From symbiosis to copilot, a wide range of metaphors have been employed to characterize cooperative and collaborative relationships between human and non-human agents (be they software, robots, algorithms, or automated agents of any kind) in support of designing such advanced technologies. Recently, the emergence and rapid commoditization of artificial intelligence (AI) and machine learning (ML) algorithms have driven a highly bimodal debate on what metaphor is best to account for AI’s and ML’s new capabilities, particularly when those closely mimic humans’: Is AI a tool or a teammate for humans using the technology? This debate, however, occludes critical elements necessary to practitioners in the fields of human system design. To move past the “tool vs. teammate debate,” we propose an orthogonal metaphor, that of a sidekick, inspired by popular and literary culture, which can both accomplish and facilitate work (i.e., they do, and they help do). The sidekick metaphor was applied to a variety of efforts where it yielded novel design considerations which would have otherwise been unattainable by previous approaches. In this contribution, we report on the debate, describe the sidekick metaphor, and exemplify its application to real-world use cases, in domains such as intelligence analysis, aircraft maintenance, and missile defense.
Three versions of a prototype ground controller interface were tested for their effect on aircraft departure sequencing in a simulation of Dallas/Forth-Worth International Airport. Two versions featured automated decision aids and a third served as a baseline with no decision aid. The two decision aids performed fundamentally different functions, with a Temporal Constraint Visualization (TCV) providing a visualization of spatiotemporal constraints on the departure sequence and a Timeline display providing release sequences derived by an optimization algorithm. Results indicate that participants in the TCV condition had more efficient departure sequences than the Baseline and Timeline conditions. No significant differences were found between conditions for timeliness of departures or handling of arrival aircraft. These results indicate that, through the use of appropriate decision aids, task performance in complex dynamic environments can be improved with humans retaining full decision making control. Additional research is warranted to investigate situation awareness and failure mode performance using these decision aid types.
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