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BEGIN:VEVENT
DTSTAMP:20251016T135138Z
LOCATION:Riverside East
DTSTART;TZID=America/Chicago:20251014T173000
DTEND;TZID=America/Chicago:20251014T183000
UID:HFESAM_ASPIRE 2025_sess131_POST215@linklings.com
SUMMARY:Explaining Trust Contagion in Human-Human-AI Teams: Convergence fr
 om Grounded Theory and Structural Topic Modeling
DESCRIPTION:Trevor Patten, Stephanie Kim, Emanuel Rojas, and Mengyao Li (G
 eorgia Institute of Technology)\n\nTrust contagion is the effect that huma
 ns have on each other’s trust attitude which can play a role in determinin
 g how human teams interact with AI teammates. While the effect of trust co
 ntagion is known, the potential mechanism for trust contagion in human/AI 
 teams is unclear. We outlined how trust contagion spreads within human tea
 ms by manipulating the level of trust a confederate placed in an AI teamma
 te and evaluating the dialogue between participants and the confederate. W
 e combined both qualitative (Grounded Theory) and computational (Structura
 l Topic Modeling) methods to identify team dynamics where high-trust confe
 derate teams displayed efficient communication compared to low and neutral
 -trust confederate teams. These findings describe the behaviors associated
  with adopting a team member's trust attitude and demonstrate how a combin
 ation of qualitative and computational methods may be appropriate for unde
 rstanding complex dynamics from converging methods.\n\n
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