28 citations · 38 across the 4 of their papers we have counts for
6 papers
Reducing SNAP Payment Errors at Lower Cost With AI: A Simulation Study
Alex Chohlas-Wood
New federal legislation will require states with high payment error rates in the Supplemental Nutrition Assistance Program (SNAP) to pay a share of benefit costs, potentially costi…
Algorithm Validation as a Policy Audit: Evidence from Race-blind Charging
Muskan Walia, Joe Nudell, Alex Chohlas-Wood
California recently required all prosecutors in the state to conduct a "race-blind charging" decision by reviewing case documents in which selected race-related proxies have been r…
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
Neel Guha, Julian Nyarko, Daniel E. Ho +37
The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform? To enable great…
Automated Reminders Reduce Incarceration for Missed Court Dates: Evidence from a Text Message Experiment
Alex Chohlas-Wood, Madison Coots, Joe Nudell +4
Millions of Americans must attend mandatory court dates every year. To boost appearance rates, jurisdictions nationwide are increasingly turning to automated reminders, but previou…
Designing Equitable Algorithms
Alex Chohlas-Wood, Madison Coots, Sharad Goel +1
Predictive algorithms are now used to help distribute a large share of our society's resources and sanctions, such as healthcare, loans, criminal detentions, and tax audits. Under…
Learning to be Fair: A Consequentialist Approach to Equitable Decision-Making
Alex Chohlas-Wood, Madison Coots, Henry Zhu +2
In an attempt to make algorithms fair, the machine learning literature has largely focused on equalizing decisions, outcomes, or error rates across race or gender groups. To illust…