Dear ASA friends:
I'd like to share an important paper titled "Statistics and AI: A Fireside Conversation", just published in Issue 7.2 of the Harvard Data Science Review. This paper is based on a three-hour webinar held on Sunday, March 17, 2024, and features rich discussions on key topics, including:
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Statistical challenges and opportunities (Panel I)
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The evolving publication process in the AI era (Panel II)
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Advancing next-generation statistical pipelines and resources (Panel III)
The full recording of this event is available on our Stats Up AI YouTube channel.
ASA members are invited to join our ASA Interest Group via the ASA Community platform. To join, simply click the "Join Community" button on the right side of our interest group's page.
best
hongtu
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Statistics and AI: A Fireside Conversation
by Xihong Lin, Tianxi Cai, David Donoho, Haoda Fu, Tracy Ke, Jiashun Jin, Xiao-Li Meng, Annie Qu, Chengchun Shi, Peter Song, Qiang Sun, Wenyi Wang, Hulin Wu, Bin Yu, Heping Zhang, Tian Zheng, Harrison Zhou, Jin Zhou, Hongtu Zhu, and Ji Zhu
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.
These discussions were organized by (in alphabetical order) Xihong Lin (Harvard University), Tracy Ke (Harvard University), Tian Zheng (Columbia University), Jing Zhou (University of California at Los Angeles), and Hongtu Zhu (University of North Carolina at Chapel Hill).
In the dynamic landscape of statistical science, the fireside chat organized by the Stats Up AI Alliance (https://statsupai.org/) and the International Chinese Statistical Association (ICSA) emerged as a seminal event, bringing together leading experts to explore the evolving role of statistics in the era of artificial intelligence.
Keywords: artificial intelligence, statistical research, publication culture, statistics education, reproducibility, team science
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Hongtu Zhu
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