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

• URL: http://arxiv.org/abs/2401.06686v1
• Date: Mon, 8 Jan 2024 10:23:52 GMT
• Title: Exploring Conversational Agents as an Effective Tool for Measuring Cognitive Biases in Decision-Making
• Authors: Stephen Pilli
• Abstract summary: The research aims to explore conversational agents as an effective tool to measure various cognitive biases in different domains. Our initial experiments to measure framing and loss-aversion biases indicate that the conversational agents can be effectively used to measure the biases.
• Score: 0.65268245109828
• License: http://creativecommons.org/licenses/by/4.0/
• 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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