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.

翻译：启发式与认知偏差是人类决策过程中的重要组成部分。自动检测特定认知偏差可使智能工具提供更好的决策支持。目前检测认知偏差的存在需要手工设计的实验和人工解读。本研究旨在探索将对话代理作为衡量不同领域多种认知偏差的有效工具。我们提出的对话代理整合了基于现有实验设计和文献中各种实验任务的偏差测量机制。初步测量框架效应与损失厌恶偏差的实验表明，对话代理可有效用于衡量这些偏差。