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VERSION:2.0
PRODID:Linklings LLC
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TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
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TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
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TZOFFSETFROM:-0500
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TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
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BEGIN:VEVENT
DTSTAMP:20251016T135137Z
LOCATION:Grand B
DTSTART;TZID=America/Chicago:20251015T152000
DTEND;TZID=America/Chicago:20251015T154000
UID:HFESAM_ASPIRE 2025_sess210_LECT304@linklings.com
SUMMARY:Error Type Influences Communication Recipient Selection: Consisten
 t Patterns During Autonomy and Automation Errors in a Synthetic Task Envir
 onment
DESCRIPTION:Ray Hao, Jamie Gorman, Robert Gutzwiller, and Nancy Cooke (Ari
 zona State University)\n\nEffective communication in human-autonomy teams 
 is crucial for optimizing error management during autonomy or automation f
 ailures. This study explores how error type (autonomy vs. automation failu
 res) determines how human team members communicate the error and examines 
 whether training interventions (control, trust calibration, or coordinatio
 n training) influence these behaviors in text-based communication channels
 . Previously collected data from an experiment conducted in a synthetic ta
 sk environment designed for team reconnaissance tasks (CERTT-RPAS-STE; Coo
 ke & Shope, 2004) was analyzed using multilevel logistic regression. Resul
 ts indicated that human team members were less likely to communicate with 
 other human team members during autonomy failures (when the AI teammate ma
 lfunctions) compared to automation failures (when the operating system fai
 ls, such as display failures), regardless of training type. These findings
  help to understand the decision-making process of human teammates in mana
 ging errors during unexpected automation and autonomy failures.\n\nTrack: 
 Human AI Robot Teaming (AI)\n\nSession Chair: Maha Khalid (Rice University
 )\n\n
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