Computational Social Science

The Working Group on Computational Social Science at Columbia University, in partnership with the Institute for Social and Economic Research and Policy (ISERP) and the Data Science Institute (DSI) explores profound and urgent questions about how the information revolution will transform society as a whole.

The incipient field of computational social science continues to generate an array of interdisciplinary projects, often pursued in partnership with computer scientists, statisticians, and mathematicians. Some involve leveraging tools of prediction and machine learning to assist in tackling policy problems. Others entail applying recent advances in speech and image recognition to classic and novel problems in the social sciences. These projects often require methodological innovation or scaling proven techniques to new levels, as well as designing new metrics and interfaces to make research findings intelligible to scholars who lack coding skills but have deep domain expertise.

Computational social sciences raises inescapable questions about the politics and ethics of data science research, particularly when it focuses on sociopolitical problems with applications in government and the private sector. Just as with the field of genomics, to which computational social sciences has been compared, it may well take a generation before we see researchers who combine high-level competence in data science with equivalent expertise in anthropology, sociology, and other social sciences.

As of the present, we have yet to see an “Asilomar moment,” in which researchers pause to consider both the historical record and future risks before plunging ahead. Instead, there are vast experiments limited only by what researchers believe an informed public would consider “creepy.” Columbia seeks to be a convener for a more sophisticated conversation, grounded in an understanding of both the research itself and how it relates to law, philosophy, and ethics.

COMMITTEE

Matthew Connelly, History (Chair)
Manan Ahmed, History
Kelly M. Barrick, Libraries Social Sciences
Dave Blei, Statistics and Computer Science
Robert T. Cartolano, Libraries Administration
Augustin Chaintreau, Computer Science
Merlin Chowkwanyun, Sociomedical Sciences
Thomas DiPrete, Sociology
Greg Eirich, Sociology and ISERP
Andy Gelman, Statistics and Political Science
Alex Gil, Libraries Humanities/History
Alexander Hertel-Fernandez, School Intl & Public Affairs
Shigeo Hirano, Political Science
Julia Hirschberg, Computer Science
Matthew Jones, History
Bruce Kogut, Graduate School of Business and Sociology
Yao Lu, Sociology
Kathy McKeown, Computer Science
Andreas Mueller, Computer Science
Suresh Naidu, School Intl & Public Affairs and Economics
Emi Nakamura, Graduate School of Business and Economics
Alondra Nelson, Sociology
Mark Newton, Center for Digital Research and Scholarship
Serena Ng, Economics and School Intl & Public Affairs
David K. Park, Office of EVP Arts & Sciences
Kenneth Prewitt, School Intl & Public Affairs
Owen Rambow, Computational Learning Systems and Computer Science
Barbara Rockenbach, Libraries Humanities/History
David Rosner, Sociomedical Sciences
Pamela Smith, History
Jack Snyder, Political Science
David Stark, Sociology
Jón Steinsson, Economics
Eric Talley, Law
Dennis Tenen, English & Comp Literature
Ann D. Thornton, University Libraries
Dan Wang, Statistics and Sociology
Duncan Watts, ISERP
Greg Wawro, Political Science
Chris Wiggins, Applied Physics & Math
Tian Zheng, Statistics
Hugo Zylberberg, School Intl & Public Affairs


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