AI technologies have the potential to unlock significant growth for the UK financial services sector through novel personalised products and services, improved cost-efficiency, increased consumer confidence, and more effective management of financial, systemic, and security risks. However, there are currently significant barriers to adoption of these technologies, which stem from a capability deficit in translating high-level principles (of which there is an abundance) concerning trustworthy design, development and deployment of AI technologies ("trustworthy AI"), including safety, fairness, privacy-awareness, security, transparency, accountability, robustness and resilience, to concrete engineering, governance, and commercial practice. In developing an actionable framework for trustworthy AI, the major research challenge that needs to be overcome lies in resolving the tensions and tradeoffs which inevitably arise between all these aspects when considering specific application settings.For example, reducing systemic risk may require data sharing that creates security risks; testing algorithms for fairness may require gathering more sensitive personal data; increasing the accuracy of predictive models may pose threats to fair treatment of customers; improved transparency may open systems up to being "gamed" by adversarial actors, creating vulnerabilities to system-wide risks. This comes with a business challenge to match. Financial service providers that are adopting AI approaches will experience a profound transformation in key areas of business as customer engagement, risk, decisioning, compliance and other functions transition to largely data-driven and algorithmically mediated processes that involve less and less human oversight. Yet, adapting current innovation, governance, partnership and stakeholder relation management practice in response to these changes can only be successfully achieved once assurances can be confidently given regarding the trustworthiness of target AI applications. Our research hypothesis is based on recognising the close interplay between these research and business challenges: Notions of trustworthiness in AI can only be operationalised sufficiently to provide necessary assurances in a concrete business setting that generates specific requirements to drive fundamental research into practical solutions, with solutions which balance all of these potentially conflicting requirements simultaneously. Recognising the importance of close industry-academia collaboration to enable responsible innovation in this area, the partnership will embark on a systematic programme of industrially-driven interdisciplinary research, building on the strength of the existing Turing-HSBC partnership. It will achieve a step change in terms of the ability of financial service providers to enable trustworthy data-driven decision making while enhancing their resilience, accountability and operational robustness using AI by improving our understanding of sequential data-driven decision making, privacy- and security- enhancing technologies, methods to balance ethical, commercial, and regulatory requirements, the connection between micro- and macro-level risk, validation and certification methods for AI models, and synthetic data generation. To help drive innovation across the industry in a safe way which will help establish the appropriate regulatory and governance framework, and a common "sandbox" environment to enable experimentation with emerging solutions and to test their viability in a real-world business context. This will also provide the cornerstone for impact anticipation and continual stakeholder engagement in the spirit of responsible research and innovation.

Overview: We propose a Centre for Doctoral Training in Data Science. Data science is an emerging discipline that combines machine learning, databases, and other research areas in order to generate new knowledge from complex data. Interest in data science is exploding in industry and the public sector, both in the UK and internationally. Students from the Centre will be well prepared to work on tough problems involving large-scale unstructured and semistructured data, which are increasingly arising across a wide variety of application areas. Skills need: There is a significant industrial need for students who are well trained in data science. Skilled data scientists are in high demand. A report by McKinsey Global Institute cites a shortage of up to 190,000 qualified data scientists in the US; the situation in the UK is likely to be similar. A 2012 report in the Harvard Business Review concludes: "Indeed the shortage of data scientists is becoming a serious constraint in some sectors." A report on the Nature web site cited an astonishing 15,000% increase in job postings for data scientists in a single year, from 2011 to 2012. Many of our industrial partners (see letters of support) have expressed a pressing need to hire in data science. Training approach: We will train students using a rigorous and innovative four-year programme that is designed not only to train students in performing cutting-edge research but also to foster interdisciplinary interactions between students and to build students' practical expertise by interacting with a wide consortium of partners. The first year of the programme combines taught coursework and a sequence of small research projects. Taught coursework will include courses in machine learning, databases, and other research areas. Years 2-4 of the programme will consist primarily of an intensive PhD-level research project. The programme will provide students with breadth throughout the interdisciplinary scope of data science, depth in a specialist area, training in leadership and communication skills, and appreciation for practical issues in applied data science. All students will receive individual supervision from at least two members of Centre staff. The training programme will be especially characterized by opportunities for combining theory and practice, and for student-led and peer-to-peer learning.

