Statistics and AI: a rireside conversation

Lin, Xihong, Cai, Tianxi, Donoho, David, Fu, Haoda, Ke, Tracy, Jin, Jiashun, Meng, Xiao-Li, Qu, Annie, Shi, Chengchun ORCID: 0000-0001-7773-2099, Song, Peter, Sun, Qiang, Wang, Wenyi, Wu, Hulin, Yu, Bin, Zhang, Heping, Zheng, Tian, Zhou, Harrison, Zhou, Jin, Zhu, Hongtu and Zhu, Ji (2025) Statistics and AI: a rireside conversation. Harvard Data Science Review, 7 (2).

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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.

Item Type:	Article
Additional Information:	© 2025 The Authors
Divisions:	Statistics
Subjects:	Q Science > Q Science (General) H Social Sciences > HA Statistics
Date Deposited:	29 May 2025 10:36
Last Modified:	29 May 2025 10:36
URI:	http://eprints.lse.ac.uk/id/eprint/128203

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