UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent AI

Lead Research Organisation: University of Bath
Department Name: Computer Science


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.

Planned Impact

The AI sector is projected to have a very significant impact on the UK economy according to the government's own white paper and several government and independent reports (see Case for Support). Realizing that impact will very much depend on individuals who understand technological capabilities, societal needs for and implications of AI systems, and have the technical skills to deliver them. ART-AI CDT targets future decision-making and leadership positions, since without a deep understanding of the technology's capabilities, limitations and attendant risks, it is easy to make the wrong decision. The consequences, economically, societally and potentially physically, could be
great (e.g. the 2008 banking crisis). The aim of this CDT is to ensure that the UK has people with the right training in the right places across the economy.

ART-AI not only addresses the traditional separation of science and engineering that hinders the translation of scientific excellence into responsible innovative outcomes, but also the more entrenched divide between the humanities and STEM, by embedding the CDT's graduates' research and innovation in a social science context, through which to construct multi-perspective analyses of the implications of applications. In so doing, ART-AI will impact not only these disciplines but also the economic and societal sectors to which they connect via our diverse range of partners. Our partners illustrate the interest, and the importance accorded to the challenges that society with AI represents, across commerce and industry as well as in government and NGOs. Academic and non-academic partner representatives will sit on a key CDT board, give specialist lectures, and participate in the residential and other cohort events to meet students, make presentations, generate research priorities, and discuss job opportunities.

International and academic impact comes from a) publishing in leading journals and conferences, b) 3-6 months research placements at our international academic partners to set up and strengthen long term collaborations, c) ART-AI workshops and summer/winter schools with our academic partners to engage with the wider academic community. Current partners include: Artificial Intelligence Research Institute (CSIC, Barcelona), National Institute for Informatics (Tokyo), Technical University of Delft (Delft Design for Values Institute), Tsinghua University, University of Tampere, University of Potsdam, Zhejiang University.

Industrial, commercial and governmental impact will come from PhD students spending 3 to 6 months at a non-academic project partner, e.g. Airbus, BMT Limited, the Church of England, Civica, the FCA, Google AI, IBM, Microsoft, NPL, Ocado, the ONS, PwC, Rolls-Royce, SEA, Seiche or WillisTowersWatson, to work on their research. Further impact with our partners is facilitated through our AI Challenge days. Bringing all partners together bi-annually will foster information and impact sharing between all our partners.

Through a range of public engagement activities, as part of their training, our students will reach out to the wider community. AI receives a lot of coverage in the press these days. However the understanding of what AI truly is and what it currently can do and cannot do is probably understood by only a few, mainly the AI researchers and practitioners themselves. Through public engagement we aim to start the process of de-mystifying AI and to allow citizens to develop a more informed understanding of the technology that is impacting their lives.

Impact will not stop with graduation: we will continue to work with ART-AI graduates by encouraging their continuing participation in CDT activities. In this way, we will continue to track and facilitate further impact with and through our graduates, e.g. via initiatives to convert research into commercially viable products (Lords report, para.159, Govt. response para.40).



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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023437/1 01/04/2019 30/09/2027
2283260 Studentship EP/S023437/1 30/09/2019 30/09/2023 Jack Roe SAUNDERS
2283238 Studentship EP/S023437/1 30/09/2019 30/09/2024 Elena SAFRYGINA
2282644 Studentship EP/S023437/1 30/09/2019 30/09/2023 Mafalda RIBEIRO
2284306 Studentship EP/S023437/1 30/09/2019 30/09/2023 Huixin ZHONG
2282428 Studentship EP/S023437/1 30/09/2019 30/09/2023 Akshil PATEL
2283246 Studentship EP/S023437/1 30/09/2019 30/09/2023 Jack Euan SAUNDERS
2279205 Studentship EP/S023437/1 30/09/2019 30/09/2023 Oscar BRYAN
2279286 Studentship EP/S023437/1 30/09/2019 30/09/2023 George FLETCHER
2283562 Studentship EP/S023437/1 30/09/2019 30/09/2023 Damian ZIUBRONIEWICZ
2279122 Studentship EP/S023437/1 30/09/2019 30/09/2023 Catriona GRAY
2455562 Studentship EP/S023437/1 28/09/2020 30/09/2024 Alexander David TAYLOR
2486024 Studentship EP/S023437/1 28/09/2020 30/09/2024 Jessica Maria NICHOLSON
2436123 Studentship EP/S023437/1 01/10/2020 30/09/2024 Deborah MORGAN
2432473 Studentship EP/S023437/1 01/10/2020 30/09/2024 Andrew EVANS
2435204 Studentship EP/S023437/1 01/10/2020 30/09/2024 Joseph GOODIER
2446449 Studentship EP/S023437/1 01/10/2020 30/09/2024 Thao DO
2436503 Studentship EP/S023437/1 01/10/2020 30/09/2024 Emma LI
2441784 Studentship EP/S023437/1 01/10/2020 30/09/2024 Scott WELLINGTON
2435257 Studentship EP/S023437/1 01/10/2020 30/09/2024 Finnian HAMBLY
2431958 Studentship EP/S023437/1 01/10/2020 30/09/2024 Edward CLARK
2440213 Studentship EP/S023437/1 01/10/2020 31/03/2025 Brier RIGBY DAMES
2436774 Studentship EP/S023437/1 01/10/2020 30/09/2024 Alice PARFETT
2427780 Studentship EP/S023437/1 01/10/2020 20/10/2020 Peter BAYLISS
2436078 Studentship EP/S023437/1 01/10/2020 30/09/2024 Pablo Jesus MEDINA ALIAS
2435119 Studentship EP/S023437/1 01/10/2020 30/09/2024 Thomas DONNELLY
2436013 Studentship EP/S023437/1 01/10/2020 30/09/2024 Matthew HEWITT