Exploring Conversational Agents as an Effective Tool for Measuring Cognitive Biases in Decision-Making
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916089301041152 |
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| author | Pilli, Stephen |
| author_facet | Pilli, Stephen |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2401_06686 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring Conversational Agents as an Effective Tool for Measuring Cognitive Biases in Decision-Making Pilli, Stephen Human-Computer Interaction Artificial Intelligence 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. |
| title | Exploring Conversational Agents as an Effective Tool for Measuring Cognitive Biases in Decision-Making |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2401.06686 |