4 papers
Winner's Curse Drives False Promises in Data-Driven Decisions: A Case Study in Refugee Matching
Hamsa Bastani, Osbert Bastani, Bryce McLaughlin
A major challenge in data-driven decision-making is accurate policy evaluation-i.e., guaranteeing that a learned decision-making policy achieves the promised benefits. A popular st…
Are AI Capabilities Increasing Exponentially? A Competing Hypothesis
Haosen Ge, Hamsa Bastani, Osbert Bastani
Rapidly increasing AI capabilities have substantial real-world consequences, ranging from AI safety concerns to labor market consequences. The Model Evaluation & Threat Research (M…
Beating the Winner's Curse via Inference-Aware Policy Optimization
Hamsa Bastani, Osbert Bastani, Bryce McLaughlin
There has been a surge of recent interest in automatically learning policies to target treatment decisions based on rich individual covariates. In addition, practitioners want conf…
Strategic Hiring under Algorithmic Monoculture
Jackie Baek, Hamsa Bastani, Shihan Chen
We study the impact of strategic behavior in labor markets characterized by algorithmic monoculture, where firms compete for a shared pool of applicants using a common algorithmic…