Law / Frameworks / Crosswalk / NIST AI RMF to FINOS AIGF

The NIST AI Risk Management Framework, mapped to the FINOS AI Governance Framework

28 of NIST AI RMF's controls connect to 16 of FINOS AIGF's through 489 laws in 176 jurisdictions. Two controls connect when the same duties, in at least 2 laws we track, reach both. The connections are our own reading of the law; no framework publisher has reviewed or endorsed them.

From
NIST AI Risk Management Framework, version 1.0, January 2023 (NIST AI 100-1), National Institute of Standards and Technology
To
FINOS AI Governance Framework, version 2, as maintained on , FINOS
See also
FINOS AIGF to NIST AI RMF, the other way · every pair in the crosswalk · law library as of

Download this mapping, with every law behind each connection: nist-ai-rmf--finos-ai-governance-framework.csv · nist-ai-rmf--finos-ai-governance-framework.json

NIST AI RMFFINOS AIGFLawsJurisdictionsWhere the laws stand
GOVERN 1.1Legal and regulatory requirements involving AI are understood, managed, and documented. AIR-DET-004AI System Observability 41 22 31 in force, 9 not yet in force, 1 proposed
The 41 laws behind GOVERN 1.1 and AIR-DET-004

and 31 more, every one in the free file.

AIR-DET-021Agent Decision Audit and Explainability 41 22 31 in force, 9 not yet in force, 1 proposed
The 41 laws behind GOVERN 1.1 and AIR-DET-021

and 31 more, every one in the free file.

AIR-PREV-005System Acceptance Testing 38 20 28 in force, 9 not yet in force, 1 proposed
The 38 laws behind GOVERN 1.1 and AIR-PREV-005

and 28 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 38 20 28 in force, 9 not yet in force, 1 proposed
The 38 laws behind GOVERN 1.1 and AIR-PREV-006

and 28 more, every one in the free file.

AIR-PREV-024Human-in-the-Loop Action Approval Gate 38 20 28 in force, 9 not yet in force, 1 proposed
The 38 laws behind GOVERN 1.1 and AIR-PREV-024

and 28 more, every one in the free file.

AIR-DET-011Human Feedback Loop for AI Systems 38 20 28 in force, 9 not yet in force, 1 proposed
The 38 laws behind GOVERN 1.1 and AIR-DET-011

and 28 more, every one in the free file.

GOVERN 1.4The risk management process and its outcomes are established through transparent... AIR-PREV-005System Acceptance Testing 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and AIR-PREV-005

and 7 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and AIR-PREV-006

and 7 more, every one in the free file.

AIR-PREV-024Human-in-the-Loop Action Approval Gate 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and AIR-PREV-024

and 7 more, every one in the free file.

AIR-DET-004AI System Observability 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and AIR-DET-004

and 7 more, every one in the free file.

AIR-DET-011Human Feedback Loop for AI Systems 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and AIR-DET-011

and 7 more, every one in the free file.

AIR-DET-021Agent Decision Audit and Explainability 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and AIR-DET-021

and 7 more, every one in the free file.

