Supporting AI-Augmented Meta-Decision Making with InDecision
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arXiv
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| Format: | Preprint |
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2025
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| author | Castañeda, Chance Mindel, Jessica Page, Will Stec, Hayden Yu, Manqing Holstein, Kenneth |
| author_facet | Castañeda, Chance Mindel, Jessica Page, Will Stec, Hayden Yu, Manqing Holstein, Kenneth |
| contents | From school admissions to hiring and investment decisions, the first step behind many high-stakes decision-making processes is "deciding how to decide." Formulating effective criteria to guide decision-making requires an iterative process of exploration, reflection, and discovery. Yet, this process remains under-supported in practice. In this short paper, we outline an opportunity space for AI-driven tools that augment human meta-decision making. We draw upon prior literature to propose a set of design goals for future AI tools aimed at supporting human meta-decision making. We then illustrate these ideas through InDecision, a mixed-initiative tool designed to support the iterative development of decision criteria. Based on initial findings from designing and piloting InDecision with users, we discuss future directions for AI-augmented meta-decision making. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_12433 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Supporting AI-Augmented Meta-Decision Making with InDecision Castañeda, Chance Mindel, Jessica Page, Will Stec, Hayden Yu, Manqing Holstein, Kenneth Human-Computer Interaction From school admissions to hiring and investment decisions, the first step behind many high-stakes decision-making processes is "deciding how to decide." Formulating effective criteria to guide decision-making requires an iterative process of exploration, reflection, and discovery. Yet, this process remains under-supported in practice. In this short paper, we outline an opportunity space for AI-driven tools that augment human meta-decision making. We draw upon prior literature to propose a set of design goals for future AI tools aimed at supporting human meta-decision making. We then illustrate these ideas through InDecision, a mixed-initiative tool designed to support the iterative development of decision criteria. Based on initial findings from designing and piloting InDecision with users, we discuss future directions for AI-augmented meta-decision making. |
| title | Supporting AI-Augmented Meta-Decision Making with InDecision |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2504.12433 |