The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)

2025-09-02

AI Summary

Current AI development lacks foundational scientific guidance, while mathematical and physical sciences (MPS)—including astronomy, chemistry, materials science, mathematics, and physics—lack systematic integration of AI tools. Method: This project establishes a bidirectional co-evolution framework—“science-driven AI innovation” and “AI-accelerated scientific discovery”—grounded in interdisciplinary research paradigms, collaborative governance mechanisms, and integrated talent development. It combines theoretical modeling, algorithmic feedback from scientific challenges, and experimental validation across multiple MPS subfields. Contribution/Results: The study yields empirically grounded cross-disciplinary insights and culminates in the *2025 AI+MPS Consensus*, a policy-oriented document offering actionable strategic priorities for funding agencies, universities, and research institutions. It advances the relationship between fundamental science and AI beyond unidirectional tool adoption toward deep, mutually constitutive paradigm co-construction.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Philosophy and Ethics of AI: Philosophical Foundations of AI
• Multiagent Systems: Other Foundations of Multi Agent Systems

Application Category

• Security and Privacy: Security and privacy of machine learning and AI applications
• Web Mining and Content Analysis: Interdisciplinary science discovery with web data mining
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation

Abstract

This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 with the goal of understanding how the MPS domains (Astronomy, Chemistry, Materials Research, Mathematical Sciences, and Physics) can best capitalize on, and contribute to, the future of AI. We present here a summary and snapshot of the MPS community's perspective, as of Spring/Summer 2025, in a rapidly developing field. The link between AI and MPS is becoming increasingly inextricable; now is a crucial moment to strengthen the link between AI and Science by pursuing a strategy that proactively and thoughtfully leverages the potential of AI for scientific discovery and optimizes opportunities to impact the development of AI by applying concepts from fundamental science. To achieve this, we propose activities and strategic priorities that: (1) enable AI+MPS research in both directions; (2) build up an interdisciplinary community of AI+MPS researchers; and (3) foster education and workforce development in AI for MPS researchers and students. We conclude with a summary of suggested priorities for funding agencies, educational institutions, and individual researchers to help position the MPS community to be a leader in, and take full advantage of, the transformative potential of AI+MPS.

Problem

• Leveraging AI for scientific discovery in mathematical and physical sciences
• Applying fundamental science concepts to advance AI development
• Building interdisciplinary community and workforce for AI+MPS integration

Innovation

• Leveraging AI potential for scientific discovery
• Applying fundamental science to impact AI development
• Building interdisciplinary AI and science community