This Fellowship is about re-orientating interactive AI systems, away from systems that might lead to people feeling powerless, redundant and undervalued, turning towards approaches that let people experience joy, creativity, connection and agency as they use AI innovations to amplify their innate abilities, qualities and values. Many everyday people worry about the impact of artificial intelligence on their lives and livelihoods. In the most recent Stanford AI-100 report (September 2021), for example, while the fear of robots taking people's jobs has reduced, there is a strong concern that such systems will erode democracy and values through deep fakes, manipulated social media feeds and the like. The report points to Grand Challenges for AI that involve systems outpacing or outsmarting humans. Even as I write this summary (late Jan 2023), there is a frenzy of excitement over Open AI's ChatGPT, a system that can turn a simple written request (e.g. "Write me a compelling EPSRC summary") into, at least at the surface level, a seductively articulate response (N.B., this summary is definitely written by me). Further, I am writing this while in South Africa where I have engaged with community members in Langa, a township on the outskirts of Cape Town, South Africa, as part of the preparation for the Fellowship. These people spoke of the starkly real problems (from violent crime to very high unemployment). With so many underserved and unheard voices, globally and indeed in the UK, there is a timely and urgent need to think about how to radically enable these "natural intelligences" rather than to replace them with artificial ones. In this Fellowship, then, we will work intensively with people who are not usually involved in AI discovery and innovation - people with lower socio-economic opportunities in the UK and those in Global South communities such as the informal settlements in India, Kenya, Brazil and South Africa. Their lived-experiences will be brought into the design and development process, a process further richly enhanced through the involvement of a diverse set of technology, service provision and creative partners. In doing so, we aim to discover novel ways for people - everywhere, whatever their contexts and opportunities - to engage with AI systems. We call this new trajectory for AI research, EVE - everyone virtuoso everyday - to succinctly summarise the drive of the work. That is, we are interested in defining and evaluating a class of AI technology that enable expressive, individual and masterful interactions, like a virtuoso musician who channels all of their being - physical, mental, emotional and even spiritual - through their instrument to help themselves and others make sense of the world. However, our work is not about turning everyone into an AI-fuelled artist, dancer or musician. Quite the contrary, we look to providing tools that can be deployed in the mundanity of their daily lives. As a Fellowship, the vision and agenda is broad and open to continuous shaping with communities, academics and wider societal stakeholders as the work proceeds over three cycles, each 20 months long, as ideas move from seeds of possibility, growing and being refined into working embodiments, enabling us to evaluate them, integrating them into toolkits for wide impact in academic and practice worlds.

