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Human-AI Teaming: State-of-the-Art and Research Needs (2022)

Chapter: Appendix B: Human-AI Teaming Workshop Agenda

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Suggested Citation:"Appendix B: Human-AI Teaming Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2022. Human-AI Teaming: State-of-the-Art and Research Needs. Washington, DC: The National Academies Press. doi: 10.17226/26355.
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Appendix B

Human-AI Teaming Workshop Agenda

July 28-29, 2021

MEETING OBJECTIVES

  • Identify key human-systems integration design considerations, methods, approaches, and associated research aimed at warfighter systems that incorporate human-AI teaming
  • Identify gaps in knowledge on effective human-machine teaming necessary to achieve future Air Force mission capability
  • Identify promising human-systems integration and human factors research opportunities that would accelerate mission capability development.

WEDNESDAY, JULY 28, 2021

10:00 a.m. Welcome and Introductions
  • Mica Endsley, Chair
10:15 a.m. AI in Future DOD Operations
Facilitated by Nancy Cooke (committee member)
  • Mark Draper, Human-AI Interaction in Future Joint All Domain Operations: Some Challenges and Opportunities, Air Force Research Laboratory
  • Robin Murphy, Role of Autonomy in DOD and HADR, Texas A&M University
  • Greg Zacharias, Human-Autonomy Test and Evaluation, DOD-OSD
12:00 p.m. Break
12:45 p.m. AI Status and Challenges
Facilitated by Missy Cummings (committee member)
  • Matt Turek, XAI Program, DARPA
  • Joanna Bryson, AI Ethics and Human Cooperation, Hertie School
Page 120 Cite
Suggested Citation:"Appendix B: Human-AI Teaming Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2022. Human-AI Teaming: State-of-the-Art and Research Needs. Washington, DC: The National Academies Press. doi: 10.17226/26355.
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2:00 p.m. Break
2:30 p.m. Human-AI Teaming Approaches
Facilitated by Bill Rouse (committee member)
  • Ben Shneiderman, Human-Centered AI, University of Maryland
  • Jay Shively, Human Autonomy Teaming, NASA Ames
  • Matthew Johnson, Intelligent Teaming, Florida Institute for Human and Machine Cognition
4:45 p.m. Adjourn

THURSDAY, JULY 29, 2021

10:00 a.m. Welcome and First Day wrap up
  • Mica Endsley, Chair
10:15 a.m. Human-AI Team Design and Processes
Facilitated by Emilie Roth (committee member)
  • Jamie Gorman, Modeling Human-Autonomy Team Coordination Using Layered Dynamics, Georgia Tech University
  • Brian Sandberg, ASIST Program, DARPA
  • Thomas O’Neill, Future Directions in Human-Autonomy Teams Research, University of Calgary
12:15 p.m. Break
12:30 p.m. Bias and Trust
Facilitated by John Lee (committee member)
  • Chris Wickens, Black Swans, Complacency and Automation Bias
  • Peter Hancock, Trust in AI Meta-Analysis, University of Central Florida
  • Joe Lyons, Trust Research in AFRL, Air Force Research Laboratory
2:00 p.m. Break
2:30 p.m. Transparency and Explainability
Facilitated by Chris Miller (committee member)
  • Shane Mueller, XAI, Michigan Technology University
  • Jessie Chen, Transparent Communications for Effective Human-Autonomy Teaming, Army Research Laboratory
  • Tim Miller, Transparency and Explainability, University of Melbourne
4:30 p.m. Conclusions/Discussion
5:00 p.m. Adjourn
Page 119 Cite
Suggested Citation:"Appendix B: Human-AI Teaming Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2022. Human-AI Teaming: State-of-the-Art and Research Needs. Washington, DC: The National Academies Press. doi: 10.17226/26355.
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Page 120 Cite
Suggested Citation:"Appendix B: Human-AI Teaming Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2022. Human-AI Teaming: State-of-the-Art and Research Needs. Washington, DC: The National Academies Press. doi: 10.17226/26355.
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Although artificial intelligence (AI) has many potential benefits, it has also been shown to suffer from a number of challenges for successful performance in complex real-world environments such as military operations, including brittleness, perceptual limitations, hidden biases, and lack of a model of causation important for understanding and predicting future events. These limitations mean that AI will remain inadequate for operating on its own in many complex and novel situations for the foreseeable future, and that AI will need to be carefully managed by humans to achieve their desired utility.

Human-AI Teaming: State-of-the-Art and Research Needs examines the factors that are relevant to the design and implementation of AI systems with respect to human operations. This report provides an overview of the state of research on human-AI teaming to determine gaps and future research priorities and explores critical human-systems integration issues for achieving optimal performance.

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