CFQ trains quantizer parameters and mixed-precision allocation to preserve counterfactual recourse validity, cost, and direction on Adult, German Credit, and COMPAS while matching accuracy of standard quantizers.
The accuracy, fairness, and limits of predicting recidivism
3 Pith papers cite this work. Polarity classification is still indexing.
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AI deployment in high-stakes areas requires domain-scoped calibrated verification with monitoring and revocation, using a proposed six-component Verification Coverage standard instead of mechanistic interpretability.
A six-dimension framework shows structural failures in four governance principles under radical capability asymmetry, with two requiring new normative theory and a pattern of interdependent breakdown.
citing papers explorer
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When Bits Break Recourse: Counterfactual-Faithful Quantization
CFQ trains quantizer parameters and mixed-precision allocation to preserve counterfactual recourse validity, cost, and direction on Adult, German Credit, and COMPAS while matching accuracy of standard quantizers.
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The Open-Box Fallacy: Why AI Deployment Needs a Calibrated Verification Regime
AI deployment in high-stakes areas requires domain-scoped calibrated verification with monitoring and revocation, using a proposed six-component Verification Coverage standard instead of mechanistic interpretability.
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Cognitive Comparability and the Limits of Governance: Evaluating Authority Under Radical Capability Asymmetry
A six-dimension framework shows structural failures in four governance principles under radical capability asymmetry, with two requiring new normative theory and a pattern of interdependent breakdown.