How local communities and publics make sense of AI
In this new report, we reflect on what lessons can be learnt for national, local and regional government from the AI in the Street pilot.
Dominique Barron, and Noortje Marres, Rachel Coldicutt, Alex Taylor, and Maya Indira Ganesh
One year on from our original pilot, this new report investigates how local communities and everyday publics make sense of the introduction of data-intensive and AI-based technologies to everyday environments. In this new report, we reflect on what lessons can be learnt for local and regional government AI initiatives in today’s AI policy context.
The AI in the Street project prototyped everyday observatories of AI and trialled these in four cities in the UK and one in Australia in the summer of 2024, in collaboration with local partners and artists. The observatories used creative methods to invite local participants to observe the effects of AI in the lived environment. The principal finding of our research is that urban communities and everyday publics in the street often do not perceive themselves as the beneficiaries of AI innovation in urban settings, and in particular of the uptake of AI in the delivery of public services.
Based on a discussion of the observatory results, we identify a set of mismatches between, on the one hand, institutional discourse on the societal benefits of AI innovation and, on the other hand, self-defined priorities of local communities. We identify three types of mismatch – relating to purpose, beneficiaries, and need – between government discourse on AI innovation and place-based perceptions of AI in the street, and suggest that there is a relative lack of communication and engagement designed for everyday publics in place, which risks further entrenching perceptions of exclusion and feelings of distrust towards government institutions.
We go on to discuss the current and future AI policy landscape in the UK, outlining the main current government AI policies and their intersection with initiatives in support of flourishing community and place-based innovation. We review the case of data centres as publicly visible AI infrastructures, with likely significant impact on local communities. Highlighting the disconnect between technology and innovation policy and social policy, we call attention to the significant risks of AI innovation policy becoming a driver of public distrust and outline a set of recommendations in support of demonstrating public value of AI in local and regional settings and the development of a best practice model of participatory approaches for engaging with communities regarding AI innovation impacts.
In conclusion, we recommend the UK government’s AI policy approach should expand to include a cross-departmental social and wellbeing strategy for AI that empowers local and regional governments to deliver in place. This should be supported by greater transparency on AI Growth Zones, the establishment of everyday AI Observatories across the UK to understand the public’s response to increased use of AI, and the establishment of everyday AI Observatories across the UK to adopt a transparent participatory approach to innovation policy and to understand the public’s views of AI.