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February 27, 20260 citationsOpen Access

When AI Enters Federal Statistics: A Crosswalk Between Data Quality and AI Trustworthiness Frameworks

BWBrock F Webb

Key Points

  • The aim is to systematically connect the data quality and AI trustworthiness frameworks used by federal agencies.
  • Conducted a systematic crosswalk between FCSM 20-04 and NIST AI RMF 1.0
  • Mapped relationships across 11 FCSM dimensions and 72 NIST subcategories
  • Identified structural gaps in both frameworks
  • Demonstrated the crosswalk with two experimental implementations.
  • Established a complete bidirectional mapping between the two frameworks
  • Highlighted critical gaps in both data quality and AI trustworthiness areas
  • Improved understanding of the relationship between statistical production and AI implementation.

Abstract

Federal agencies using AI in statistical production face two frameworks that don't reference each other: FCSM 20-04 (data quality) and NIST AI RMF 1.0 (AI trustworthiness). This paper presents the first systematic crosswalk between them, mapping relationships across 11 FCSM dimensions and 72 NIST subcategories. It identifies structural gaps in both frameworks, and two experimental implementations demonstrate the crosswalk in practice. A complete bidirectional mapping is provided in the appendix.

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Cite This Study

Brock F Webb (2026) studied this question.

synapsesocial.com/papers/69a13591ed1d949a99abf9abhttps://doi.org/10.5281/zenodo.18766095
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