Digital technologies and services are shaping our lives. Work, education, finance, health, politics and society are all affected. They also raise concomitant and complex challenges relating to the security of and trust in systems and data. TIPS (Trust, Identity, Privacy and Security) issues thus lie at the heart of our adoption of new technologies and are critical to our economic prosperity and the well-being of our citizens. Identifying and addressing such issues requires a coherent, coordinated, multi-disciplinary approach, with strong stakeholder relationships at the centre. SPRITE+ is a vehicle for communication, engagement, and collaboration for people involved in research, practice, and policy relevant to TIPS in digital contexts. Since launching in 2019, we have established ourselves as the go-to point of contact to engage with the broadest UK network of interdisciplinary, cross-sector digital TIPS experts. The second phase of SPRITE+ ('SPRITE+2') will continue to build our membership, whilst expanding the breadth and depth of our innovation, and deepen our impact through proactive engagement. SPRITE+2 will have the following objectives: 1. Expand our TIPS community, harnessing the expertise and collaborative potential of the national and international TIPS communities 2. Identify and prioritise future TIPS research challenges 3. Explore and develop priority research areas to enhance our collective understanding of future global TIPS challenges 4. Stimulate innovative research through sandpits, industry led calls, and horizon scanning 5. Deepen engagement with TIPS research end users across sectors to accelerate knowledge Exchange 6. Understand, inform, and influence policy making and practice at regional, national and international level These will be delivered through four work packages and two cross cutting activities. All work packages will be led by the PI (Elliot) to ensure that connections are made and synergies exploited. Each sub-work package will be led by a member of the Management Team and supported by our Expert Fellows and Project Partners. WP1 Develop the Network We will deliver a set of activities designed to expand, broaden, and engage the network, from expert meetings and workshops to student bootcamps and international conferences. WP2 Engage stakeholders to enhance knowledge exchange and deliver impact. We will be greatly enhancing our purposive engagement activity in SPRITE+2. This activity will include a new business intelligence function and PP engagement grants, designed to enhance mutual understanding between researchers and stakeholders. WP3 Identify, prioritise, and explore future TIPS challenges We will select and then investigate priority areas of future TIPS. Two areas are pre-scoped based on the work we have done so far in SPRITE+ (TIPS in digital cities; trustworthy digital identities) with a further two be identified during the lead up to SPRITE+2. WP4 Drive innovation in research This WP concerns the initiation and production of high-quality impactful research. Through horizon scanning, sandpits and industry-led calls, we will steer ideas through an innovation pipeline ensuring SPRITE+2 is future focused. Cross cutting activities The first cross-cutting activity will accelerate the translation of TIPS research into policy and practice for public and private sector end uses. The second focuses on mechanisms to facilitate communication within our community. The experiences of SPRITE+ and the other DE Network+s demonstrate that it takes years of consistent and considerable effort for a new network to grow membership and develop productive relationships with stakeholders. In SPRITE+2 grant we would hit the ground running and maximise the impact of four additional years of funding. A successful track record, a well-established team, and a raft of ambitious new plans provide a solid foundation for strong delivery in 2023-27.

Autonomous Systems (AS) are cyberphysical complex systems that combine artificial intelligence with multi-layer operations. Security for dynamic and networked ASs has to develop new methods to address an uncertain and shifting operational environment and usage space. As such, we have developed an ambitious program to develop fundamental secure AS research covering both the technical and social aspects of security. Our research program is coupled with internationally leading test facilities for AS and security, providing a research platform for not only this TAS node, but the whole TAS ecosystem. To enhance impact, we have built a partnership with leading AS operators in the UK and across the world, ranging from industrial designers to frontline end-users. Our long-term goal is to translate the internationally leading research into real-world AS impact via a number of impact pathways. The research will accelerate UK's position as a leader in secure AS research and promote a safer society.

Underwater monitoring and surveillance (UMS) for a country surrounded by sea is an exceptionally important task. Important applications include port/harbour security, pollution monitoring, people trafficking, smuggling, maintaining integrity and detecting attacks on underwater infrastructure. The purpose of such systems is to detect, localise and classify underwater targets, and communicate this information to the authorities. The targets can be manned or unmanned underwater and surface vehicles, sources of pollution, mines, pipelines, cables, divers, swimmers, animals, etc. Surveillance has been traditionally based on using surface ships and manned submarines, which are very costly to operate. Due to the physical properties of water, UMS systems, in the majority of cases, exploit acoustic waves. Sound navigation and ranging (SONAR) is a key technology for underwater imaging and target detection, and is an equivalent technology to radio detection and ranging (RADAR) which is widely used in above water environments. Recent developments in underwater acoustic (UWA) communication networks, underwater robotics and vehicles make it timely to consider the development of cooperative UWA networks based on the use of low-cost static and moving sensor (including SONAR) nodes. Our hypothesis is that such networks can significantly enhance performance and reduce the cost of surveillance operations, and that UMS sonar, communication and navigation systems must be jointly designed and optimised to achieve the greatest performance. Given recent developments in radio systems for surveillance, it is clear that significant advances can be similarly achieved in UMS systems. Our aim in this project is to investigate and practically demonstrate (at sea) novel joint designs of low-cost UWA networks for enhanced UMS. This will build upon our experience and recent collaborative success in the theoretical research and practical design of UWA sensor networks at the respective universities.

