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.

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.

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.

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.

This Centre for Doctoral training in Industrially Focused Mathematical Modelling will train the next generation of applied mathematicians to fill critical roles in industry and academia. Complex industrial problems can often be addressed, understood, and mitigated by applying modern quantitative methods. To effectively and efficiently apply these techniques requires talented mathematicians with well-practised problem-solving skills. They need to have a very strong grasp of the mathematical approaches that might need to be brought to bear, have a breadth of understanding of how to convert complex practical problems into relevant abstract mathematical forms, have knowledge and skills to solve the resulting mathematical problems efficiently and accurately, and have a wide experience of how to communicate and interact in a multidisciplinary environment. This CDT has been designed by academics in close collaboration with industrialists from many different sectors. Our 35 current CDT industrial partners cover the sectors of: consumer products (Sharp), defence (Selex, Thales), communications (BT, Vodafone), energy (Amec, BP, Camlin, Culham, DuPont, GE Energy, Infineum, Schlumberger x2, VerdErg), filtration (Pall Corp), finance (HSBC, Lloyds TSB), food and beverage (Nestle, Mondelez), healthcare (e-therapeutics, Lein Applied Diagnostics, Oxford Instruments, Siemens, Solitonik), manufacturing (Elkem, Saint Gobain), retail (dunnhumby), and software (Amazon, cd-adapco, IBM, NAG, NVIDIA), along with two consultancy companies (PA Consulting, Tessella) and we are in active discussion with other companies to grow our partner base. Our partners have five key roles: (i) they help guide and steer the centre by participating in an Industrial Engagement Committee, (ii) they deliver a substantial elements of the training and provide a broad exposure for the cohorts, (iii) they provide current challenges for our students to tackle for their doctoral research, iv) they give a very wide experience and perspective of possible applications and sectors thereby making the students highly flexible and extremely attractive to employers, and v) they provide significant funding for the CDT activities. Each cohort will learn how to apply appropriate mathematical techniques to a wide range of industrial problems in a highly interactive environment. In year one, the students will be trained in mathematical skills spanning continuum and discrete modelling, and scientific computing, closely integrated with practical applications and problem solving. The experience of addressing industrial problems and understanding their context will be further enhanced by periods where our partners will deliver a broad range of relevant material. Students will undertake two industrially focused mini-projects, one from an academic perspective and the other immersed in a partner organisation. Each student will then embark on their doctoral research project which will allow them to hone their skills and techniques while tackling a practical industrial challenge. The resulting doctoral students will be highly sought after; by industry for their flexible and quantitative abilities that will help them gain a competitive edge, and by universities to allow cutting-edge mathematical research to be motivated by practical problems and be readily exploitable.