AI for Science and Engineering Advice

This project will explore how artificial intelligence (AI) could and should be used to enhance the practice of translating scientific and engineering knowledge into public policy domains (‘science advice’). AI technologies have the potential to change the way that science advice is done in four key areas: synthesising evidence, horizon scanning, drafting policy briefs, and impact evaluation.

Science advice has been done the same way for decades. Advisers’ approaches to evidence syntheses and horizon scanning tend to be rather ad hoc. Policy briefs are one-size-fits-all and take months to produce. Impact evaluation often amounts to counting publications and event attendees. AI tools could revolutionise all these areas, from automating parts of the evidence synthesis process, to producing multiple versions of personalised policy briefs.

The design and application of future AI tools in science advisory systems will inevitably be complicated by legitimate concerns about rigour and trustworthiness. These tools must be co-created with academia and science advisory institutions. Processes will need to be developed to deal with system glitches, such as the tendency for ChatGPT to show political bias.

This PhD project will have two main goals. The first would be to identify AI technologies for science advice, and an assessment of opportunities and challenges in their use. The second goal would be to deliver real-world impact in policy institutions. The programme will be designed from the outset as practice-oriented and will aim to offer advice on and toolkits for the deployment of AI technology for science advice, and/or the production of AI tools for use in science advice.

Project supervisor

Dr Chris Tyler, Associate Professor in Science Policy and Knowledge Infrastructure within UCL’s Department of Science, Technology, Engineering and Public Policy (STEaPP).

Eligibility and how to apply

We are looking for a PhD candidate with a background in computer science (essential) and experience in public policy (desirable).

Full details on eligibility and how to apply can be found here (link to: https://www.ucl.ac.uk/epsrc-doctoral-training/prospective-students/apply-ucl-epsrc-dtp-studentship#eligibility)

If you have any questions please contact Dr Chris Tyler at [Email Address Removed] or [Email Address Removed]

Duration of award

4 years