关于ai生成目标建议的警示故事

Falk Lieder, Pin-Zhen Chen, Jugoslav Stojcheski, Saksham Consul, Viktoria Pammer-Schindler
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引用次数: 1

摘要

设定正确的目标并确定优先级可能是人们为自己、团队和组织做出的最关键、最具挑战性的决定。在本文中,我们探讨了是否有可能利用人工智能(AI)来帮助人们设定更好的目标,以及这些应用程序可能会产生哪些潜在问题。我们设计了人工智能驱动的数字目标设定助手的第一个原型,以及用于评估人工智能生成的目标建议质量的严格经验范式。我们的经验范式将人工智能生成的目标建议与随机生成的目标建议和无辅助目标设置进行比较,在大规模重复测量的在线实验中,对重要目标特征、动机和可用性进行一系列自我报告测量。一项有259名参与者参与的在线实验结果显示,我们直觉上令人信服的目标建议算法对人们的目标质量和追求目标的动机是有害的。这些令人惊讶的发现突出了未来利用人工智能帮助人们设定更好目标的工作需要解决的三个关键问题:1)将人工智能算法的目标函数与设计目标保持一致;2)帮助人们量化不同目标对他们的价值;3)保留用户的自主权。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Cautionary Tale About AI-Generated Goal Suggestions
Setting the right goals and prioritizing them might be the most crucial and the most challenging type of decisions people make for themselves, their teams, and their organizations. In this article, we explore whether it might be possible to leverage artificial intelligence (AI) to help people set better goals and which potential problems might arise from such applications. We devised the first prototype of an AI-powered digital goal-setting assistant and a rigorous empirical paradigm for assessing the quality of AI-generated goal suggestions. Our empirical paradigm compares the AI-generated goal suggestions against randomly-generated goal suggestions and unassisted goal-setting on a battery of self-report measures of important goal characteristics, motivation, and usability in a large-scale repeated-measures online experiment. The results of an online experiment with 259 participants revealed that our intuitively compelling goal suggestion algorithm was actively harmful to the quality of the people’s goals and their motivation to pursue them. These surprising findings highlight three crucial problems to be tackled by future work on leveraging AI to help people set better goals: i) aligning the objective function of the AI algorithms with the design goals, ii) helping people quantify how valuable different goals are to them, and iii) preserving the user’s sense of autonomy.
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