We address the timely topic of online gender-based violence (GBV): Almost 1 in every 2 women and non-binary people (46%) reported experiencing online abuse since the beginning of COVID-19 (Glitch report, 2020). Our aim is to create 'equally safe' online spaces by prevention, intervention and support for online GBV through the development of advanced Machine Learning algorithms. In contrast to previous research in this area, our team will include experts on GBV and online harassment to ensure that we frame the problem in a way which is most helpful to victims/survivors of GBV. In other words, we not only focus on *how* to automatically detect online abuse, but also re-think *what* it is we need to detect, how we can *support* the victims and how to *prevent* online GBV through promoting digital citizenship (i.e. prevention and intervention aimed at perpetrators and bystanders). Our methodology is based on the Scottish Government's Equally Safe strategy and implements a Responsible Innovation Approach in a close collaboration with 3rd sector charities with a long-standing track record in this domain. Our proposal aims to create the following impacts: 1. Create longterm technical solutions to support safer online spaces, including advanced abuse detection tools, tools to automatically generate counter narratives aimed at perpetrators and bystanders, and a chatbot for providing proactive support to victims/survivors. 2. Promote 'equitable' algorithms which are able to reflect multiple perspectives/viewpoints and not marginalise minority views; 3. Increase digital literacy concerning the safe use of social media from an early age.

We urgently need proactive health support at the level of the general population: we have become, on average, an unhealthy nation. The new statistical norm is overweight to obese (60% of men and 49% of women). Co-related conditions from heart disease to type II diabetes, cost the NHS £48 Bn/year. Lack of sleep costs £40Bn. Stress costs £40Bn. 6% of our GDP goes to preventable "lifestyle conditions." Of the top 20 western nations, the UK ranks 18th or lower in QoL, Health, Wealth, Education and Democracy. Our productivity is 20% lower than the rest of the G7. While there is incredible optimism and investment in the potential benefits of ubiquitous, pervasive technology to help redress these conditions, digital health approaches to date have had low impact. This fellowship hypothesises that the lack of broad and sustained uptake of digital health technology is not a fault of the technology per se but with the range of models that inform how these technologies are designed. The current state of the art in digital health tech is (i) targeted at individuals although health practices are significantly influenced by social contexts; (ii) it assumes that given the right data we will make a rational decision to adopt a health practice without taking into account how the rest of our bodies - from our gut to our nervous system - is involved in decision processes (iii) the tools themselves can be antagonistic to rather than supporting of how the body works. E.g. a "smart alarm" that still disrupts sleep rather than finds ways to help us get sleep is antagonistic to our physiology which requires certain amounts of sleep to stay healthy. While current digital health technologies can and do work for some of the people some of the time, they have not been sufficient to deliver health in the complex contexts in which the UK lives and works. We need to develop better models to inform health tech design. This fellowship proposes to develop and test Inbodied Interaction (the alignment of health tech with how the body optimally performs) as a foundation to deliver and sustain personal and social Health Resilience: the capacity for individuals and their groups to build health knowledge, skills and practice to recover from and redress health challenges, from stress at home to shift changes at work. In line with EPSRC's challenge to "transform community health" by enabling better "self-management," digital interactive technologies must be aligned with how we work as organic-physical-cognitive-social complex systems. In respect of that model of "self" the fellowship will innovate on three strands of inbodied interaction technology: 1) Environment-Body Aligned: designing technology to support our physiology, from displays that help us maintain peripheral vision to stay more creative, to light use in VR lenses to improve cognitive performance. 2) Experience-to-Practice Aligned: to provide rapid access to the effects of better health experiences, and connect these with personally effective means to maintain these. 3) Group-to-Culture Aligned: to support groups identify and build more health resilient practices that work for their contexts. Thus "self-management" is transformed into our 3-level model of how this "self" is empowered by health tech in various contexts to create build and maintain "health." Through our co-design we will be engaging directly with hundreds of participants, and thousands more citizens virtually through our nation-wide Citizen Scientist web trials. We also have regular engagement with our expert advisory team representing industry, policy, and a range of disciplines. The Team is committed to help translate our work from project to practice, from policy to process, for transformational impact. By Fellowship end, we will have new digital health technologies and validated models for those tools to deliver Health Resilience for a Healthy Nation, and so help #makeNormalBetter@scale, for all.