Technological advances have done, and will do, much to improve cybersecurity. But, a technological approach is only part of the solution - achieving digital security is inherently a socio-technical endeavour. By combining world-leading research with challenge fellows from across the social sciences, expert working groups, innovative approaches to networking and agile, industry-facing commissioning, the DiScriBe Hub+ will not only address the challenges faced by the ISCF Digital Security by Design (DSbD) initiative, but will fundamentally reshape the ways in which social sciences and STEM disciplines work together to address the challenges of digital security by design in the 21st Century. The core missions of the DiScriBe Hub+ are to provide interdisciplinary leadership to realise digital security by design by connecting social science to a hardware layer that rarely receives support or engagement from social science. This social science input will help to unleash the transformational potential that the hardware innovations within Digital Security by Design makes possible. The Hub+ has five main ways of doing this: 1) Running a series of deep engagements with DSbD stakeholders using techniques from the arts and humanities in order to elicit a shared view of 'Digital Security by Design Futures' 2) Conducting an innovative programme of interdisciplinary research to improve our understanding of the barriers and incentives around adoption of new secure architectures, business readiness levels and adoption, regulatory opportunities and challenges, and ways these are experienced and understood across diverse sectors; 3) Commissioning a range of agile, responsive, industry-facing projects and 'connecting capabilities' grants to address specific DSbD challenges; 4) Establishing a network of 'challenge fellows' tasked with synthesising research outcomes (core and commissioned), connecting insights to the wider Digital Security by Design initiative, and ensuring impact, alongside expert working groups comprising industry and researchers to tackle specific problems in a sharp, focussed way; and, 5) Building a community of social scientists, hardware engineers, software developers, industry and policy makers who are deeply engaged in applying a socio-technical lens to digital security by design. DiScriBe is unique in its focus on the benefits of connecting security architecture innovation with leading social science - and will provide a step change in how cybersecurity is treated as an inter-disciplinary, social as well as technical, problem. Many of the lessons on cross disciplinary working will be tested and embedded through close working with the Bristol Digital Futures Institute - a £70m investment in how our ways of working will need to change in the digital future. We have expert challenge fellows who are leading social scientists applying their work to cybersecurity for the first time. These fellows will also lead working groups on specific topics connecting industry, policy and academia, which in turn will lead to a range of open calls for commissioned industry-facing research. This research will be both theoretically rigorous within social science, while also remaining responsive and agile enough to meet the needs of the wider DSbD programme. As a consequence, a major outcome of DiScriBE will not only be a vibrant, new community, but novel insights that can be applied to the development and implementation of new security-related developments.

We are in a biodiversity crisis. A million species of plants and animals are threatened with global extinction, and wildlife populations across much of the planet have been dramatically reduced, perhaps by as much as a half in recent decades. This is of profound concern because biodiversity underpins human existence. Biodiversity provides the foundation of our economies, livelihoods, food security, health and quality of life. Increasing numbers of people, organisations and governments recognise the need to reverse the perilous state of our ecological inheritance. However, while there is unprecedented willingness to act, what we do not know is what will work most effectively to renew biodiversity and ensure continued delivery of its benefits. The Renewing biodiversity through a people-in-nature approach (RENEW) programme will develop solutions to the renewal of biodiversity. We will work, with a sense of urgency, to reshape understanding and action on biodiversity renewal across scales, creating knowledge at the cutting edge of global debates and policy development, and influencing national institutions, communities and individuals. We know that understanding of, and action on, renewal must take a step change and we will focus on the agency of people in nature, both as part of the problem and as the solution. We focus on a set of challenges: how popular support for biodiversity renewal can be harnessed; how populations that are disengaged, disadvantaged, or disconnected from nature can benefit from inclusion in solutions development; how renewal activities can be designed and delivered by diverse sets of land-managers and interest groups; and how biodiversity renewal can most effectively be embedded in finance and business activities (as has occurred with carbon accounting and climate change). This sits alongside the scientific and technical development necessary to underpin solutions options. Biodiversity renewal is a complex and whole system problem. The solutions require the creation of a new kind of inclusive and diverse research community, one that transcends traditional boundaries between the disciplines needed to tackle the environmental crises of the Anthropocene. Solutions also need to address the inequalities and lack of diversity found in current renewal practices. RENEW has therefore prioritised partnership building, to allow us to combine research with experiment, learning, sharing, outreach and impact, across relevant organisations and wider communities. Our approach means that practical impact is guaranteed. With the National Trust as co-owners of RENEW, we will have significant reach through their membership, outreach programs and public voice. Alongside other key partners in RENEW, our links are responsible for or have influence over much of the UK landscape in which biodiversity renewal activities need to occur. We will use the many landscape-scale nature activities currently underway (or planned in the near future) to develop learning, as if they were 'real time' experiments. The UK is one of the most biodiversity depleted countries in the world. Our ways of working in RENEW, the knowledge we develop, and the solutions we propose, will be of international importance. The lessons we learn will enable future biodiversity researchers and practitioners around the world to do better science, and deliver fairer outcomes.