An investigation of disparate outcomes in internet deals across 38 major cities in the United States.
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Updated
Oct 25, 2022 - Jupyter Notebook
An investigation of disparate outcomes in internet deals across 38 major cities in the United States.
📊 R package for computing and visualizing fair ML metrics
Implementation of the paper "Fair Clustering Through Fairlets" by Chierichetti et al. (NIPS 2017)
What You See is What You Get: Distributional Generalization for Algorithm Design in Deep Learning
Fairness-aware ICU mortality prediction using MIMIC-III data and Group-Aware SMOTE
Open source React app for testing AI systems for bias and disparate impact using the Anthropic Claude API. Fisher's Exact, Chi-Square, and Z-test. Based on NIST AI RMF 1.0, NIST SP 1270, EEOC Technical Assistance on AI and Title VII (May 2023)
Bias detection and mitigation in the COMPAS dataset using fairness-aware machine learning techniques.
HRai Labs - Open source toolkit
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