GOVERN 1.6Mechanisms are in place to inventory AI systems and are resourced according to... AIR-PREV-005System Acceptance Testing 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and AIR-PREV-024
AIR-DET-004AI System Observability 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and AIR-DET-011
AIR-DET-021Agent Decision Audit and Explainability 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and AIR-DET-021
GOVERN 2.1Roles and responsibilities and lines of communication related to mapping, measuring,... AIR-PREV-005System Acceptance Testing 7 6 7 in force
The 7 laws behind GOVERN 2.1 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 7 6 7 in force
The 7 laws behind GOVERN 2.1 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 7 6 7 in force
The 7 laws behind GOVERN 2.1 and AIR-PREV-024
AIR-DET-004AI System Observability 7 6 7 in force
The 7 laws behind GOVERN 2.1 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 7 6 7 in force
The 7 laws behind GOVERN 2.1 and AIR-DET-011
AIR-DET-021Agent Decision Audit and Explainability 7 6 7 in force
The 7 laws behind GOVERN 2.1 and AIR-DET-021
GOVERN 2.3Executive leadership of the organization takes responsibility for decisions about... AIR-PREV-005System Acceptance Testing 4 4 4 in force
The 4 laws behind GOVERN 2.3 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 4 4 4 in force
The 4 laws behind GOVERN 2.3 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 4 4 4 in force
The 4 laws behind GOVERN 2.3 and AIR-PREV-024
AIR-DET-004AI System Observability 4 4 4 in force
The 4 laws behind GOVERN 2.3 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 4 4 4 in force
The 4 laws behind GOVERN 2.3 and AIR-DET-011
AIR-DET-021Agent Decision Audit and Explainability 4 4 4 in force
The 4 laws behind GOVERN 2.3 and AIR-DET-021
GOVERN 4.2Organizational teams document the risks and potential impacts of the AI technology... AIR-DET-021Agent Decision Audit and Explainability 10 7 6 in force, 3 not yet in force, 1 proposed
The 10 laws behind GOVERN 4.2 and AIR-DET-021
AIR-DET-004AI System Observability 8 6 5 in force, 3 not yet in force
The 8 laws behind GOVERN 4.2 and AIR-DET-004
AIR-PREV-005System Acceptance Testing 2 2 2 in force
The 2 laws behind GOVERN 4.2 and AIR-PREV-005
GOVERN 4.3Organizational practices are in place to enable AI testing, identification of... AIR-DET-004AI System Observability 2 2 1 in force, 1 not yet in force
The 2 laws behind GOVERN 4.3 and AIR-DET-004
AIR-DET-021Agent Decision Audit and Explainability 2 2 1 in force, 1 not yet in force
The 2 laws behind GOVERN 4.3 and AIR-DET-021
GOVERN 6.1Policies and procedures are in place that address AI risks associated with third-party... AIR-PREV-007Legal and Contractual Frameworks for AI Systems 2 2 1 in force, 1 not yet in force
The 2 laws behind GOVERN 6.1 and AIR-PREV-007
MAP 1.6System requirements (e.g., “the system shall respect the privacy of its users”) are... AIR-DET-021Agent Decision Audit and Explainability 4 4 3 in force, 1 not yet in force
The 4 laws behind MAP 1.6 and AIR-DET-021
MAP 2.2Information about the AI system’s knowledge limits and how system output may be... AIR-DET-021Agent Decision Audit and Explainability 5 4 1 in force, 4 not yet in force
The 5 laws behind MAP 2.2 and AIR-DET-021
MAP 2.3Scientific integrity and TEVV considerations are identified and documented, including... AIR-PREV-005System Acceptance Testing 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and AIR-PREV-005

and 2 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and AIR-PREV-006

and 2 more, every one in the free file.

AIR-PREV-024Human-in-the-Loop Action Approval Gate 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and AIR-PREV-024

and 2 more, every one in the free file.

AIR-DET-004AI System Observability 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and AIR-DET-004

and 2 more, every one in the free file.

AIR-DET-011Human Feedback Loop for AI Systems 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and AIR-DET-011

and 2 more, every one in the free file.

AIR-DET-021Agent Decision Audit and Explainability 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and AIR-DET-021

and 2 more, every one in the free file.

MAP 3.3Targeted application scope is specified and documented based on the system’s... AIR-PREV-005System Acceptance Testing 148 88 127 in force, 17 not yet in force, 1 blocked by a court, 3 proposed
The 148 laws behind MAP 3.3 and AIR-PREV-005

and 138 more, every one in the free file.

