Search Results for author:
Found 13 papers, 7 papers with code
Auditing the Use of Language Models to Guide Hiring Decisions
We find evidence of moderate race and gender disparities, a pattern largely robust to varying the types of application material input to the models, as well as the framing of the task to the LLMs.
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
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?
Designing Equitable Algorithms
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.
Causal Conceptions of Fairness and their Consequences
Recent work highlights the role of causality in designing equitable decision-making algorithms.
Adaptive Sampling Strategies to Construct Equitable Training Datasets
In domains ranging from computer vision to natural language processing, machine learning models have been shown to exhibit stark disparities, often performing worse for members of traditionally underserved groups.
Learning to be Fair: A Consequentialist Approach to Equitable Decision-Making
In our approach, one first elicits stakeholder preferences over the space of possible decisions and the resulting outcomes--such as preferences for balancing spending parity against court appearance rates.
Probability Paths and the Structure of Predictions over Time
Given a collection of such probability paths, we introduce a Bayesian framework -- which we call the Gaussian latent information martingale, or GLIM -- for modeling the structure of dynamic predictions over time.
Surveilling Surveillance: Estimating the Prevalence of Surveillance Cameras with Street View Data
In a detailed analysis of the 10 U. S. cities, we find that cameras are concentrated in commercial, industrial, and mixed zones, and in neighborhoods with higher shares of non-white residents -- a pattern that persists even after adjusting for land use.
The Measure and Mismeasure of Fairness
The field of fair machine learning aims to ensure that decisions guided by algorithms are equitable.
Computers and Society
A large-scale analysis of racial disparities in police stops across the United States
We find that black drivers are stopped more often than white drivers relative to their share of the driving-age population, but that Hispanic drivers are stopped less often than whites.
Applications
Fast Threshold Tests for Detecting Discrimination
Threshold tests have recently been proposed as a useful method for detecting bias in lending, hiring, and policing decisions.
Simple rules for complex decisions
From doctors diagnosing patients to judges setting bail, experts often base their decisions on experience and intuition rather than on statistical models.
Predictive Indexing for Fast Search
We tackle the computational problem of query-conditioned search.
