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The AI-Enabled Scientific FrontierThe AI-Enabled Scientific Frontier

📅 2026-09-16 ⏱️ 约 5 分钟阅读⏱️ 5 min read ✍️ AI导航编辑部✍️ AI Nav Editorial 🔗 arxiv.org
The AI-Enabled Scientific Frontier
📝 内容摘要📝 Summary

Computer Science > Artificial Intelligence [Submitted on 14 Sep 2026] Title:The AI-Enabled Scientific Frontier VieComputer Science > Artificial Intelligence [Submitted on 14 Sep 2026] Title:The AI-Enabled Scientific Frontier Vie

📌 核心要点

  • Computer Science > Artificial IntelligenceComputer Science > Artificial Intelligence
  • [Submitted on 14 Sep 2026][Submitted on 14 Sep 2026]
  • Title:The AI-Enabled Scientific FrontierTitle:The AI-Enabled Scientific Frontier

Computer Science > Artificial Intelligence

[Submitted on 14 Sep 2026]

Title:The AI-Enabled Scientific Frontier

View PDF HTML (experimental)Abstract:As artificial intelligence's capabilities improve, it is increasingly viewed as a general scientific method. But how true are these claims? Does AI outperform all techniques, or only some, and how is this changing? To assess the claims, we assemble a corpus of 2,507 head-to-head comparisons between AI and other scientific analysis techniques across 27 scientific disciplines from papers published between 2000 and early 2025. We find a profound dichotomy. Relative to traditional statistics, AI often outperforms, but at a significantly higher computational cost. But there are also nearly a quarter of cases where AI is both more expensive and performs worse than traditional statistical techniques and this fraction has been stable for a decade. Relative to scientific computing, AI often underperforms, but at lower computational cost. This has begun to change: since 2020, AI's performance against scientific computing has notably strengthened and it now outperforms on more than half of comparisons. These patterns suggest that AI is therefore not a universal replacement for existing methods, but rather a valuable -- and improving -- part of a new AI-enabled scientific frontier.

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Computer Science > Artificial Intelligence

[Submitted on 14 Sep 2026]

Title:The AI-Enabled Scientific Frontier

View PDF HTML (experimental)Abstract:As artificial intelligence's capabilities improve, it is increasingly viewed as a general scientific method. But how true are these claims? Does AI outperform all techniques, or only some, and how is this changing? To assess the claims, we assemble a corpus of 2,507 head-to-head comparisons between AI and other scientific analysis techniques across 27 scientific disciplines from papers published between 2000 and early 2025. We find a profound dichotomy. Relative to traditional statistics, AI often outperforms, but at a significantly higher computational cost. But there are also nearly a quarter of cases where AI is both more expensive and performs worse than traditional statistical techniques and this fraction has been stable for a decade. Relative to scientific computing, AI often underperforms, but at lower computational cost. This has begun to change: since 2020, AI's performance against scientific computing has notably strengthened and it now outperforms on more than half of comparisons. These patterns suggest that AI is therefore not a universal replacement for existing methods, but rather a valuable -- and improving -- part of a new AI-enabled scientific frontier.

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Bibliographic Explorer (What is the Explorer?)

Connected Papers (What is Connected Papers?)

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scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)

CatalyzeX Code Finder for Papers (What is CatalyzeX?)

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arXivLabs: experimental projects with community collaborators

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来源arxiv.org· 本文为编辑整理,仅供参考