Our mission is to train the next generations of innovators in responsible, data-driven and knowledge-intensive human-in-the-loop AI systems. Our innovative, cohort-based training programme will deliver cohorts of highly trained PhD graduates with the skills to design and implement complex interactive AI pipelines solving societally important problems in responsible ways. While fully autonomous artificial intelligence dominates today's headlines in the form of self-driving cars and human-level game play, the key AI challenges of tomorrow are posed by the need for interactive knowledge-intensive systems in which the human plays an essential role, be it as an end-user providing relevant case-specific knowledge or interrogating the system, an operator requiring crucial information to be presented in an intelligible form, a supervisor requiring confirmation that the system's performance remains within acceptable limits, or a regulator assessing to what extent the system operates according to exacting standards concerning transparency, accountability and fairness. Each of these examples demonstrates a need for specific and meaningful interaction between the AI system and human(s). The examples also demonstrate the importance of knowledge for achieving human-level interaction, in addition to the data driving the machine learning aspect of the system. In close conversation with our industry partners we thus identified Interactive Artificial Intelligence (IAI) as a core sub-discipline of AI where the need for and deficit in advanced AI skills is abundantly evident while being homogeneous enough to have intellectual integrity and be taught and researched within the context of a single CDT. The most important aspects of the training programme are: - Knowledge-Driven AI and Data-Driven AI are core components treated in a close symbiotic relationship: the former uses knowledge in processes such as reasoning, argumentation and dialogue, but in such a way that data is treated as a first-class citizen; the latter starts from data but emphasises knowledge-intensive forms of machine learning such as relational learning which take knowledge as an additional input. - Human-AI Interaction is another core component addressing all human-in-the-loop aspects, overseen by a co-investigator from the human-computer interaction field. - Responsible AI is underpinning not just the taught first year but the students' doctoral training throughout all four years, overseen by two dedicated co-investigators with backgrounds in IT law and industrial codes of practice. Other skill requirements from stakeholders include: the ability to design and implement complete end-to-end systems; acquiring depth in some AI-related subjects without sacrificing breadth; the ability to work in teams of people with diverse skill sets; and being able to take on a role as "AI ambassadors" who are able to inspire but also to manage expectations through their in-depth understanding of the strengths and weaknesses of different AI techniques. The IAI training programme is designed to achieve this by strongly emphasising cohort-based training. Students will develop their projects and coursework within an innovative software environment which means easy integration of their work with that of others. This virtual hub is complemented by a physical hub where all cohorts are colocated -- together both hubs will strongly promote interaction both within and between cohorts: e.g., projects can aim at improving or extending software produced by the previous cohort, so that senior students can be involved in mentoring their juniors. In summary, the IAI training programme pulls together Bristol's unique and comprehensive strengths in doctoral training and AI to deliver highly trained AI innovators, equipping them with essential skills to deliver the interactive AI technology society requires to deal with current and future challenges.

