Mitigating knowledge imbalance in AI-advised decision-making through collaborative user involvement
Mitigating knowledge imbalance in AI-advised decision-making through collaborative user involvement
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DOI：
10.1016/j.ijhcs.2022.102977
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发表时间：
2022-12-23
影响因子：
5.4
通讯作者：
Huang, Chien-Ming
中科院分区：
文献类型：
--
作者：
Gomez, Catalina;Unberath, Mathias;Huang, Chien-Ming
将人工智能(AI)系统集成到决策任务中，试图通过增强或补充人们的能力来帮助他们，并最终提高任务绩效。然而，在考虑来自现代黑匣子智能系统的推荐时，用户面临着接受还是推翻人工智能的建议的决定。当用户和人工智能系统之间存在严重的知识不平衡时，即当人们缺乏必要的任务知识，因此无法准确地独立完成任务时，做出这些决定甚至更具挑战性。在这项工作中，我们旨在了解人们在面对知识不平衡的挑战时在人工智能辅助决策任务中的行为，并探索让用户参与人工智能的预测生成过程是否会使他们更愿意遵循人工智能的建议，并增强他们对协作的感知。我们的实证研究表明，在一个显著的知识不平衡的任务中，用户参与生成人工智能推荐会使他们更愿意同意人工智能的建议，并更积极地感知人工智能代理和他们的合作是一个团队。
Integrating artificial intelligence (AI) systems into decision-making tasks attempts to assist people by augment -ing or complementing their abilities and ultimately improve task performance. However, when considering recommendations from modern "black box"intelligent systems, users are confronted with the decision of accepting or overriding AI's recommendations. These decisions are even more challenging to make when there exists a significant knowledge imbalance between the users and the AI system-namely, when people lack necessary task knowledge and are therefore unable to accurately complete the task on their own. In this work, we aim to understand people's behavior in AI-assisted decision-making tasks when faced with the challenge of knowledge imbalance and explore whether involving users in an AI's prediction generation process makes them more willing to follow the AI's recommendations and enhances their perception of collaboration. Our empirical study reveals that the involvement of users in generating AI recommendations during a task with notable knowledge imbalance causes them to be more willing to agree with the AI's suggestions and to perceive the AI agent and their collaboration as a team more positively.