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- Creators: Barrett, The Honors College
- Resource Type: Text
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.
Passed in April of 2010, Arizona Senate Bill 1070 is nationally recognized as the first state-level anti-immigration legislation of its kind that deputized local police officers to enforce immigration laws. Though response strategies varied widely across activists and organizations, many community organizations devised strategies specifically aimed to protect and assist the undocumented community during the reign of terror that accompanied SB 1070. In looking at the reflections of activists and organization leaders on their own actions and decision-making rationale, I analyze how their strategies and tactics worked to both counter and reconceptualize hegemonic notions of citizenship, belonging, and community through the creation of networks and knowledge funds. By specifically examining the efforts made by No Mas Muerte, Puente Human Rights Movement, and the Calle Dieciseis Mural Project, I show that efforts that go beyond voter mobilization and legal action, which not only work to combat dominant rhetoric but also center the voices of the targeted population through disrupting public space, are essential to responding to political efforts designed to target vulnerable communities. Given their necessity, academics and institutional actors must acknowledge the importance of grassroots efforts in contributing to inter-institutional strategies and ensure that a ground-up analysis of community-based organizations informs their actions taken against state-level anti-immigration laws.