Conference: Statistics in the Age of AI

“人工智能时代的统计”会议将于2024年5月9日至11日在华盛顿特区的乔治华盛顿大学举行。随着人工智能（AI）的蓬勃发展，部分由于大型语言模型的推出而加速（例如，ChatGPT），人工智能工具已经到达我们社会的每个角落。在这个通过人工智能系统解决许多商业和科学问题的时代，统计学变得比以往任何时候都更加重要，因为它可以提供不确定性量化，因果分析和可解释性等，而这些都是大多数人工智能系统所缺乏的。本次会议将汇集学术界和行业的研究人员和从业人员，探讨人工智能对统计研究，教育和实践的影响，并集思广益统计如何为人工智能做出贡献。会议组织者鼓励学生，博士后学者，早期职业研究人员和代表性不足的群体的个人参与和出席。会议的特点是短期课程，海报和口头报告，以及小组讨论。这两个短期课程将分别侧重于因果推理和共形推理。演讲和小组讨论将讨论人工智能模型和架构数据的有效处理，不确定性量化以及负责任的决策等主题。更多信息将在会议网站上提供：https://statistics.columbian.gwu.edu/statistics-age-ai.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

The conference “Statistics in the Age of AI” will be held at George Washington University, Washington, DC on May 9-11, 2024. With the boom of artificial intelligence (AI), partly accelerated by the launching of large language models (e.g., ChatGPT), AI tools have reached every corner of our society. In this era where many business and scientific problems are being tackled via AI systems, statistics has become more critical than ever since it can offer uncertainty quantification, causal analysis, and interpretability among others, which most AI systems are lacking. This conference will bring together researchers and practitioners in academics and industries to explore the impact of AI on statistical research, education, and practice and also to brainstorm how statistics can contribute to AI. The conference organizers encourage participation and attendance by students, post-doctoral scholars, early-career researchers, and individuals from underrepresented groups. The conference features short courses, poster and oral presentations, and panel discussions. The two short courses will focus on causal inference and conformal inference respectively. The presentations and panel discussions will address efficient handling of data for AI models and architectures, uncertainty quantification, and responsible decision-making among other topics. Further information will become available on the conference website: https://statistics.columbian.gwu.edu/statistics-age-ai.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.