Why Data Science Must Inherently Be Interdisciplinary

Xiao-Li Meng, Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review. Meng was named the best statistician under the age of 40 by COPSS (Committee of Presidents of Statistical Societies) in 2001, and he is the recipient of numerous awards and honors for his more than 150 publications. In 2020, he was elected to the American Academy of Arts and Sciences. Meng received his BS in mathematics from Fudan University in 1982 and his PhD in statistics from Harvard in 1990. He was on the faculty of the University of Chicago before returning to Harvard, where he served as the Chair of the Department of Statistics (2004-2012) and the Dean of Graduate School of Arts and Sciences (2012-2017). IN THIS EPISODE: With a greater impact into more aspects of our lives, data science is no longer exclusively a topic for scientists or engineers. Xiao-Li Meng, Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review discusses the importance of a broader vision around our overall relationship with data and "data science". He explains why philosophers and others should be an integral part of our discussions, especially given some of the serious ethical and social challenges we face as a result of data automation.