Presentation
From Parts to Whole: How Trust in AI and Humans Shapes System Trust
DescriptionRecently, an increasing number of studies on human-autonomy interaction (HAI) have started to expand their focus to investigating complex multi-agent HAI, involving multiple humans and/or agents within the interaction. The shift introduces new challenges. Organizational theory suggests that trust is multi-referent, meaning it is directed toward various targets. Within a human organization, trust typically has three possible referents: interpersonal, team, and organization. Applying to HAI, trust can be directed at three different referents: human teammates, agent teammates, and the team/system as a whole. However, no study has yet examined the relationships between trust in these different referents. This study addresses this gap by exploring trust in three referents: the AI planner, peers, and the system. The study is conducted in a scenario where multiple people in the system must evacuate as quickly as possible, with the ability to support each other by reporting roadblock information while receiving assistance from an AI planner that provides the shortest route. After the evacuation, participants evaluated their trust in the three referents, respectively. This study aims to understand the relationships between these three trust constructs, specifically examining whether trust in a higher-level entity can be explained and predicted by trust in lower-level entities.
Event Type
Lecture
TimeTuesday, October 14th4:30pm - 4:50pm CDT
LocationGrand B
Human AI Robot Teaming (AI)