Data-empowered products and decision automated decision systems increasingly determine our political, professional, and personal realities. How did we come to this data moment? And how do we shape its future, as scholars and educators, as well as consumers and members of the electorate? I'll briefly share lessons learned from a class investigating these questions, co-developed with Matthew L. Jones, a historian of science, technology, and mathematics at Columbia University, and the resulting book (http://bit.ly/hdh-book), published in 2023. Additional material, syllabus, readings, and code (in Python) can be found via https://data-ppf.github.io/.
About the speaker
About the speaker
Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. At Columbia, he is a founding member of the executive committee of the Data Science Institute, and of the Department of Applied Physics and Applied Mathematics, as well as the Department of Systems Biology, and is affiliated faculty in Statistics. He is a co-founder and co-organizer of hackNY (http://hackNY.org), a nonprofit since 2010, which has organized the hackNY Fellows Program, a structured summer internship at NYC startups. Prior to joining the faculty at Columbia, he was a Courant Instructor at NYU (1998-2001) and earned his PhD at Princeton University (1993-1998) in theoretical physics. He is a Fellow of the American Physical Society and is a recipient of Columbia's Avanessians Diversity Award. His book, Data Science in Context: Foundations, Challenges, Opportunities, with Alfred Spector, Peter Norvig, and Jeannette M. Wing, was published by Cambridge University Press in October 2022. His book, How Data Happened: A History from the Age of Reason to the Age of Algorithms, with Matthew L. Jones, was published by Norton Press in March 2023.
Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. At Columbia, he is a founding member of the executive committee of the Data Science Institute, and of the Department of Applied Physics and Applied Mathematics, as well as the Department of Systems Biology, and is affiliated faculty in Statistics. He is a co-founder and co-organizer of hackNY (http://hackNY.org), a nonprofit since 2010, which has organized the hackNY Fellows Program, a structured summer internship at NYC startups. Prior to joining the faculty at Columbia, he was a Courant Instructor at NYU (1998-2001) and earned his PhD at Princeton University (1993-1998) in theoretical physics. He is a Fellow of the American Physical Society and is a recipient of Columbia's Avanessians Diversity Award. His book, Data Science in Context: Foundations, Challenges, Opportunities, with Alfred Spector, Peter Norvig, and Jeannette M. Wing, was published by Cambridge University Press in October 2022. His book, How Data Happened: A History from the Age of Reason to the Age of Algorithms, with Matthew L. Jones, was published by Norton Press in March 2023.
