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05/27/2023
Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems
Many recommender systems are based on optimizing a linear weighting of d...
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05/26/2023
Twitter's Algorithm: Amplifying Anger, Animosity, and Affective Polarization
As social media continues to have a significant influence on public opin...
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07/19/2021
Causal Inference Struggles with Agency on Online Platforms
Online platforms regularly conduct randomized experiments to understand ...
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08/21/2020
From Optimizing Engagement to Measuring Value
Most recommendation engines today are based on predicting user engagemen...
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02/12/2020
Reward-rational (implicit) choice: A unifying formalism for reward learning
It is often difficult to hand-specify what the correct reward function i...
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12/03/2019
Value-laden Disciplinary Shifts in Machine Learning
As machine learning models are increasingly used for high-stakes decisio...
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10/23/2019
Strategic Adaptation to Classifiers: A Causal Perspective
Consequential decision-making incentivizes individuals to adapt their be...
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03/09/2019
Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning
It is incredibly easy for a system designer to misspecify the objective ...
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08/25/2018
The Social Cost of Strategic Classification
Consequential decision-making typically incentivizes individuals to beha...
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07/13/2018
Model Reconstruction from Model Explanations
We show through theory and experiment that gradient-based explanations o...
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11/08/2017
Inverse Reward Design
Autonomous agents optimize the reward function we give them. What they d...
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11/02/2017
Interpretable and Pedagogical Examples
Teachers intentionally pick the most informative examples to show their ...
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05/28/2017
