Kish Bar-On, Kati and Friedman, Michael (2026) Rethinking Mathematical Intuition in the Age of AI. [Preprint]
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Abstract
The integration of artificial intelligence (AI) into mathematical practice raises profound questions about the nature of mathematical intuition in discovery and research. This paper examines the epistemological shifts induced by AI-based programs and tools, and explores how they challenge traditional notions of intuition. Building on three case studies, we argue that AI-based systems do not abolish intuition but relocate it, shifting it from a primarily anticipatory capacity to one that can also operate retroactively as interpretation, reconstruction, critique, and integration. Drawing on the historical flexibility of the concept, we propose a working definition of mathematical intuition as a family of practice-embedded capacities for orienting, evaluating, and rendering intelligible mathematical moves and outcomes across hybrid human–machine collaborations. Ultimately, we argue that AI-based programs, even when their capacities are more limited than some narratives suggest, are not merely new computational aids but a transformative epistemic force that reconfigures what it means to “do mathematics” in the 21st century.
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| Item Type: | Preprint | |||||||||
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| Keywords: | Mathematical Intuition; AI in Mathematics; Mathematical Practice; Human-Machine Collaboration; Mathematical Reasoning | |||||||||
| Subjects: | Specific Sciences > Mathematics > History of Philosophy Specific Sciences > Artificial Intelligence Specific Sciences > Artificial Intelligence > Machine Learning Specific Sciences > Mathematics |
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| Depositing User: | Dr. Kati Kish Bar-On | |||||||||
| Date Deposited: | 26 Mar 2026 22:58 | |||||||||
| Last Modified: | 26 Mar 2026 22:58 | |||||||||
| Item ID: | 28776 | |||||||||
| Subjects: | Specific Sciences > Mathematics > History of Philosophy Specific Sciences > Artificial Intelligence Specific Sciences > Artificial Intelligence > Machine Learning Specific Sciences > Mathematics |
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| Date: | 10 February 2026 | |||||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/28776 |
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