CAIUS: Consequences of AI-Based Decision Making for Urban Societies

The deployment of AI in decision-making processes has the potential to allocate resources efficiently and evaluate situations objectively. Drawing upon these advantages, municipalities employ sensors, cameras, and other AI-related technologies and applications to enhance their smart city infrastructures. However, apart from the desired improvements, such technologies may also have unintended consequences for urban societies: by exacerbating existing social inequalities or creating new ones, social solidarity of the urban society can be eroded. CAIUS aims to unveil such unintended consequences on a theoretical, empirical, and applied level: drawing upon real-world applications in the smart city context (resource allocation and service pricing), we investigate the impact of AI-based decision-making on individual citizen behaviour and human society at large. To this end and to advance theory on the digitization of society, we conduct social simulations modelling AI-based decision-making, citizen behaviour, and attitudes. The parameters for these simulations are empirically acquired through surveys and experiments. The gained insights are applied in two real-world use cases with local partners: (1) the choice of spots to install smart cameras for traffic law enforcement and (2) dynamic pricing of parking places. Ultimately, going beyond these specific use cases, we infer a general framework for the evaluation of AI applications in urban contexts.