Latest / AI Ethics with Fexingo: Bias, Safety, and Responsible Artificial Intelligence
How AI Bias Creeps Into Public Benefits Systems
For episode 150 of AI Ethics, Lucas and Luna drill into a fresh, high-stakes corner of algorithmic fairness: automated eligibility systems used by public benefits agencies. They walk through how a model trained on historical case data can inherit the very inequities it was meant to fix, with a concrete example of a state Medicaid system that flagged a disproportionate share of applicants from certain zip codes. The conversation covers the specific mechanics — proxy variables, feedback loops, and the challenge of explaining a decision to someone whose benefits were just cut — and why the usual…
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