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A Cautionary Tale About AI-Generated Goal Suggestions

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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.


Lieder, Falk; Chen, Pin-Zhen; Consul, Saksham; Stojcheski, Jugoslav; Pammer-Schindler, Viktoria (2022): A Cautionary Tale About AI-Generated Goal Suggestions. Mensch und Computer 2022 - Tagungsband. DOI: 10.1145/3543758.3547539. New York: ACM. pp. 344-349. MCI-POSTER. Darmstadt. 4.-7. September 2022