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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135210Z
LOCATION:Grand B
DTSTART;TZID=America/Chicago:20251014T163000
DTEND;TZID=America/Chicago:20251014T165000
UID:HFESAM_ASPIRE 2025_sess202_LECT557@linklings.com
SUMMARY:From Parts to Whole: How Trust in AI and Humans Shapes System Trus
 t
DESCRIPTION:Hyesun Chung and X. Jessie Yang (University of Michigan)\n\nRe
 cently, 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 s
 hift 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: interpe
 rsonal, 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 be
 tween 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 ot
 her by reporting roadblock information while receiving assistance from an 
 AI planner that provides the shortest route. After the evacuation, partici
 pants evaluated their trust in the three referents, respectively. This stu
 dy aims to understand the relationships between these three trust construc
 ts, specifically examining whether trust in a higher-level entity can be e
 xplained and predicted by trust in lower-level entities.\n\nTrack: Human A
 I Robot Teaming (AI)\n\nSession Chairs: Pawinee Pithayarungsarit (George M
 ason University) and Aakash Yadav (University of Wisconsin - Madison)\n\n
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