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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 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.

ContributorsFreeman, Jared T. (Author) / Huang, Lixiao (Author) / Woods, Matt (Author) / Cauffman, Stephen J. (Author)
Created2021-11-04
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Description

The Future of Wastewater Sensing workshop is part of a collaboration between Arizona State University Center for Nanotechnology in Society in the School for the Future of Innovation in Society, the Biodesign Institute’s Center for Environmental Security, LC Nano, and the Nano-enabled Water Treatment (NEWT) Systems NSF Engineering Research Center.

The Future of Wastewater Sensing workshop is part of a collaboration between Arizona State University Center for Nanotechnology in Society in the School for the Future of Innovation in Society, the Biodesign Institute’s Center for Environmental Security, LC Nano, and the Nano-enabled Water Treatment (NEWT) Systems NSF Engineering Research Center. The Future of Wastewater Sensing workshop explores how technologies for studying, monitoring, and mining wastewater and sewage sludge might develop in the future, and what consequences may ensue for public health, law enforcement, private industry, regulations and society at large. The workshop pays particular attention to how wastewater sensing (and accompanying research, technologies, and applications) can be innovated, regulated, and used to maximize societal benefit and minimize the risk of adverse outcomes, when addressing critical social and environmental challenges.

ContributorsWithycombe Keeler, Lauren (Researcher) / Halden, Rolf (Researcher) / Selin, Cynthia (Researcher) / Center for Nanotechnology in Society (Contributor)
Created2015-11-01
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Description

Students in Organic Chemistry for Majors were required to write a paper as the culminating course assignment. Prior to completing this assignment, students could attend a library instruction session covering relevant databases and resources. Upon submission of their papers, bibliographies from 53 students were collected. Calculations were made to attempt

Students in Organic Chemistry for Majors were required to write a paper as the culminating course assignment. Prior to completing this assignment, students could attend a library instruction session covering relevant databases and resources. Upon submission of their papers, bibliographies from 53 students were collected. Calculations were made to attempt a holistic account of costs associated with completing the assignment. Factors such as the cost of journals, databases, and librarian time were all included in the overall cost estimate, totalling $7,189.22 for this single assignment.

ContributorsKromer, John (Author)
Created2019-07-02