As computing systems become increasingly autonomous--able to independently pilot vehicles, detect fraudulent banking transactions, or read and diagnose our medical scans--it is vital that humans can confidently assess and ensure their trustworthiness. Our project develops a novel, people-centred approach to overcoming a major obstacle to this, known as responsibility gaps. Responsibility gaps occur when we cannot identify a person who is morally responsible for an action with high moral stakes, either because it is unclear who was behind the act, or because the agent does not meet the conditions for moral responsibility; for example, if the act was not voluntary, or if the agent was not aware of it. Responsibility gaps are a problem because holding others responsible for what they do is how we maintain social trust. Autonomous systems create new responsibility gaps. They operate in high-stakes areas such as health and finance, but their actions may not be under the control of a morally responsible person, or may not be fully understandable or predictable by humans due to complex 'black-box' algorithms driving these actions. To make such systems trustworthy, we need to find a way of bridging these gaps. Our project draws upon research in philosophy, cognitive science, law and AI to develop new ways for autonomous system developers, users and regulators to bridge responsibility gaps-by boosting the ability of systems to deliver a vital and understudied component of responsibility, namely answerability. When we say someone is 'answerable' for an act, it is a way of talking about their responsibility. But answerability is not about having someone to blame; it is about supplying people who are affected by our actions with the answers they need or expect. Responsible humans answer for actions in many different ways; they can explain, justify, reconsider, apologise, offer amends, make changes or take future precautions. Answerability encompasses a richer set of responsibility practices than explainability in computing, or accountability in law. Often, the very act of answering for our actions improves us, helping us be more responsible and trustworthy in the future. This is why answerability is key to bridging responsibility gaps. It is not about who we name as the 'responsible person' (which is more difficult to identify in autonomous systems), but about what we owe to the people holding the system responsible. If the system as a whole (machines + people) can get better at giving the answers that are owed, the system can still meet present and future responsibilities to others. Hence, answerability is a system capability for executing responsibilities that can bridge responsibility gaps. Our ambition is to provide the theoretical and empirical evidence and computational techniques that demonstrate how to enable autonomous systems (including wider "systems" of developers, owners, users, etc) to supply the kinds of answers that people seek from trustworthy agents. Our first workstream establishes the theoretical and conceptual framework that allows answerability to be better understood and executed by system developers, users and regulators. The second workstream grounds this in a people-centred, evidence-driven approach by engaging various publics, users, beneficiaries and regulators of autonomous systems in the research. Focus groups, workshops and interviews will be used to discuss cases and scenarios in health, finance and government that reveal what kinds of answers people expect from trustworthy systems operating in these areas. Finally, our third workstream develops novel computational AI techniques for boosting the answerability of autonomous systems through more dialogical and responsive interfaces with users and regulators. Our research outputs and activities will produce a mix of academic, industry and public-facing resources for designing, deploying and governing more answerable autonomous systems.

The UK RDRF brings together a number of research strands funded under the DET, EPSRC and ESRC portfolios over the last decade to create a national facility to tackle the vexed question of regional competitiveness and rebalancing the UK economy. Following the Scottish referendum there have been renewed calls for greater devolution to regions and core cities. This facility will bring together the big economic data and construct the high resolution models needed to support policy makers at national, regional and local level. It will innovate by building together a model of the fixed stock of buildings, including housing, commercial, warehousing and manufacturing, with a network model of key infrastructure. This will allow analysis of which policy nudges might be expected to overcome the inertia present in the historic geography of the UK. It will allow a common framework of data and evidence ti be used by regional and local policy professionals wishing to evaluate policy options. The whole facility is built on the opportunity created by CDT funding to develop a cohort of evidence based policy professionals and analysts to support the needs of a more devolved form of planning. We aim to support the creation of a 'community of practice' based on access to big economic data and open source analysis and modelling tools. We will host workshops and networks to spread best practice and create some institutional glue amongst the people concerned. Finally, we will engage local communities in the debate and bring the same evidence and tools to the public at large through crowd science and in-the-wild research engagement.

The Lancaster Centre for Doctoral Training in Statistics and Operational Research (STOR) will meet the current critical need to address the national skills shortage within both disciplines. These complementary areas of mathematics underpin a wide-range of industries including defence, healthcare, finance, energy and transport. Thus, the development of this integrated, industrially-focused doctoral training centre is key for national competitiveness. Combined with the input of our industrial partners, the formation of the centre will provide a research training environment focused on methodological research motivated and applied to important real scientific/industrial applications. The centre will be designed to attract, train and nurture the analytic research capacity of the UK's strongest numerate graduates, thus developing a generation of doctoral scientists capable of applying their research skills to industrial applications through either academic or industrial career paths. Key aims of centre are:(i) to increase national doctoral recruitment into STOR through a programme attractive to substantial numbers of students outside those who would normally consider doctoral study in the area; (ii) to train graduates capable of producing research of high quality and with major industrial and scientific impact;(iii) to produce highly employable graduates equipped with the broad skills needed for rapid career progression in academia or industry;(iv) to stimulate research at the interface of STOR through doctoral projects which span the disciplines. The long-term vision for this centre is that it will grow into a national centre of excellence for a collaborative doctoral training environment in STOR between academia and industry, leading to a sustainable model for better exploitation of research.