Modern society faces a fundamental problem: the reliability of complex, evolving software systems on which it critically depends cannot be guaranteed by the established, non-mathematical techniques, such as informal prose specification and ad-hoc testing. Modern companies are moving fast, leaving little time for code analysis and testing; concurrent and distributed programs cannot be adequately assessed via traditional testing methods; users of mobile applications neglect to apply software fixes; and malicious users increasingly exploit programming errors, causing major security disruptions. Trustworthy, reliable software is becoming harder to achieve, whilst new business and cyber-security challenges make it of escalating importance. Developers cope with complexity using abstraction: the breaking up of systems into components and layers connected via software interfaces. These interfaces are described using specifications: for example, documentation in English; test suites with varying degrees of rigour; static typing embedded in programming languages; and formal specifications written in various logics. In computer science, despite widespread agreement on the importance of abstraction, specifications are often seen as an afterthought and a hindrance to software development, and are rarely justified. Formal specification as part of the industrial software design process is in its infancy. My over-arching research vision is to bring scientific, mathematical method to the specification and verification of modern software systems. A fundamental unifying theme of my current work is my unique emphasis on what it means for a formal specification to be appropriate for the task in hand, properly evaluated and useful for real-world applications. Specifications should be validated, with proper evidence that they describe what they should. This validation can come in many forms, from formal verification through systematic testing to precise argumentation that a formal specification accurately captures an English standard. Specifications should be useful, identifying compositional building blocks that are intuitive and helpful to clients both now and in future. Specifications should be just right, providing a clear logical boundary between implementations and client programs. VeTSpec has four related objectives, exploring different strengths of program specification, real-world program library specification and mechanised language specification, in each case determining what it means for the specification to be appropriate, properly evaluated and useful for real-world applications. Objective A: Tractable reasoning about concurrency and distribution is a long-standing, difficult problem. I will develop the fundamental theory for the verified specification of concurrent programs and distributed systems, focussing on safety properties for programs based on primitive atomic commands, safety properties for programs based on more complex atomic transactions used in software transactional memory and distributed databases, and progress properties. Objective B: JavaScript is the most widespread dynamic language, used by 94.8% of websites. Its dynamic nature and complex semantics make it a difficult target for verified specification. I will develop logic-based analysis tools for the specification, verification and testing of JavaScript programs, intertwining theoretical results with properly engineered tool development. Objective C: The mechanised specification of real-world programming languages is well-established. Such specifications are difficult to maintain and their use is not fully explored. I will provide a maintainable mechanised specification of Javascript, together with systematic test generation from this specification. Objective D: I will explore fundamental, conceptual questions associated with the ambitious VeTSpec goal to bring scientific, mathematical method to the specification of modern software systems.

Promoting improved understanding of how children's daily lives are influenced by the digital world that now surrounds them and how they experience family, peer and school life as a result represents a substantial challenge and opportunity relative to facilitating positive mental health and development for children and young people. Historically, researchers have emphasised the role of supportive parenting and positive school experiences (including peer relationships) as primary social environmental influences on children's mental health, with most interventions targeting family and school-based influences aimed at remediating poor mental health outcomes for children and young people. It is increasingly recognised that the digital environment constitutes a new dimension or common denominator to these traditional agencies of socialisation influence on children's mental health. Yet, little progress has been made in equipping parents, teachers and the professional agencies that work with families and schools with new knowledge that harnesses potential strengths while offering protection from substantial risks posed to children by the digital world. How do we equip parents, teachers, practitioners, policy makers and youth themselves with information, support and resources that promotes positive mental health in a contemporary (and future) digital age? Addressing this core challenge represents the primary objective of our multi-disciplinary e-Nurture network. While significant advances have been made in relation to highlighting and understanding the genetic and biological underpinnings of poor mental health and mental health disorders in recent years, it is recognised that the social environments children experience and interact with remain a substantial influence on their positive and negative mental health trajectories (even when genetic factors are considered). Three primary areas of social environmental influence on children's mental health have dominated past research and practice in this area. First, family socialisation processes, specifically parenting practices are recognised as a substantive influence on children's mental health. Second, peer influences are noted as an important influence on children's mental health. Third, school-based factors are recognised as a further influence on children's mental health and development. Increasingly, the digital environment is recognised as a factor that both infuses traditional agencies of socialisation for children and that can influence children directly. Policy makers have recently directed significant attention to the prevalence rates and support needs among children and young people who experience mental health problems. The digital environment and its potential for positive and negative influences on children's well-being, mental health and development has also received substantial research, policy and media attention. Building on this policy platform, the primary objectives of our network are to (1) explore how the digital environment has changed the ways in which children experience and interact with family, school and peer-based influences and what these changes mean for children's mental health, (2) identify how we can recognise and disentangle digital risks from opportunities when working with families, schools and professional agencies in developing intervention programmes to improve mental health outcomes for children and young people, and (3) identify how we effectively incorporate and disseminate this new knowledge to engage present and future practice models and the design and development of digital platforms and interventions aimed at promoting mental health and reducing negative mental health trajectories for young people. The network will engage a collaborative, cross sectoral approach to facilitating impacts by directly engaging academic, charity, industry, policy and front-line beneficiaries (e.g. families, parents, schools, teachers, children and young people).