AI Integrity is defined as verifiable protection of an AI system's four-layer Authority Stack from corruption, with PRISM as the measurement framework.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.AI 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Eight AI models show split value priorities at the top layer, divergent evidence preferences in the middle, and broad convergence on institutional sources at the bottom, with substantial sensitivity to scenario framing.
citing papers explorer
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AI Integrity: A New Paradigm for Verifiable AI Governance
AI Integrity is defined as verifiable protection of an AI system's four-layer Authority Stack from corruption, with PRISM as the measurement framework.
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Measuring the Authority Stack of AI Systems: Empirical Analysis of 366,120 Forced-Choice Responses Across 8 AI Models
Eight AI models show split value priorities at the top layer, divergent evidence preferences in the middle, and broad convergence on institutional sources at the bottom, with substantial sensitivity to scenario framing.