The Optimizing Government Project drew together researchers from across the University of Pennsylvania and the Philadelphia area to collaborate on studying the implementation of machine learning by government.
The project aimed to assess the technical, legal, ethical, and political challenges associated with machine learning in government, promoting collaboration between government, the private sector, and the academy.
The project was centrally organized around seven major workshops held during the 2016-2017 academic year. This project website archives video recordings of each workshop. It also contains a variety of research papers and other resources related to governmental use of artificial intelligence.
The project was initiated and led by Cary Coglianese of the University of Pennsylvania Law School and the Penn Program on Regulation, in collaboration with other Penn faculty.
What is Machine Learning (and Why Might it be Unfair)?
Thurs., September 22, 2016, 4:30-6:00 pm
What is Fair and Equal Treatment?
Thurs., October 6, 2016, 4:30-6:00 pm
Fairness and Performance Trade-Offs in Machine Learning
Thurs., November 3, 2016, 4:30-6:00 pm
Regulating Robo-Advisors Across the Financial Services Industry
Fri., December 9, 2016, 12:00-1:20 pm
For the People, By the Robots? Democratic Governance in a Machine-Learning Era
Mon., February 20, 2017, 4:30-6:00 pm
Can Technology be Democratic? Transparency and Accountability in Machine Learning
Tues., March 21, 2017, 4:30-6:00 pm
Big Data and Government: Meeting the Real-World Challenges
Tues., April 11, 2017, 4:30-6:00 pm