AIR-DET-021Agent Decision Audit and Explainability 5 4 4 in force, 1 not yet in force
The 5 laws behind MAP 3.3 and AIR-DET-021
AIR-PREV-006Data Quality & Classification/Sensitivity 4 3 3 in force, 1 not yet in force
The 4 laws behind MAP 3.3 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 3 2 3 in force
The 3 laws behind MAP 3.3 and AIR-PREV-024
AIR-DET-004AI System Observability 3 2 3 in force
The 3 laws behind MAP 3.3 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 3 2 3 in force
The 3 laws behind MAP 3.3 and AIR-DET-011
MAP 3.5Processes for human oversight are defined, assessed, and documented in accordance with... AIR-DET-021Agent Decision Audit and Explainability 29 22 21 in force, 8 not yet in force
The 29 laws behind MAP 3.5 and AIR-DET-021

and 19 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 28 21 20 in force, 8 not yet in force
The 28 laws behind MAP 3.5 and AIR-PREV-006

and 18 more, every one in the free file.

AIR-PREV-005System Acceptance Testing 26 19 18 in force, 8 not yet in force
The 26 laws behind MAP 3.5 and AIR-PREV-005

and 16 more, every one in the free file.

AIR-PREV-024Human-in-the-Loop Action Approval Gate 25 18 17 in force, 8 not yet in force
The 25 laws behind MAP 3.5 and AIR-PREV-024

and 15 more, every one in the free file.

AIR-DET-004AI System Observability 25 18 17 in force, 8 not yet in force
The 25 laws behind MAP 3.5 and AIR-DET-004

and 15 more, every one in the free file.

AIR-DET-011Human Feedback Loop for AI Systems 25 18 17 in force, 8 not yet in force
The 25 laws behind MAP 3.5 and AIR-DET-011

and 15 more, every one in the free file.

MAP 4.1Approaches for mapping AI technology and legal risks of its components – including the... AIR-PREV-018Agent Authority Least Privilege Framework 145 107 142 in force, 3 not yet in force
The 145 laws behind MAP 4.1 and AIR-PREV-018

and 135 more, every one in the free file.

AIR-PREV-023Agentic System Credential Protection Framework 145 107 142 in force, 3 not yet in force
The 145 laws behind MAP 4.1 and AIR-PREV-023

and 135 more, every one in the free file.

AIR-PREV-007Legal and Contractual Frameworks for AI Systems 51 39 50 in force, 1 not yet in force
The 51 laws behind MAP 4.1 and AIR-PREV-007

and 41 more, every one in the free file.

AIR-DET-013Providing Citations and Source Traceability for AI-Generated Information 33 28 33 in force
The 33 laws behind MAP 4.1 and AIR-DET-013

and 23 more, every one in the free file.

AIR-PREV-005System Acceptance Testing 3 3 2 in force, 1 not yet in force
The 3 laws behind MAP 4.1 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 2 2 2 in force
The 2 laws behind MAP 4.1 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 2 2 2 in force
The 2 laws behind MAP 4.1 and AIR-PREV-024
AIR-DET-004AI System Observability 2 2 2 in force
The 2 laws behind MAP 4.1 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 2 2 2 in force
The 2 laws behind MAP 4.1 and AIR-DET-011
AIR-DET-021Agent Decision Audit and Explainability 2 2 2 in force
The 2 laws behind MAP 4.1 and AIR-DET-021
MAP 5.1Likelihood and magnitude of each identified impact (both potentially beneficial and... AIR-PREV-005System Acceptance Testing 14 13 8 in force, 1 not yet in force, 5 proposed
The 14 laws behind MAP 5.1 and AIR-PREV-005

and 4 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 3 3 3 in force
The 3 laws behind MAP 5.1 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 3 3 3 in force
The 3 laws behind MAP 5.1 and AIR-PREV-024
AIR-DET-004AI System Observability 3 3 3 in force
The 3 laws behind MAP 5.1 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 3 3 3 in force
The 3 laws behind MAP 5.1 and AIR-DET-011
AIR-DET-021Agent Decision Audit and Explainability 3 3 3 in force
The 3 laws behind MAP 5.1 and AIR-DET-021
MEASURE 2.4The functionality and behavior of the AI system and its components – as identified in... AIR-PREV-005System Acceptance Testing 23 12 13 in force, 10 not yet in force
The 23 laws behind MEASURE 2.4 and AIR-PREV-005

and 13 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 23 12 13 in force, 10 not yet in force
The 23 laws behind MEASURE 2.4 and AIR-PREV-006

and 13 more, every one in the free file.

