Panel: How Can Machine Learning and Information Technology Make Government More Responsive
(Public and Non-Profit Management and Finance)

Friday, November 8, 2019: 3:15 PM-4:45 PM
Plaza Building: Concourse Level, Plaza Court 6 (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Panel Chair:  Ryan P. Scott, Colorado State University
Discussants:  Federica Fusi, University of Illinois, Chicago and Ryan P. Scott, Colorado State University

How Can Machine Learning and Information Technology Make Government More Responsive


Manual Categories Versus Machine Learning in U.S. Social Policy: The Case of Housing Vouchers and School Districts
Rebecca Johnson and Simone Zhang, Princeton University



ICT As Public Engagement Tool: Evidence from the U.S. City Governments
Haneul Choi, Arizona State University



Megaphone or Mute Button? an Experiment to Test the Equity Implications of Representative Bureaucracy for Machine Learning
Matthew Young, Syracuse University and Peter Mawhorter, Wellesley College




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