Human team members show a remarkable ability to infer the state of their partners and anticipate their needs and actions. Prior research demonstrates that an artificial system can make some predictions accurately concerning artificial agents. This study investigated whether an artificial system could generate a robust Theory of Mind of human teammates. An urban search and rescue (USAR) task environment was developed to elicit human teamwork and evaluate inference and prediction about team members by software agents and humans. The task varied team members’ roles and skills, types of task synchronization and interdependence, task risk and reward, completeness of mission planning, and information asymmetry. The task was implemented in MinecraftTM and applied in a study of 64 teams, each with three remotely distributed members. An evaluation of six Artificial Social Intelligences (ASI) and several human observers addressed the accuracy with which each predicted team performance, inferred experimentally manipulated knowledge of team members, and predicted member actions. All agents performed above chance; humans slightly outperformed ASI agents on some tasks and significantly outperformed ASI agents on others; no one ASI agent reliably outperformed the others; and the accuracy of ASI agents and human observers improved rapidly though modestly during the brief trials.

There is much at stake with the smart city. This urban governance movement is

predicated on infusing information-and-communication technology into nearly all aspects of the built environment, while at the same time transforming how cities are planned and managed. The smart city movement is global in scale with initiatives being rolled out all over the planet, driven by proponents with deep pockets of wealth and influence, and a lucrative opportunity with market projections in the billions or trillions of dollars (over the next five to ten years). However, the smart city label can be nebulous and amorphous, seemingly subsuming unrelated technologies, practices, and policies as necessary. Yet, even with this ambiguity, or perhaps because of it, the smart city vision is still able to colonize urban landscapes and capture the political imaginations of decision makers. In order to know just what the smart city entails I work to bring analytic clarity to the actions, visions, and values of this movement.

In short, the arc of this project moves from diving into the "smart city" discourses; to picking apart the ideologies at its heart; to engaging with the dual logics—control and accumulation—that drive the smart city; and finally to imagining what an alternative techno- politics might look like and how we might achieve it. My goal is that by analyzing the techno- politics of the smart city we will be better equipped to understand these urban transformations— what logics drive them, what they herald, and what our role should be in how they develop.