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algorithmic-bias

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Fair-Code

Auditing algorithmic bias in criminal justice, hiring, lending, healthcare, welfare, and tenant screening: 7 open-source audits, measurable fairness gaps, and concrete fixes.

  • Updated Nov 6, 2026
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A deep exploration of Algorithmic Empathy, the next frontier in AI understanding. This project examines how machines can learn from human fallibility, model disagreement, and align with moral reasoning. It blends psychology, fairness metrics, interpretability, and co-learning design into one framework for humane intelligence.

  • Updated Nov 5, 2025

⚖️ An analytical framework for LAPD crime hotspot mapping with a focus on algorithmic fairness. This project identifies high-crime areas while rigorously auditing predictive models for bias, ensuring that resource allocation is driven by data without compromising social equity. 🚔📊

  • Updated Jul 3, 2026
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