AIR-PREV-024Human-in-the-Loop Action Approval Gate 23 12 13 in force, 10 not yet in force
The 23 laws behind MEASURE 2.4 and AIR-PREV-024

and 13 more, every one in the free file.

AIR-DET-004AI System Observability 23 12 13 in force, 10 not yet in force
The 23 laws behind MEASURE 2.4 and AIR-DET-004

and 13 more, every one in the free file.

AIR-DET-011Human Feedback Loop for AI Systems 23 12 13 in force, 10 not yet in force
The 23 laws behind MEASURE 2.4 and AIR-DET-011

and 13 more, every one in the free file.

AIR-DET-021Agent Decision Audit and Explainability 23 12 13 in force, 10 not yet in force
The 23 laws behind MEASURE 2.4 and AIR-DET-021

and 13 more, every one in the free file.

MEASURE 2.5The AI system to be deployed is demonstrated to be valid and reliable. Limitations of... AIR-DET-021Agent Decision Audit and Explainability 2 2 2 in force
The 2 laws behind MEASURE 2.5 and AIR-DET-021
AIR-PREV-007Legal and Contractual Frameworks for AI Systems 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and AIR-PREV-007
AIR-PREV-008Quality of Service (QoS) and DDoS Prevention for AI Systems 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and AIR-PREV-008
AIR-PREV-012Role-Based Access Control for AI Data 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and AIR-PREV-012
AIR-PREV-014Encryption of AI Data at Rest 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and AIR-PREV-014
AIR-PREV-017AI Firewall Implementation and Management 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and AIR-PREV-017
AIR-PREV-020MCP Server Security Governance 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and AIR-PREV-020
AIR-DET-001AI Data Leakage Prevention and Detection 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and AIR-DET-001
MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... AIR-DET-021Agent Decision Audit and Explainability 3 3 1 in force, 1 not yet in force, 1 proposed
The 3 laws behind MEASURE 2.6 and AIR-DET-021
AIR-PREV-007Legal and Contractual Frameworks for AI Systems 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and AIR-PREV-007
AIR-PREV-008Quality of Service (QoS) and DDoS Prevention for AI Systems 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and AIR-PREV-008
AIR-PREV-012Role-Based Access Control for AI Data 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and AIR-PREV-012
AIR-PREV-014Encryption of AI Data at Rest 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and AIR-PREV-014
AIR-PREV-017AI Firewall Implementation and Management 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and AIR-PREV-017
AIR-PREV-020MCP Server Security Governance 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and AIR-PREV-020
AIR-DET-001AI Data Leakage Prevention and Detection 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and AIR-DET-001
AIR-DET-004AI System Observability 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.6 and AIR-DET-004
MEASURE 2.7AI system security and resilience – as identified in the MAP function – are evaluated... AIR-PREV-007Legal and Contractual Frameworks for AI Systems 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.7 and AIR-PREV-007
AIR-PREV-008Quality of Service (QoS) and DDoS Prevention for AI Systems 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.7 and AIR-PREV-008
AIR-PREV-012Role-Based Access Control for AI Data 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.7 and AIR-PREV-012
AIR-PREV-014Encryption of AI Data at Rest 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.7 and AIR-PREV-014
AIR-PREV-017AI Firewall Implementation and Management 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.7 and AIR-PREV-017
AIR-PREV-020MCP Server Security Governance 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.7 and AIR-PREV-020
AIR-DET-001AI Data Leakage Prevention and Detection 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.7 and AIR-DET-001
AIR-PREV-005System Acceptance Testing 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and AIR-PREV-024
AIR-DET-004AI System Observability 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and AIR-DET-011
AIR-DET-021Agent Decision Audit and Explainability 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and AIR-DET-021
MEASURE 2.8Risks associated with transparency and accountability – as identified in the MAP... AIR-DET-021Agent Decision Audit and Explainability 66 43 41 in force, 13 not yet in force, 12 proposed
The 66 laws behind MEASURE 2.8 and AIR-DET-021

and 56 more, every one in the free file.

