Society is seeing enormous growth in the development and implementation of autonomous systems, which can offer significant benefits to citizens, communities, and businesses. The potential for improvements in societal wellbeing is substantial. However, this positive potential is balanced by a similar potential for societal harm through contingent effects such as the environmental footprint of autonomous systems, systemic disadvantage for some socio-economic groups, and entrenchment of digital divides. The rollout of autonomous systems must therefore be addressed with responsibilities to society in mind. This must include engaging in dialogue with society and with those affected, trying to anticipate challenges before they occur, and responding to them. One such anticipated challenge is the effect of change on autonomous systems. Autonomous systems are not designed to be deployed in conditions of perfect stasis, as they are unlikely to encounter such conditions in real-world environments. They are frequently designed for changing environments, like public roads, and may also be designed to change themselves over time, for instance by means of learning capabilities. Not only that, but these changes in deployed systems and in their operating conditions are also likely to take place against a shifting contextual background of societal alteration (e.g. other technologies, 'black swan' events, or simply the day-to-day operation of communities). The effects of such change, on the systems themselves, on the environments within which they are operating, and on the humans with which they engage, must be considered as part of a responsible innovation approach. The RAILS project brings together a team from UCL and the Universities of York, Leeds and Oxford, from multiple disciplines, with the aim of engaging with the challenges associated with the long-term operation of autonomous systems and the effects of change on these systems. In particular, we will explore how the notion of responsibility is affected by (i) open-ended dynamic environments - situations that change over time, and (ii) lifelong-learning systems - i.e. systems that are designed to adapt themselves to their circumstances and 'learn' over time. The RAILS project will focus on such independent long-term autonomous systems in different applications. These will include (i) autonomous vehicles and (ii) autonomous robot systems such as unmanned aerial vehicles (drones). RAILS will look at social and legal contexts, as well as technical requirements, in order to assess whether and how these systems can be designed, developed, and operated in a way that they are responsible, accountable, and trustworthy. The overall aim of the RAILS project is to bring together responsible development principles with governance mechanisms and technical understanding to create new understandings of how autonomous systems can adapt to change, how they can be deployed in a responsible and trustworthy way, and how such deployment can be framed by governance to ensure accountability and flexibility.

A growing consensus identifies autonomous systems as core to future UK prosperity, but only if the present skills shortage is addressed. The AIMS CDT was founded in 2014 to address the training of future leaders in autonomous systems, and has established a strong track record in attracting excellent applicants, building cohorts of research students and taking Oxford's world-leading research on autonomy to achieve industrial impact. We seek the renewal of the CDT to cement its successes in sustainable urban development (including transport and finance), and to extend to applications in extreme and challenging environments and smart health, while strengthening training on the ethical and societal impacts of autonomy. Need for Training: Autonomous systems have been the subject of a recent report from the Royal Society, and an independent review from Professor Dame Wendy Hall and Jérôme Pesenti. Both reports emphatically underline the economic importance of AI to the UK, estimating that "AI could add an additional USD $814 billion (£630bn) to the UK economy by 2035". Both reports also highlight the urgency of training many more skilled experts in autonomy: the summary of the Royal Society's report states "further support is needed to build advanced skills in machine learning. There is already high demand for people with advanced skills, and additional resources to increase this talent pool are critically needed." In contrast with pure Artificial Intelligence CDTs, AIMS places emphasis on the challenges of building end-to-end autonomous systems: such systems require not just Machine Learning, but the disciplines of Robotics and Vision, Cyber-Physical Systems, Control and Verification. Through this cross-disciplinary training, the AIMS CDT is in a unique position to provide positive economic and societal impacts for autonomous systems by 1) growing its existing strengths in sustainable urban development, including autonomous vehicles and quantitative finance, and 2) expanding its scope to the two new application pillars of extreme and challenging environments and smart health. AIMS itself provides evidence for the strong and increasing demand for training in these areas, with an increase in application numbers from 49 to 190 over the last five years. The increase in applications is mirrored by the increase in interest from industrial partners, which has more than doubled since 2014. Our partners span all application areas of AIMS and their contributions, which include training, internships and co-supervision opportunities, will immerse our students in a variety of research challenges linked with real-world problems. Training programme: AIMS has and will provide broad cohort training in autonomous intelligent systems; theoretical foundations, systems research, industry-initiated projects and transferable skills. It covers a comprehensive range of topics centered around a hub of courses in Machine Learning; subsequent spokes provide training in Robotics and Vision, Control and Verification, and Cyber-Physical Systems. The cohort-focused training program will equip our students with both core technical skills via weekly courses, research skills via mini and long projects, as well as transferable skills, opportunities for public engagement, and training on entrepreneurship and IP. The growing societal impacts of autonomous systems demand that future AIMS students receive explicit training in responsible and ethical research and innovation, which will be provided by ORBIT. Additionally, courses on AI ethics, safety, governance and economic impacts will be delivered by Oxford's world-leading Future of Humanity Institute, Oxford Uehiro Centre for Practical Ethics and Oxford Martin Programme on Technology and Employment.