AI in the street: scoping everyday observatories for public engagement with connected and automated urban environments

A collage of cars, smoke, a bird, a policeman, a person lying down, and buildings, with blue marker connecting different elements of the photo. The phrases 'Their actions and existence has impact', 'They can physically interact' and 'They have power over people' are written on top of the image.
Diagramming the ShotSpotter “acoustic sensor” system in Chicago, by Yasmine Boudiaf, Dominique Barron, and AI in the street (March 2024)
  • Led by Professor Noortje Marres, University of Warwick

This project will explore divergences between principles of responsible AI and the messy reality of AI as encountered in the street, in the form of automated vehicles and surveillance infrastructure. The aim is to ground understandings of AI in lived experiences.

Over the last decade, the street has emerged as one of the primary sites where everyday publics encounter AI. Industry and public sector organisations have deployed a variety of AI-based technologies in UK streets, from autonomous vehicles (AVs) to navigation apps, data-driven modelling in smart city projects and facial recognition technologies (FRT). These deployments have been accompanied by significant policy initiatives defining societal benefits of AI-driven innovation (safety, levelling up, sustainability, inclusion) as well as institutional engagements with affected communities through policy exhibitions, user-centred workshops and citizen cafés. However, from the perspective of the street, AI innovation often manifests as a messy social reality, provoking frictions that exceed existing frameworks for responsible innovation: in Cambridge, firefighters battling a fire had to move a delivery robot that was in their way, while in Australia suburbs were left without electricity after a food delivery drone made an emergency landing on top of a set of powerlines. There remain, then, significant divergences between the general frameworks for responsible AI and the particular lived realities of AI in the street. To build capacity among everyday publics and AI innovation consortia to engage across such divides, this 6-month project will develop a situated, creative approach to public engagement with AI: street-level observatories of everyday AI.

To bridge divides between lay and expert understandings of AI innovation, we will evaluate and prototype a set of street-level observatories for everyday AI. The aim of these observatories is to explore how everyday publics perceive and engage with AI at a primary site ‘city streets’ where specific transformations, benefits, harms and (ir)responsibilities of AI in society can be made visible and thus legible for both publics and stakeholders. To realise this, we will collaborate with local partners and the arts to trial creative interventions that invite people on the street to observe the effects of AI in the lived environment. Our scoping project will 1) build partnerships across the humanities, arts and social sciences and with organisations and groups committed to situated forms of public engagement with AI-based science and innovation in connected and automated cities. In partnership with local government, we will 2) trial street-level AI observatories in 4 diverse UK cities Cambridge, Coventry, London and Edinburgh and one international location, Logan (Australia). The observatories will combine digital, place-based and/or embodied approaches, such as data walks and sensor media (apps) and will be designed to support shared learning across the project teams and partners.

Trialling AI observatories in city streets will enable us to undertake 3) a joint process of evaluating and prototyping an everyday AI observatory. This will make visible the entanglement of everyday social life with AI, showing people and technologies in complex real-world settings where sectoral, disciplinary and specialist interests intersect. This will be a space of interest to partners in local and national government, public policy innovation, and AI scientists and industry representatives, and create opportunities for developing shared understandings of societal responses and priorities between industry, policymakers, researchers and everyday publics.

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