AIR-PREV-005System Acceptance Testing 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.8 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.8 and AIR-PREV-006
MEASURE 2.9The AI model is explained, validated, and documented, and AI system output is... AIR-DET-021Agent Decision Audit and Explainability 17 14 10 in force, 6 not yet in force, 1 proposed
The 17 laws behind MEASURE 2.9 and AIR-DET-021

and 7 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 11 11 7 in force, 4 not yet in force
The 11 laws behind MEASURE 2.9 and AIR-PREV-006

and 1 more, every one in the free file.

AIR-PREV-005System Acceptance Testing 5 5 5 in force
The 5 laws behind MEASURE 2.9 and AIR-PREV-005
AIR-PREV-024Human-in-the-Loop Action Approval Gate 4 4 4 in force
The 4 laws behind MEASURE 2.9 and AIR-PREV-024
AIR-DET-004AI System Observability 4 4 4 in force
The 4 laws behind MEASURE 2.9 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 4 4 4 in force
The 4 laws behind MEASURE 2.9 and AIR-DET-011
MEASURE 2.10Privacy risk of the AI system – as identified in the MAP function – is examined and documented. AIR-PREV-005System Acceptance Testing 6 6 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.10 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.10 and AIR-PREV-006
AIR-DET-021Agent Decision Audit and Explainability 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.10 and AIR-DET-021
MEASURE 2.11Fairness and bias – as identified in the MAP function – are evaluated and results are... AIR-PREV-005System Acceptance Testing 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and AIR-PREV-024
AIR-DET-004AI System Observability 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and AIR-DET-004
AIR-DET-011Human Feedback Loop for AI Systems 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and AIR-DET-011
AIR-DET-021Agent Decision Audit and Explainability 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and AIR-DET-021
MEASURE 3.3Feedback processes for end users and impacted communities to report problems and... AIR-DET-021Agent Decision Audit and Explainability 21 21 10 in force, 4 not yet in force, 7 proposed
The 21 laws behind MEASURE 3.3 and AIR-DET-021

and 11 more, every one in the free file.

AIR-PREV-006Data Quality & Classification/Sensitivity 12 12 8 in force, 3 not yet in force, 1 proposed
The 12 laws behind MEASURE 3.3 and AIR-PREV-006

and 2 more, every one in the free file.

AIR-DET-004AI System Observability 3 3 3 in force
The 3 laws behind MEASURE 3.3 and AIR-DET-004
AIR-PREV-005System Acceptance Testing 2 2 2 in force
The 2 laws behind MEASURE 3.3 and AIR-PREV-005
AIR-PREV-024Human-in-the-Loop Action Approval Gate 2 2 2 in force
The 2 laws behind MEASURE 3.3 and AIR-PREV-024
AIR-DET-011Human Feedback Loop for AI Systems 2 2 2 in force
The 2 laws behind MEASURE 3.3 and AIR-DET-011
MANAGE 1.3Responses to the AI risks deemed high priority, as identified by the MAP function, are... AIR-PREV-005System Acceptance Testing 8 8 2 in force, 1 not yet in force, 5 proposed
The 8 laws behind MANAGE 1.3 and AIR-PREV-005
MANAGE 2.4Mechanisms are in place and applied, and responsibilities are assigned and understood,... AIR-DET-021Agent Decision Audit and Explainability 6 5 5 in force, 1 not yet in force
The 6 laws behind MANAGE 2.4 and AIR-DET-021
AIR-DET-004AI System Observability 5 4 4 in force, 1 not yet in force
The 5 laws behind MANAGE 2.4 and AIR-DET-004
AIR-PREV-005System Acceptance Testing 4 3 4 in force
The 4 laws behind MANAGE 2.4 and AIR-PREV-005
AIR-PREV-006Data Quality & Classification/Sensitivity 4 3 4 in force
The 4 laws behind MANAGE 2.4 and AIR-PREV-006
AIR-PREV-024Human-in-the-Loop Action Approval Gate 4 3 4 in force
The 4 laws behind MANAGE 2.4 and AIR-PREV-024
AIR-DET-011Human Feedback Loop for AI Systems 4 3 4 in force
The 4 laws behind MANAGE 2.4 and AIR-DET-011
MANAGE 4.1Post-deployment AI system monitoring plans are implemented, including mechanisms for... AIR-DET-004AI System Observability 7 6 6 in force, 1 not yet in force
The 7 laws behind MANAGE 4.1 and AIR-DET-004
AIR-DET-021Agent Decision Audit and Explainability 7 6 6 in force, 1 not yet in force
The 7 laws behind MANAGE 4.1 and AIR-DET-021
AIR-PREV-006Data Quality & Classification/Sensitivity 2 2 1 in force, 1 not yet in force
The 2 laws behind MANAGE 4.1 and AIR-PREV-006
MANAGE 4.3Incidents and errors are communicated to relevant AI actors, including affected... AIR-DET-004AI System Observability 9 7 5 in force, 3 not yet in force, 1 proposed
The 9 laws behind MANAGE 4.3 and AIR-DET-004
AIR-DET-021Agent Decision Audit and Explainability 8 6 4 in force, 3 not yet in force, 1 proposed
The 8 laws behind MANAGE 4.3 and AIR-DET-021
Not connected to the FINOS AIGF: 44 of NIST AI RMF's controls

