AI to help engage communities through Greater Cambridge Shared Planning partnership with the University of Liverpool

This is a joint release on behalf of Cambridge City Council, South Cambridgeshire District Council and the Greater Cambridge Shared Planning Service.

Greater Cambridge shared planning logo

Greater Cambridge Shared Planning, a shared service between South Cambridgeshire District and Cambridge City councils, is pioneering the development of a new AI tool to improve how public feedback on planning policies is reviewed and analysed.

Funded through the Government’s PropTech Innovation Fund, this project aims to use AI to transform the way communities engage in the planning system.

Developed in partnership with the University of Liverpool, the AI tool - known as a Large Language Model (LLM) - is being specifically designed to process and summarise the thousands of comments that residents, community groups and other stakeholders submit during consultations on the Local Plan and other planning documents.

Cllr Dr. Tumi Hawkins Lead Cabinet Member for Planning for South Cambridgeshire District Council, said: “With Greater Cambridge Shared Planning being one of the first local authorities in the UK to develop its own bespoke LLM, the aim is to provide more reliable and meaningful insights into what people in the area think about proposed developments and planning policies.”

She added: “In the last two consultations on the emerging Greater Cambridge Local Plan, around 19,000 comments were submitted by residents, community associations, parish councils, developers, and other stakeholders. Reviewing such a large number of responses takes a considerable amount of time, especially where responses include technical documents. It also means it takes a long time for people to see how the councils have responded to their comments as the Local Plan progresses through the various plan making stages.”

The AI tool has the potential to significantly improve this by offering a faster, more efficient way to summarise comments without compromising on quality.

While the University of Liverpool is the primary partner developing the AI, additional input from Anglia Ruskin University and the University of Cambridge, funded by the AI@Cam initiative, will enrich the project with valuable insights and expertise in AI technology and ethical considerations. This collaboration will help to ensure that the AI is developed responsibly, prioritising transparency and inclusivity in its implementation.

Cllr Katie Thornburrow, Executive Councillor for Planning, Building Control and Infrastructure at Cambridge City Council, said: “Ultimately, the new tool will help us make more informed and more efficient decisions, whilst ensuring that the views of local communities continue to play a key role in helping to shape the new Local Plan and other planning documents. This initiative is a step forward in using modern technology to create a more inclusive planning system that listens to and serves the needs of the community.”

Professor Alexander Lord, Lever Chair at the University of Liverpool said: “We are excited to be working with Greater Cambridge Shared Planning on this project to bring AI into the planning process.  Few aspects of public policy arouse such strong feelings in local communities as planning and so it will be very important for us to develop technologies that we can all be confident represent citizens’ views accurately. Our goal with this project is to create a tool that allows the planning service to lead the way in harnessing AI to enhance the public’s engagement with the planning system.”

While the tool is being developed, there will be safeguards in place, including manual checking of responses to avoid any AI hallucinations - where the AI might generate incorrect or made-up information - or misrepresentations.

It's important to note that AI will not replace humans in reading and interpreting feedback. The tool is designed to assist the Greater Cambridge Shared Planning team, with people still playing a key role in ensuring accuracy and quality throughout the process.



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