Round-trip policy engineering
Most policies are written by humans for humans. One line of attack on the problem of how to deliver the promise of autonomous system, while constraining their behaviour within human expectations – not that unexpected behaviour is necessarily bad! – is to use formal models of human and machine understandable policies to communicate those intentions. One formulation of the policy transduction problem is how to extract human intentions from natural language, verify that the extracted model is correct – for some definition of correct – and validate the model against user stories/use cases. A subsequent problem is policy maintenance and development: which version of the policy is the reference model? The natural language one or the formal model? This suggests a second transduction problem: how to render the formal model in natural language, sufficiently accurately, to limit the scope for mis-communication, while making both humans and software agents stakeholders in the evolution of the policy framework, taking account of a policy in isolation and its interaction with co-existing policies.
This project is associated with the UKRI CDT in Accountable, Responsible and Transparent AI (ART-AI), which is looking for its second cohort of at least 10 students to start in September 2020. Further details can be found at: www.bath.ac.uk/centres-for-doctoral-training/ukri-centre-for-doctoral-training-in-accountable-responsible-and-transparent-ai/.
Applicants should hold, or expect to receive, a First or Upper Second Class Honours degree. A master’s level qualification would also be advantageous.Desirable qualities in candidates include intellectual curiosity, a strong background in maths and programming experience.
Informal enquiries should be directed to Dr Julian Padget: [Email Address Removed].
Enquiries about the application process should be sent to [Email Address Removed].
Formal applications should be made via the University of Bath’s online application form: https://samis.bath.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RDUCM-FP02&code2=0002
Start date: 28 September 2020.
ART-AI CDT studentships are available on a competition basis for UK and EU students for up to 4 years. Funding will cover UK/EU tuition fees as well as providing maintenance at the UKRI doctoral stipend rate (£15,009 tax-free per annum in 2019/20, updated annually in line with the GDP deflator) and a training support fee of £1,000 per annum.
We also welcome all-year-round applications from self-funded candidates and candidates who can source their own funding.
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