AINeutralarXiv – CS AI · Feb 277/107
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Operationalizing Fairness: Post-Hoc Threshold Optimization Under Hard Resource Limits
Researchers developed a new framework for deploying AI systems in high-stakes environments that balances safety, fairness, and efficiency under strict resource constraints. The study found that capacity limits dominate ethical considerations, determining deployment thresholds in over 80% of tested scenarios while maintaining better performance than traditional fairness approaches.
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