• Media type: E-Article
  • Title: The National Academies Board on Human System Integration (BOHSI) Panel: Explainable AI, System Transparency, and Human Machine Teaming
  • Contributor: Warden, Toby; Carayon, Pascale; Roth, Emilie M.; Chen, Jessie; Clancey, William J.; Hoffman, Robert; Steinberg, Marc L.
  • imprint: SAGE Publications, 2019
  • Published in: Proceedings of the Human Factors and Ergonomics Society Annual Meeting
  • Language: English
  • DOI: 10.1177/1071181319631100
  • ISSN: 2169-5067; 1071-1813
  • Keywords: General Medicine
  • Origination:
  • Footnote:
  • Description: <jats:p> The National Academies Board on Human Systems Integration (BOHSI) has organized this session exploring the state of the art and research and design frontiers for intelligent systems that support effective human machine teaming. An important element in the success of human machine teaming is the ability of the person on the scene to develop appropriate trust in the automated software (including recognizing when it should not be trusted). Research is being conducted in the Human Factors community and the Artificial Intelligence (AI) community on the characteristics that software need to display in order to foster appropriate trust. For example, there is a DARPA program on Explainable AI (XAI). The Panel brings together prominent researchers from both the Human Factors and AI communities to discuss the current state of the art, challenges and short-falls and ways forward in developing systems that engender appropriate trust. </jats:p>