Burges Salmon’s specialist team, led by Tom Whittaker, authored the practical chapter alongside Rebecca Williams (Professor of Public Law and Criminal Law, University of Oxford) and Azeem Suterwalla and Will Perry (Monckton Chambers).
During the research and drafting of the chapter the authors made a series of observations relevant to practitioners, which they thought may be of assistance to the questions raised by the Public Accounts Committee’s consultation into public sector use of AI. Those points are also of practical importance to those in the public sector looking to procure, build and use AI.
The full response can be found here. The key points are:
- Definitions - it is unclear whether the public sector use a single, consistent definition of “artificial intelligence” or of specific types of AI technology, such as generative AI. Government strategies, the White Paper on AI regulation (2022 and the response in 2023), and various government guidance notes all describe AI loosely, differently, and based on thematic issues, such as adaptability and autonomy. That varied approach may prove an issue when trying to create a precise and comprehensive overview of where AI is used in the public sector.
- Known uses - there is no publicly available, comprehensive, updated register of uses of AI in the UK public sector. This is changing since our consultation response, as the UK government has announced it intends for the Algorithmic Transparency Recording Standard to be used by all public bodies. However, there are likely to be exceptions, and we do not yet know what this looks like in practice. Consequently, accurately and comprehensively identifying when and where the public sector is using AI is difficult.
- Guidance - up-to-date guidance for public sector use of AI was relatively limited, appears to be fragmented and has not been updated; for example, UK government’s A guide to using artificial intelligence in the public sector was published in June 2019 and last updated October 2019, and has no reference to generative AI.
- Disputes - identifying when and where challenges are bought to the use of AI by public bodies is limited. Court data is limited, so monitoring and analysing disputes related to AI is difficult.
- Legal risk - common law is capable of evolving with emerging technologies and use cases. However, there remains a risk that - without greater transparency of public sector use of AI and review of potential legal issues arising - increasing and evolving public sector use of AI raises novel legal risks which the current law may be able to accommodate but for which the parties will not be able to foresee with certainty. We expect that such legal risk would inhibit effective public sector uptake of AI.
There have been developments since the book was written. Key regulators in the UK have set out their strategic updates on how they approach AI, the EU AI Act has been enacted (see here) the Council of Europe’s Framework Convention on AI has been signed (here), and development of the UK’s proposed AI regulation is anticipated to progress. We can expect that AI regulation and policy will continue to evolve quickly, as do the technology and use cases.
The chapter aims to provide practical, evidence-based guidance for practitioners covering: a brief overview of the technology, identifying issues and themes relevant to public sector use of AI; the use of AI in the public sector; the current legal and regulatory framework applicable to public sector procurement, development and deployment of AI; and potential legal challenges. It is available on Westlaw or in hard copy.
If you would like to discuss how current or future regulations impact what you do with AI, please contact Tom Whittaker, Brian Wong, David Varney, Lucy Pegler, Martin Cook or any other member in our Technology team.
For the latest on AI law and regulation, see our blog and sign-up to our AI newsletter.
This article was written by Tom Whittaker. The other authors to the chapter contributed to the consultation response referred to above on which this article is based, but not the content of this article.