Perceptions of Intelligence in Urban AI and the Contingent Logics of Real Estate Estimate Algorithms

This chapter reconsiders the way scholars locate ‘intelligence’ in particular objects within the urban environment, from various forms of robotics to integrated urban sensing networks and purportedly autonomous algorithms. Scholars tend to highlight and interrogate the specific capacities and functions of a given object or system, often explicitly or implicitly equating these capacities with ‘intelligence,’ thus allowing for categorizations of different kinds of digital agents based on their distinct dis/embodiments and/or autonomy. This chapter contrasts this approach through a relational theory in which intelligence is not located in a given subject or object but is rather an emergent property of their interactions in particular contexts. This chapter thus engages the recent social science literature on AI in relation to the broader philosophy on intelligence to ask not only what autonomy means in the context of AI but how intelligence is a contingent concept made real through perceptions and encounters. We apply this theoretical take to the operations of real estate estimate algorithms and iBuyer programs and ask how perceptions of intelligence emerge through situated encounters and come to influence the ways differentially situated individuals interact with and make use of purported AI systems.