all. These, along with several other mechanisms (such as intra- and inter-cohort sandpits and side projects) are designed to develop a powerful bonding and shaping "cohort effect". The need for and value of our Centre is evidenced by substantial external industrial investment we have have secured: £1,750,000 of cash and £4,136,050 in-kind (total:£5,886,050). These partners and stakeholders have helped create the vision and detail of the proposal and include: Vint Cerf ("father of the internet" and Vice President of Google); NHS; Pfizer; Tata Steel; Ford; QinetiQ; McAfee; Ordnance Survey; Facebook; IBM; Microsoft; Fujitsu; Worshipful Company of IT Spiritual and Ethical Panel; and, Vicki Hanson (CEO, Association of Computing Machinery).