[2603.24914] Shaping the Future of Mathematics in the Age of AI

[2603.24914] Shaping the Future of Mathematics in the Age of AI

arXiv - AI 3 min read

About this article

Abstract page for arXiv paper 2603.24914: Shaping the Future of Mathematics in the Age of AI

Mathematics > History and Overview arXiv:2603.24914 (math) [Submitted on 26 Mar 2026] Title:Shaping the Future of Mathematics in the Age of AI Authors:Johan Commelin, Mateja Jamnik, Rodrigo Ochigame, Lenny Taelman, Akshay Venkatesh View a PDF of the paper titled Shaping the Future of Mathematics in the Age of AI, by Johan Commelin and 4 other authors View PDF HTML (experimental) Abstract:Artificial intelligence is transforming mathematics at a speed and scale that demand active engagement from the mathematical community. We examine five areas where this transformation is particularly pressing: values, practice, teaching, technology, and ethics. We offer recommendations on safeguarding our intellectual autonomy, rethinking our practice, broadening curricula, building academically oriented infrastructure, and developing shared ethical principles - with the aim of ensuring that the future of mathematics is shaped by the community itself. Comments: Subjects: History and Overview (math.HO); Artificial Intelligence (cs.AI) Cite as: arXiv:2603.24914 [math.HO]   (or arXiv:2603.24914v1 [math.HO] for this version)   https://doi.org/10.48550/arXiv.2603.24914 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Akshay Venkatesh [view email] [v1] Thu, 26 Mar 2026 01:04:28 UTC (8 KB) Full-text links: Access Paper: View a PDF of the paper titled Shaping the Future of Mathematics in the Age of AI, by Johan Commelin and 4 other authorsView PDFHT...

Originally published on March 27, 2026. Curated by AI News.

Related Articles

Washington needs AI guardrails — now | Opinion
Ai Safety

Washington needs AI guardrails — now | Opinion

We need legislation that draws clear lines on what AI systems may and may not do on behalf of the United States government

AI Tools & Products · 3 min ·
[2601.12910] SciCoQA: Quality Assurance for Scientific Paper--Code Alignment
Ai Safety

[2601.12910] SciCoQA: Quality Assurance for Scientific Paper--Code Alignment

Abstract page for arXiv paper 2601.12910: SciCoQA: Quality Assurance for Scientific Paper--Code Alignment

arXiv - AI · 3 min ·
[2509.21385] Debugging Concept Bottleneck Models through Removal and Retraining
Machine Learning

[2509.21385] Debugging Concept Bottleneck Models through Removal and Retraining

Abstract page for arXiv paper 2509.21385: Debugging Concept Bottleneck Models through Removal and Retraining

arXiv - Machine Learning · 4 min ·
[2512.00804] Epistemic Bias Injection: Biasing LLMs via Selective Context Retrieval
Llms

[2512.00804] Epistemic Bias Injection: Biasing LLMs via Selective Context Retrieval

Abstract page for arXiv paper 2512.00804: Epistemic Bias Injection: Biasing LLMs via Selective Context Retrieval

arXiv - AI · 4 min ·
More in Ai Safety: This Week Guide Trending

No comments

No comments yet. Be the first to comment!

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Daily or weekly digest • Unsubscribe anytime