TY - GEN
T1 - How the experts do it
T2 - 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018
AU - Dodge, Jonathan
AU - Penney, Sean
AU - Hilderbrand, Claudia
AU - Anderson, Andrew
AU - Burnett, Margaret
N1 - Publisher Copyright:
Copyright © 2017 ACM.
PY - 2018/4/20
Y1 - 2018/4/20
N2 - How should an AI-based explanation system explain an agent's complex behavior to ordinary end users who have no background in AI? Answering this question is an active research area, for if an AI-based explanation system could effectively explain intelligent agents' behavior, it could enable the end users to understand, assess, and appropriately trust (or distrust) the agents attempting to help them. To provide insights into this question, we turned to human expert explainers in the real-time strategy domain -"shoutcasters"- to understand (1) how they foraged in an evolving strategy game in real time, (2) how they assessed the players' behaviors, and (3) how they constructed pertinent and timely explanations out of their insights and delivered them to their audience. The results provided insights into shoutcasters' foraging strategies for gleaning information necessary to assess and explain the players; a characterization of the types of implicit questions shoutcasters answered; and implications for creating explanations by using the patterns and abstraction levels these human experts revealed.
AB - How should an AI-based explanation system explain an agent's complex behavior to ordinary end users who have no background in AI? Answering this question is an active research area, for if an AI-based explanation system could effectively explain intelligent agents' behavior, it could enable the end users to understand, assess, and appropriately trust (or distrust) the agents attempting to help them. To provide insights into this question, we turned to human expert explainers in the real-time strategy domain -"shoutcasters"- to understand (1) how they foraged in an evolving strategy game in real time, (2) how they assessed the players' behaviors, and (3) how they constructed pertinent and timely explanations out of their insights and delivered them to their audience. The results provided insights into shoutcasters' foraging strategies for gleaning information necessary to assess and explain the players; a characterization of the types of implicit questions shoutcasters answered; and implications for creating explanations by using the patterns and abstraction levels these human experts revealed.
UR - http://www.scopus.com/inward/record.url?scp=85044533575&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044533575&partnerID=8YFLogxK
U2 - 10.1145/3173574.3174136
DO - 10.1145/3173574.3174136
M3 - Conference contribution
AN - SCOPUS:85044533575
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 21 April 2018 through 26 April 2018
ER -