Lancaster University (LU) proposes a Centre for Doctoral Training (CDT) whose goal is the development of international research leaders in statistics and operational research (STOR) through a programme in which industrial challenge is the catalyst for methodological advance. The proposal brings together LU's considerable academic strength in STOR with a formidable array of external partners, both academic and industrial. All are committed to the development of graduates capable of either leadership roles in industry or of taking their experience of and commitment to industrial engagement into academic leadership in STOR. The proposal develops an existing EPSRC-funded CDT (STOR-i) by a significant evolution of its mission which takes its degree of industrial engagement to a new level. This considerably enhanced engagement will further strengthen STOR-i's cohort-based training and will result in a minimum of 80% of students undertaking doctoral projects joint with industry, up from 50% in the current Centre. Industrial internships will be provided for those not following a PhD with industry. Industry will (i) play a role in steering the Centre, (ii) has co-designed the training programme, (iii) will co-fund and co-supervise industrial doctoral projects, (iv) will lead a programme of industrial problem-solving days and (v) will play a major role in the Centre's programme of leadership development. Industry's financial backing is providing for stipend enhancement and a range of infrastructure and training support as well as helping to bring STOR-i benefits to a wide audience. The total pledged support for STOR-i is over £5M (including £1.1M cash). The proposal addresses the priority area 'Industrially-Focussed Mathematical Modelling'. Within this theme we specifically target 'Statistics' (itself a priority area) and Operational Research (OR). This choice is motivated first by the pervasive need for STOR solutions within modern industrial problems and second by the widely acknowledged and long standing skills-shortage at doctoral level in these areas. Our partners' statements of support attest that the substantial recent growth in data acquisition and data-driven business and industrial decision-making have signalled a step change in the demand for high level STOR expertise and have opened the skills gap still wider. The current Centre has demonstrated that a high quality, industrially engaged programme of research training can create a high demand for places among the very ablest mathematically trained students, including many who would otherwise not have considered doctoral study in STOR. We believe that the new Centre will play a yet more strategic role than its predecessor in meeting the persistent skills gap. Our training programme is designed to do more than solve a numbers problem. There is an issue of quality of graduating doctoral students in STOR as much as there is one of quantity. Our goal is to develop research leaders who are able to secure impact for their work across academic, scientific and industrial boundaries; who can work alongside others who are differently skilled and who can communicate widely. Our external partners are strongly motivated to join us in achieving this through STOR-i's cohort-based training programme. We have little doubt that our graduates will be in great demand across a wide range of sectors, both industral and academic. The need for a Centre to deliver the training resides primarily in its guarantee of a critical mass of outstanding students. This firstly enables us to design a training programme around student cohorts in which peer to peer learning is a major feature. Second, we are able to attract and integrate the high quality contributions (both internal and external to LU) we need to create a programme of quality, scope and ambition.

CENTRE VISION Our vision for the new CDT in Financial Computing and Analytics is to as a national 'beacon' linking PhD & Masters' students, industry and academia in financial computing and analytics. We and our Industry partners are also central to the forthcoming investments in Big Data from EPSRC and ESRC (e.g. Business Datasafe). Its principal objective is to educate the next generation of elite PhDs with unparalleled, cross-disciplinary expertise in applied computing, analytics and financial mathematics, as well as in-depth sector understanding, to meet an increasing demand for their skills within the Financial Service Industry, Government, Retail and other Service sectors. Our existing DTC in Financial Computing is unique (there is no other research & training activity like it in the world) and by placing our PhD students in financial institutions and regulators it has had a major impact on the UK financial sector, as indicated by the Financial Times article (School for QUANTS) and our Letters of Support. The CDT is a new partnership between UCL, LSE and ICL, all providing MRes courses and PhD supervision. NATIONAL IMPORTANCE & GROWING NEED FOR CROSS-DISCIPLINARY SKILLS London is the world's leading international financial centre and the UK financial services industry is the key sector for the UK economy, contributed £124bn to the UK economy, generating a trade surplus of £36bn in 2010 and employing 1 million people. London is also the location for our financial regulators and world-class Retailers. Our Financial and other Service industries are therefore crucial to the UK's, and especially London's, continuing social and economic prosperity. Although we receive over 600 enquiries/applications per annum, and growing, recent reports by McKinsey and Accenture highlight the major and growing skills shortage of (postgrad) IT/data scientists in the USA 22,000 and the UK 4,000. EPSRC PRIORITIES AND RESEARCH The proposed CDT is aligned to EPSRC priorities across a number of Themes, in particular: Data to Knowledge (an ICT Theme priority), Industrially Focussed Mathematical Modelling (Mathematical Sciences) and New Digital Ventures (Digital Economy). The crucially important IT research challenges in just one area, namely the application of software engineering, AI and verification/correctness to algorithms for automated trading, illustrates the enormous research opportunities. IMPACT The current DTC in Financial Computing is acknowledged by the Department of Business Innovation & Skills as having had a major impact on our financial industry partners and on our academic partners. This will continue with the new CDT, impacting Regulators, government, Retailers and analytics companies. * STUDENTS - In 2011 the Centre funded more female PhD students than males, and in 2012 the Centre started 40 new PhD students if we count DTC funded students, students funded by other sources, such as retail and analytics companies, and industry-based part-time students. * ACADEMIA - UCL, LSE and Imperial College have all appointed new faculty in applied financial computing and business analytics; and UCL and ICL have started new Masters programmes. * INDUSTRY - many of the Banks now have established formal PhD programmes, in part due to the current DTC, and proved lecturers to the partners for industry-oriented programmes. * REGULATORS AND GOVERNMENT- we have placed PhD students in the BoE/FSA/PRA/FCA and the Cabinet Office, and as discussed in the Case for Support, we have held individual meetings and workshops with the Regulators (BoE, PRA, FCA) and with new (Retailer) partners (Tesco, BUPA, Unilever) to discuss how we can support them. * SOCIETAL - we encourage and support our PhD students in launching their own start-up, and we provide Masters and Undergraduate students to London-based start-ups, especially in the area called New Finance (e.g. P2P lending, crowdfunding).