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Workshop: Consequential Decisions in Dynamic Environments

Niki Kilbertus, Angela Zhou, Ashia Wilson, John Miller, Lily Hu, Lydia T. Liu, Nathan Kallus, Shira Mitchell

2020-12-12T08:00:00-08:00 - 2020-12-12T15:50:00-08:00
Abstract: Machine learning is rapidly becoming an integral component of sociotechnical systems. Predictions are increasingly used to grant beneficial resources or withhold opportunities, and the consequences of such decisions induce complex social dynamics by changing agent outcomes and prompting individuals to proactively respond to decision rules. This introduces challenges for standard machine learning methodology. Static measurements and training sets poorly capture the complexity of dynamic interactions between algorithms and humans. Strategic adaptation to decision rules can render statistical regularities obsolete. Correlations momentarily observed in data may not be robust enough to support interventions for long-term welfaremits of traditional, static approaches to decision-making, researchers in fields ranging from public policy to computer science to economics have recently begun to view consequential decision-making through a dynamic lens. This workshop will confront the use of machine learning to make consequential decisions in dynamic environments. Work in this area sits at the nexus of several different fields, and the workshop will provide an opportunity to better understand and synthesize social and technical perspectives on these issues and catalyze conversations between researchers and practitioners working across these diverse areas.


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2020-12-12T08:00:00-08:00 - 2020-12-12T08:10:00-08:00
Welcome and introduction
2020-12-12T08:10:00-08:00 - 2020-12-12T08:30:00-08:00
Invited Talk 1: What do we want? And when do we want it? Alternative objectives and their implications for experimental design.
Maximilian Kasy
2020-12-12T08:30:00-08:00 - 2020-12-12T08:50:00-08:00
Invited Talk 2: Country-Scale Bandit Implementation for Targeted COVID-19 Testing
Hamsa Bastani
2020-12-12T08:50:00-08:00 - 2020-12-12T09:00:00-08:00
Q&A for invited talks 1&2
2020-12-12T09:00:00-08:00 - 2020-12-12T10:00:00-08:00
Poster Session 1
2020-12-12T10:00:00-08:00 - 2020-12-12T10:20:00-08:00
Break 1
2020-12-12T10:20:00-08:00 - 2020-12-12T10:30:00-08:00
Introduction of invited speakers 3, 4
2020-12-12T10:30:00-08:00 - 2020-12-12T10:50:00-08:00
Invited Talk 3: Modeling the Dynamics of Poverty
Rediet Abebe
2020-12-12T10:50:00-08:00 - 2020-12-12T11:10:00-08:00
Invited Talk 4: From Moderate Deviations Theory to Distributionally Robust Optimization: Learning from Correlated Data
Daniel Kuhn
2020-12-12T11:10:00-08:00 - 2020-12-12T11:20:00-08:00
Q&A for invited talks 3, 4
2020-12-12T11:20:00-08:00 - 2020-12-12T11:25:00-08:00
Contributed Talk 1: Fairness Under Partial Compliance
Jessica Dai, Zachary Lipton
2020-12-12T11:25:00-08:00 - 2020-12-12T11:30:00-08:00
Contributed Talk 2: Better Together? How Externalities of Size Complicate Notions of Solidarity and Actuarial Fairness
Kate Donahue, Solon Barocas
2020-12-12T11:30:00-08:00 - 2020-12-12T11:35:00-08:00
Contributed Talk 3: Algorithmic Recourse: from Counterfactual Explanations to Interventions
Amir Karimi, Bernhard Schölkopf, Isabel Valera
2020-12-12T11:35:00-08:00 - 2020-12-12T11:45:00-08:00
Q&A for contributed talks 1,2,3
2020-12-12T11:45:00-08:00 - 2020-12-12T12:20:00-08:00
Break 2
2020-12-12T12:20:00-08:00 - 2020-12-12T12:30:00-08:00
Introduction of invited speakers 5, 6, 7
2020-12-12T12:30:00-08:00 - 2020-12-12T12:50:00-08:00
Invited Talk 5: What are some hurdles before we can attempt machine learning? Examples from the Public and Non-Profit Sector
Mitsue Iwata
2020-12-12T12:50:00-08:00 - 2020-12-12T13:13:00-08:00
Invited Talk 6: Unexpected Consequences of Algorithm-in-the-Loop Decision Making
Yiling Chen
2020-12-12T13:13:00-08:00 - 2020-12-12T13:35:00-08:00
Invited Talk 7: Prediction Dynamics
Moritz Hardt
2020-12-12T13:35:00-08:00 - 2020-12-12T13:50:00-08:00
Q&A for invited talks 5, 6, 7
2020-12-12T13:50:00-08:00 - 2020-12-12T14:20:00-08:00
Break 3
2020-12-12T14:20:00-08:00 - 2020-12-12T14:25:00-08:00
Contributed Talk 4: Strategic Recourse in Linear Classification
Yatong Chen, Yang Liu
2020-12-12T14:25:00-08:00 - 2020-12-12T14:30:00-08:00
Contributed Talk 5: Performative Prediction in a Stateful World
Shlomi Hod
2020-12-12T14:30:00-08:00 - 2020-12-12T14:35:00-08:00
Contributed Talk 6: Do Offline Metrics Predict Online Performance in Recommender Systems?
Karl Krauth, Sarah Dean, Wenshuo Guo, Benjamin Recht, Michael Jordan
2020-12-12T14:35:00-08:00 - 2020-12-12T14:45:00-08:00
Q&A for contributed talks 4, 5, 6
2020-12-12T14:45:00-08:00 - 2020-12-12T15:45:00-08:00
Poster Session 2
2020-12-12T15:45:00-08:00 - 2020-12-12T15:50:00-08:00
Wrap up