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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135142Z
LOCATION:Riverside East
DTSTART;TZID=America/Chicago:20251015T173000
DTEND;TZID=America/Chicago:20251015T183000
UID:HFESAM_ASPIRE 2025_sess138_POST345@linklings.com
SUMMARY:Shaping Choices: How AI Simplification and Framing Influence Decis
 ions
DESCRIPTION:Andrea Macedo Salas, Kelsey Jang, and Anne Collins McLaughlin 
 (North Carolina State University); Cuiziyi Rui (Duke Kunshan); and Sinuo T
 an (Wuhan University)\n\nThe emergence of Artificial Intelligence (AI) too
 ls offer new possibilities for simplifying complex information helping wit
 h decision-making. This study investigates how AI-simplified language and 
 framing effects influence decision-making in scenarios involving novel mil
 itary operations. Using a 2 (positive vs. negative framing) x 2 (jargon vs
 . AI-simplified language) between-subjects design, participants will be pr
 esented with one of two military scenarios—one involving a high-value targ
 et (HVT) and the other addressing improvised explosive device (IED) deacti
 vation. Outcome measures include perceived scenario desirability, complian
 ce, trust in AI, cognitive workload (NASA-TLX). Drawing from prior framing
  studies (e.g., Tversky & Kahneman, 1986; Levin et al., 1998), we hypothes
 ize that positively framed, AI-translated scenarios will result in higher 
 desirability ratings, increased compliance, and lower cognitive workload c
 ompared to negatively framed or jargon-heavy versions. The aim of this res
 earch is to inform the design of AI tools that support clear communication
  and user-centered decision-making aids. It highlights the importance of c
 onsidering human cognition and the possible use in the design of new techn
 ologies.\n\n
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