yakew7/Fair-Code

v1.0.0 Feature

This release adds 3 notable features for engineering teams evaluating rollout.

Published 1mo AI Coding Tools

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✓ No known CVEs patched

Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

ai-fairness algorithmic-bias bias-detection bias-mitigation criminal-justice fairness

+9 more

healthcare hiring jupyter lending machine-learning python responsible-ai scikit-learn welfare

Summary

AI summary

Adds five bias audits, thirteen explainers, five notebooks, a live website, and CI pipeline.

Full changelog

Fair Code's first tagged release. The project has been live and open to contributors since May 2026. This tag marks the point where the core scope is complete: 5 audits, 13 explainers, full notebook walkthroughs, a live website, and a CI pipeline.

What's included

5 bias audits

Criminal Justice (COMPAS, 70,000+ records) -71% gap reduction
Hiring (AI Fair Recruitment, ~6,500 records) - 97.3% gap reduction
Lending (German Credit, 1,000 records) - 73.6% gap reduction
Healthcare (Insurance Denial, 1,340 records) - 60–72% gap reduction
Welfare Eligibility (UCI Adult Census, 48,842 records) - 46–88% gap reduction

13 explainers
Proxy Variables, Equalized Odds, Sampling Bias, SHAP Values, Disparate Impact, Disparate Treatment, Fairness Metric Conflicts, Calibration, Demographic Parity, Feedback Loop Bias, Label Bias, Individual Fairness, Counterfactual Fairness

5 Jupyter notebooks - full walkthrough of every audit with visualisations and proxy detection

Live website - fair-code-five.vercel.app

CI pipeline - all audit scripts run automatically on every push and PR

View diff on GitHub

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