Workshop: Machine Learning for Economic Policy

Stephan Zheng, Alex Trott, Annie Liang, Jamie Morgenstern, David Parkes, Nika Haghtalab

2020-12-11T09:00:00-08:00 - 2020-12-11T16:00:00-08:00
Abstract: www.mlforeconomicpolicy.com
mlforeconomicpolicy.neurips2020@gmail.com

The goal of this workshop is to inspire and engage a broad interdisciplinary audience, including computer scientists, economists, and social scientists, around topics at the exciting intersection of economics, public policy, and machine learning. We feel that machine learning offers enormous potential to transform our understanding of economics, economic decision making, and public policy, and yet its adoption by economists and social scientists remains nascent.

We want to use the workshop to expose some of the critical socio-economic issues that stand to benefit from applying machine learning, expose underexplored economic datasets and simulations, and identify machine learning research directions that would have significant positive socio-economic impact. In effect, we aim to accelerate the use of machine learning to rapidly develop, test, and deploy fair and equitable economic policies that are grounded in representative data.

For example, we would like to explore questions around whether machine learning can be used to help with the development of effective economic policy, to understand economic behavior through granular, economic data sets, to automate economic transactions for individuals, and how we can build rich and faithful simulations of economic systems with strategic agents. We would like to develop economic policies and mechanisms that target socio-economic issues including diversity and fair representation in economic outcomes, economic equality, and improving economic opportunity. In particular, we want to highlight both the opportunities as well as the barriers to adoption of ML in economics.

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Schedule

2020-12-11T09:00:00-08:00 - 2020-12-11T09:05:00-08:00
Introduction 1
2020-12-11T09:05:00-08:00 - 2020-12-11T09:45:00-08:00
Keynote: Michael Kearns
Michael Kearns
Privacy and Fairness in Markets and Finance
2020-12-11T09:45:00-08:00 - 2020-12-11T10:00:00-08:00
Best Paper (Empirical)
"Estimating Policy Functions in Payment Systems using Reinforcement Learning” P. Castro, A. Desai, H. Du, R. Garratt, F. Rivadeneyra
2020-12-11T10:00:00-08:00 - 2020-12-11T10:05:00-08:00
5 Minute Break
2020-12-11T10:05:00-08:00 - 2020-12-11T10:45:00-08:00
Keynote: Doina Precup
Doina Precup
2020-12-11T10:45:00-08:00 - 2020-12-11T11:45:00-08:00
Panel Discussion: Algorithms & Methodology
Eva Tardos Thore Graepel Doyne Farmer TBC
2020-12-11T11:45:00-08:00 - 2020-12-11T12:00:00-08:00
15 Minute Break
2020-12-11T12:00:00-08:00 - 2020-12-11T12:40:00-08:00
Keynote: Susan Athey
Susan Athey
2020-12-11T12:40:00-08:00 - 2020-12-11T12:55:00-08:00
Best Paper (Methodology)
“Empirical Welfare Maximization with Constraints”, L. Sun
2020-12-11T12:55:00-08:00 - 2020-12-11T13:00:00-08:00
5 Minute Break
2020-12-11T13:00:00-08:00 - 2020-12-11T13:40:00-08:00
Keynote: Sendhil Mullainathan
Sendhil Mullainathan
Machine Learning and Economic Policy: The Uses of Prediction Machine learning tools excel at producing models that work in a predictive sense. Economics and policy, however, rely heavily on causality. One fruitful approach to this tension is to marry causal inference and machine learning techniques. In this talk, I will argue for a complementary, second approach: that prediction in and of itself can be very useful for a swath of applications. Many important policy problems have embedded in them pure prediction problems. Moreover, prediction tools by themselves can help reveal fundamental social mechanisms. These kinds of applications are plentiful, but sit in a blind spot: because we have not had prediction tools in the past, we are not used to seeing them.
2020-12-11T13:40:00-08:00 - 2020-12-11T14:40:00-08:00
Panel Discussion: ML in Economics & Real-World Policy
Rediet Abebe Sharad Goel Dan Bjorkegren Marietje Schaake
2020-12-11T14:40:00-08:00 - 2020-12-11T14:45:00-08:00
5 Minute Break
2020-12-11T14:45:00-08:00 - 2020-12-11T16:00:00-08:00
Posters, Focus Groups, Unstructured Discussion
GatherTown Poster Session