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AI accountability framework links public sector decisions to legal rules

By PulseAugur Editorial · [1 sources] ·

This research paper introduces a novel neuro-symbolic framework designed to enhance accountability in public-sector AI systems. The framework links AI-generated decision justifications to specific legal rules, using CalFresh, California's food assistance program, as a case study. It combines a structured ontology of eligibility requirements with a rule extraction pipeline and a solver-based reasoning layer to identify and correct legally inconsistent explanations, thereby supporting procedural accountability. AI

IMPACT Enhances transparency and contestability of AI decisions in public services, potentially setting a precedent for other government applications.

RANK_REASON Academic paper on a novel AI framework for accountability. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI accountability framework links public sector decisions to legal rules

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Academic paper on a novel AI framework for accountability. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Allen Daniel Sunny, Ido Sivan-Sevilla ·

    A Neuro-Symbolic Framework for Accountability in Public-Sector AI

    arXiv:2512.12109v3 Announce Type: replace-cross Abstract: Automated eligibility systems increasingly determine access to essential public benefits, but the explanations they generate often fail to reflect the legal rules that authorize those decisions. This thesis develops a lega…

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