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Statistics and AI: a rireside conversation

Author

Listed:
  • Lin, Xihong
  • Cai, Tianxi
  • Donoho, David
  • Fu, Haoda
  • Ke, Tracy
  • Jin, Jiashun
  • Meng, Xiao-Li
  • Qu, Annie
  • Shi, Chengchun
  • Song, Peter
  • Sun, Qiang
  • Wang, Wenyi
  • Wu, Hulin
  • Yu, Bin
  • Zhang, Heping
  • Zheng, Tian
  • Zhou, Harrison
  • Zhou, Jin
  • Zhu, Hongtu
  • Zhu, Ji

Abstract

A 3-hour webinar titled “Statistics and AI – A Fireside Conversation” was held on Sunday, March 17, 2024, attracting an online audience of approximately 1,000. The event featured three sessions aimed at engaging the statistical community on key topics in the AI era: addressing statistical challenges and opportunities (Panel I), evolving the publication process (Panel II), and advancing next-generation statistical pipelines and resources (Panel III). Panel I examined issues such as dwindling talent, shifting funding landscapes, and AI's rapid rise, highlighting the need for statistical rigor, interdisciplinary collaboration, and innovative approaches to shape the future of AI. Panel II emphasized the importance of streamlining the publication process, fostering impactful research, and prioritizing workflows and data quality. Panel III focused on modernizing statistical education by integrating AI and deep learning, promoting interdisciplinary collaboration, and maintaining foundational principles such as uncertainty and reproducibility. These discussions collectively outlined a strategic roadmap for ensuring the relevance and advancement of statistics in the age of AI.

Suggested Citation

  • Lin, Xihong & Cai, Tianxi & Donoho, David & Fu, Haoda & Ke, Tracy & Jin, Jiashun & Meng, Xiao-Li & Qu, Annie & Shi, Chengchun & Song, Peter & Sun, Qiang & Wang, Wenyi & Wu, Hulin & Yu, Bin & Zhang, He, 2025. "Statistics and AI: a rireside conversation," LSE Research Online Documents on Economics 128203, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:128203
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    More about this item

    Keywords

    artificial intelligence; statistical research; publication culture; statistics education; reproducibility; team science;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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