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DTSTAMP:20251016T135129Z
LOCATION:Grand A
DTSTART;TZID=America/Chicago:20251015T141000
DTEND;TZID=America/Chicago:20251015T143000
UID:HFESAM_ASPIRE 2025_sess211_LECT376@linklings.com
SUMMARY:A Dynamic Trust and Distrust Influence Metric that Predicts Team T
 rustworthiness and Affective Trust in Human Teams and Human-AI Teams
DESCRIPTION:Matthew Scalia, Ray Hao, Shiwen Zhou, and Xiaoyun Yin (Arizona
  State University; Center for Human, Artificial Intelligence, and Robot Te
 aming); Wen Duan and Nan Weng (Clemson University); Jessica Tuttle and Chl
 oe Bell (University of Dayton Research Institute); Michael Tolston and Gre
 gory Funke (U.S. Air Force Research Laboratory); Guo Freeman and Nathan Mc
 Neese (Clemson University); and Jamie Gorman (Arizona State University; Ce
 nter for Human, Artificial Intelligence, and Robot Teaming)\n\nThe study i
 ntroduces influence as an information-theoretic measure of trust and distr
 ust spread based in dynamical systems theory to capture the spread of trus
 t and distrust in human-AI teams over time. It utilizes average mutual inf
 ormation to determine the degree to which joint team member actions influe
 nce system-level states over time. Forty-five three-member teams completed
  five 40-minute reconnaissance missions. Participants assumed the photogra
 pher role and worked with two confederate experimenters in navigator and p
 ilot roles who portrayed either human or AI teammates. Trust and distrust 
 were spread communicatively by the navigator as a between-subject conditio
 n and behaviorally by the pilot as a within-subject condition. Three influ
 ence time series measures for each teammate joint pair were calculated eac
 h mission and used in a series of repeated measures multiple regressions t
 o predict individual performance and self-reported trust after each missio
 n (i.e., team trustworthiness; cognitive trust and affective trust in each
  teammate). Team trustworthiness was predicted in the control condition an
 d affective trust in the pilot was predicted in the communicative trust sp
 reading condition. The results suggest that the influence measure is sensi
 tive to behavioral and communicative spreading in HATs.\n\nTrack: Aerospac
 e Systems, Human AI Robot Teaming (AI)\n\nSession Chairs: Briana Sobel (Em
 bry-Riddle Aeronautical University) and Xiaoyun Yin (Arizona State Univers
 ity; Center for Human, Artificial Intelligence, and Robot Teaming)\n\n
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