Close

Presentation

37. Exploring the Taxonomy of Gaming Attributes and Feasibility of Human-AI Testbeds: An Evaluation of Empirical Studies
DescriptionThe Committee on Human-System Integration Research for the 711th Human Performance Wing of the Air Force Research Laboratory identified developing testbeds to support human-AI teaming as a crucial research objective. Their report delineated 57 research objectives into near-term (1-5 years), mid-term (6-10 years), and far-term (11-15 years) categories. While some objectives spanned one or two categories, only one research objective spanned all three categories: human-AI team testbeds. This poster explores human-autonomy teaming research along two dimensions: game attributes and feasibility. We use Bedwell et al.'s (2012) game attribute taxonomy that identifies nine categories of game states and features including action language, assessment, conflict/challenge, control, environment, game fiction, human interaction, immersion, and rules/goals. The examination of feasibility, based on Bowers et al. (1992), is evaluated on (1) accessibility of the testbed, (2) characteristics for team research (i.e., two or more subjects, interdependency, team constructs), and (3) experimental control of independent variables.
Event Type
Poster
TimeThursday, September 12th5:30pm - 6:30pm MST
LocationMcArthur Ballroom
Tracks
Aging
Augmented Cognition
Children's Issues
Communications
Cybersecurity
Education
Environmental Design
General Sessions
Human AI Robot Teaming (AI)
Macroergonomics
Occupational Ergonomics
Student Forum
Surface Transportation
Sustainability
System Development