Exploring Conversational Agents as an Effective Tool for Measuring Cognitive Biases in Decision-Making

Stephen Pilli
1/8/2024
cs.HCcs.AI

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Abstract

Heuristics and cognitive biases are an integral part of human decision-making. Automatically detecting a particular cognitive bias could enable intelligent tools to provide better decision-support. Detecting the presence of a cognitive bias currently requires a hand-crafted experiment and human interpretation. Our research aims to explore conversational agents as an effective tool to measure various cognitive biases in different domains. Our proposed conversational agent incorporates a bias measurement mechanism that is informed by the existing experimental designs and various experimental tasks identified in the literature. Our initial experiments to measure framing and loss-aversion biases indicate that the conversational agents can be effectively used to measure the biases.

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Cite this paper

@article{pilli2024exploring,
  title  = {Exploring Conversational Agents as an Effective Tool for Measuring Cognitive Biases in Decision-Making},
  author = {Stephen Pilli},
  year   = {2024},
  eprint = {2401.06686},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.06686v1}
}

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