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TRACE: Explainability Debt Governance Framework
TRACE is a newly proposed academic governance framework for measuring "Explainability Debt" — the growing inability of production AI systems to justify their decisions — potentially relevant to future AI regulatory and compliance standards.
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TRACE (Transparency, Risk, Accountability, Compliance, and Explainability) is a proposed seven-instrument governance framework introduced in an arXiv paper for measuring, tracking, and remediating "Explainability Debt" in production AI systems (arXiv, October 9). The framework's foundational instrument is the Explainability Debt Score (EDS), designed to detect the progressive inability of deployed AI systems to explain individual decisions when regulators, auditors, or affected individuals demand accountability. As AI regulation intensifies globally, frameworks like TRACE could become reference points for compliance standards and audits.