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Details of Grant 

EPSRC Reference: EP/S023437/1
Title: UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent AI
Principal Investigator: O'Neill, Professor E
Other Investigators:
Carmel, Professor E Bryson, Dr JJ Durrant, Dr H
Hunter, Dr A Larkin, Dr CJ Lauder, Professor H
Padget, Dr J Wilson, Professor P De Vos, Dr M
Metcalfe, Dr BW Simsek, Professor Ö
Researcher Co-Investigators:
Project Partners:
Airbus Operations Limited AutoNaut BMT Group Ltd (UK)
CFMS Services Ltd Church of England Civica
Dalhousie University DeepMind Delft University of Technology
DesAcc EMEA Ltd. Financial Conduct Authority Google
IBM UK Ltd Max Planck Institutes Microsoft
Moogsoft National Institute of Informatics (NII) National Physical Laboratory NPL
NATO (North Atlantic Treaty Org) Ocado Group Office for National Statistics
Price Waterhouse Coopers LLP Rolls-Royce Plc (UK) Seiche Ltd
Spanish National Research Council CSIC Systems Engineering and Assessment Ltd. Tampere University (TAU)
Tsinghua University University of Melbourne University of Oslo
University of Potsdam University of Sao Paolo Willis Towers Watson (UK)
Zhejiang University
Department: Computer Science
Organisation: University of Bath
Scheme: Centre for Doctoral Training
Starts: 01 April 2019 Ends: 30 September 2027 Value (£): 7,275,875
EPSRC Research Topic Classifications:
Artificial Intelligence Ethics
Social Policy
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Communications
Financial Services Retail
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
07 Nov 2018 UKRI Centres for Doctoral Training AI Interview Panel U – November 2018 Announced
Summary on Grant Application Form
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.

Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.bath.ac.uk