Research Area: ART-AI is a multidisciplinary CDT, bringing together computer science, social science and engineering so that its graduates will be specialists in one subject, but have substantial training and experience in the others. The ART-AI management team brings together research in AI, HCI,politics/economics, and engineering, while the CDT as a whole has a team of >40 supervisors across seven departments in three faculties and the institutes for policy research (IPR) and for mathematical innovation (IMI). This is not a marriage of convenience: many CDT members have experience of interdisciplinary working and together with CDT cohorts and partners, we will create accessible, transparent and intelligible AI, driven by ethical and responsible principles, to address issues in, for example, policy design and political decision-making, development of trust in AI for humans and organisations, autonomous systems, sensing and data analysis, explanation of machine decision-making, public service design, social simulation and the ethics of socio-technical systems. Need: Hardly a day passes without a news article on the wonders and dangers of AI. But decisions - by individuals, organisations, society and government - on how to use or not use AI should be informed and ethical. We need policy experts to recognise both opportunities and threats, engineers to extend our technical capabilities, and scientists to establish what is tractable and to predict likely outcomes of policies and innovations. We need mutually informed decisions taking account of diverse needs and perspectives. This need is expressed in measured terms by a slew of major reports (see Case for Support) and Commons and Lords committees, all reflecting the UKCES Sector Insights (Evidence report #92, 2015) prediction of a need by 2022 for >0.5M additional workers in the digital sector against just a third of that number graduating annually. To realise the government vision for AI (White Paper), a critical fraction of those 0.5M workers need to be leaders and innovators with in-depth scientific and technical knowledge to make the right calls on what is possible, what is desirable, and how it can be most safely deployed. Beyond the UK, a 2018 PwC report indicates AI will impact ~10% of jobs, or ~326 million globally by 2030, with ~33% in high-skill jobs across most economic sectors. The clear conclusion is a need for a significant cadre of high-skill workers and leaders with a detailed knowledge of AI, an understanding of how to utilise it, and its political, social and economic implications. The ART-AI is designed to deliver these in collaboration and co-creation with stakeholders in these areas. Approach: ART-AI will produce interdisciplinary graduates and interdisciplinary research by (i) exposing its students to all three disciplines in the taught elements, (ii) fostering development of multi-discipline perspectives throughout the doctoral research process, and (iii) establishing international and stakeholder perspectives whilst contributing to immediate, real-world problems through a programme of visiting lecturers, research visits to leading institutions and internships. The CDT will use some conventional teaching, but the innovations in doctoral training are: (i) multi-disciplinary team projects; (ii) structured and facilitated horizontal (intra-cohort) peer learning and vertical (inter-cohort) mentoring, and in the interdisciplinary cross-cohort activities in years 2-4; (iii) demonstrated contextualisation of the primary discipline research in the other disciplines both at transfer (confirmation) at the end of year 2 and in the final dissertation. Each student will have a primary supervisor from their main discipline, a co-supervisor from at least one of the other two, and where appropriate, one from a CDT partner, reflecting the interdisciplinarity and co-creation that underpin the CDT.

This grant engages with conceptual, empirical and theoretical research questions about military learning processes which have the potential to substantially enhance the military effectiveness of NATO member-states in a wide-variety of operational contexts. The capacity of militaries to quickly capture successful individual/group adaptation and mistakes by deployed soldiers/allies as organisational learning is an enduring feature of military effectiveness. Poor intra- and inter-organisational learning capability reduces the relevance of key 'institutional military' activities, such as training, doctrine, and officer education, leaving soldiers in ongoing and future operations facing an 'adaptation trap' of relearning lessons in the field. The increasingly fast-changing nature of contemporary operational environments has sharpened the negative consequences of an adaptation trap for the safety of soldiers and civilians, and for operational/strategic success. Militaries have sought to rise to this challenge by establishing permanent 'lessons-learned' processes within service branches and the joint environment during the 2000s. Run by dedicated lessons-learned branches, they focus on improving a military's ability to identify best-practices and to uncover, resolve, and disseminate tactical- and operational-level lessons from exercises, operations, and allies. However, the potential of lessons-learned processes to revolutionise military learning remains untapped. Technological advances in communicating, storing, and disseminating information have not been accompanied by advances in the conceptual and organisational dimensions of lessons-learned processes. Practitioner guidance provides limited advice about how militaries can ameliorate barriers to learning. Military innovation studies, management studies, and organisation studies have also failed to examine best-practice in lessons-learned processes. Hence this project makes an important contribution to understanding the potential of lessons-learned by exploring three key conceptual, empirical, and theoretical themes. First, the lessons which can be drawn from management studies and organisation studies about best-practice in the activities which enhance the capacity of military lessons-learned processes to effectively acquire, manage, disseminate, and exploit lessons from operations, exercises, and allies ('absorptive capacity'). Second, the project will explore hitherto-unexplored case studies of small military early-adopters of lessons-learned processes: Estonia, the Netherlands, and Portugal. In doing so, it will explore the utility of best-practice gathered from the private and public sectors in a military setting and the challenges that small militaries face in running lessons-learned processes. The project will also explore the more general challenges of running lessons-learned processes in high-intensity warfare training exercises and stabilisation operations. The project will enquire whether innovative practices have emerged among smaller militaries which might enrich understanding of the fundamentals of lessons-learned best-practice, applicable to all militaries, and to other public sector organisations. Finally, the project will illuminate the scope for practitioner agency in improving lessons-learned processes by exploring the analytical leverage of neoclassical realism in theorising military learning. It will sharpen understanding of the mutually-constitutive relationship between structural barriers to learning, including bureaucratic politics, organisational culture, and strategic culture and the emergence of activities which enhance absorptive capacity. The research questions, timetable and detailed impact plan have been developed in cooperation with practitioners. Its findings will deliver outputs of direct relevance to their work and will be integrated into the NATO Lessons-Learned Handbook and NATO procedures, policy, directives, and training.