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BEGIN:VEVENT
DTSTAMP:20260406T000710Z
DTSTART;VALUE=DATE-TIME:20241024T143000
DTEND;VALUE=DATE-TIME:20241024T154500
SUMMARY:DR@W Forum Talk: Kamil Fulawka (MPI\, Berlin)
TZID:Europe/London
UID:20241024-8ac672c792b40ad40192be29a5674f72@warwick.ac.uk
CREATED:20241024T105537Z
DESCRIPTION:The Anatomy of Risky Choice: Uncovering Subjective Choice Rea
 sons with Large Language Models Abstract: I will present a novel approac
 h to understanding the subjective reasons underlying risky decision-maki
 ng\, enabled by large language models (LLM). Traditional models of risky
  choice often assume that decision-making relies on a single\, stable re
 ason or process\, regardless of context. This simplification overlooks t
 he variability in reasoning that may occur depending on the situation. T
 o address these limitations\, we developed an LLM-based approach that ut
 ilizes free-text reports to reveal the subjective reasons behind decisio
 ns\, and we implemented a proof-of-concept in three stages. First\, we e
 xtracted a comprehensive set of nearly 50 decision reasons from formal m
 odels\, heuristics\, and basic motivations. Second\, we collected free-t
 ext retrospective verbal reports from 86 participants after each of 20 r
 isky choices they made. Third\, we employed advanced prompt engineering 
 techniques with a state-of-the-art LLM to identify the reasons mentioned
  in these reports. Our results provide strong evidence that decision rea
 sons vary systematically across different choice problems but less acros
 s individuals. Furthermore\, a simple predictive model based on the iden
 tified reasons achieves an out-of-sample accuracy of about 92%\, validat
 ing the approach. Our results suggest that combining verbal reports and 
 an LLM-based analysis with a large sample and comprehensive set of choic
 e problems can uncover how people make risky decisions\, including intri
 cate relationships between decision reasons and types of choice problems
 .
LOCATION:WBS 0.006
CATEGORIES:Economics,Warwick Business School,wbs,Behavioural Science GRP,
 Statistics Department,Psychology Department,Behaviour Spotlight,DR@W For
 um
LAST-MODIFIED:20241024T105537Z
ORGANIZER;CN=John Taylor:
END:VEVENT
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