Short of 2 laws

The same duties reach these and a FINOS AIGF control, in fewer than 2 of the laws we track.

No FINOS AIGF control on the same duties

Laws reach these, but no duty that reaches one of them also reaches a FINOS AIGF control.

  • GOVERN 1.2 The characteristics of trustworthy AI are integrated into organizational policies,..., 6 laws
  • GOVERN 1.7 Processes and procedures are in place for decommissioning and phasing out AI systems..., 1 law
  • GOVERN 2.2 The organization’s personnel and partners receive AI risk management training to..., 3 laws
  • GOVERN 5.1 Organizational policies and practices are in place to collect, consider, prioritize,..., 1 law
  • GOVERN 6.2 Contingency processes are in place to handle failures or incidents in third-party data..., 1 law
  • MAP 1.5 Organizational risk tolerances are determined and documented., 1 law
  • MEASURE 1.2 Appropriateness of AI metrics and effectiveness of existing controls are regularly..., 1 law
  • MEASURE 1.3 Internal experts who did not serve as front-line developers for the system and/or..., 10 laws
  • MEASURE 2.2 Evaluations involving human subjects meet applicable requirements (including human..., 1 law
  • MEASURE 2.3 AI system performance or assurance criteria are measured qualitatively or..., 6 laws
  • MEASURE 3.1 Approaches, personnel, and documentation are in place to regularly identify and track..., 2 laws
  • MANAGE 2.1 Resources required to manage AI risks are taken into account – along with viable..., 1 law
  • MANAGE 3.1 AI risks and benefits from third-party resources are regularly monitored, and risk..., 3 laws

No law we track reaches these

No duty in the laws we track reaches these controls.

  • GOVERN 3.1 Decision-making related to mapping, measuring, and managing AI risks throughout the...
  • GOVERN 5.2 Mechanisms are established to enable the team that developed or deployed AI systems to...
  • MAP 1.2 Interdisciplinary AI actors, competencies, skills, and capacities for establishing...
  • MAP 1.3 The organization’s mission and relevant goals for AI technology are understood and documented.
  • MAP 1.4 The business value or context of business use has been clearly defined or – in the...
  • MAP 2.1 The specific tasks and methods used to implement the tasks that the AI system will...
  • MAP 3.1 Potential benefits of intended AI system functionality and performance are examined...
  • MAP 3.2 Potential costs, including non-monetary costs, which result from expected or realized...
  • MAP 4.2 Internal risk controls for components of the AI system, including third-party AI...
  • MAP 5.2 Practices and personnel for supporting regular engagement with relevant AI actors and...
  • MEASURE 1.1 Approaches and metrics for measurement of AI risks enumerated during the MAP function...
  • MEASURE 2.12 Environmental impact and sustainability of AI model training and management activities...
  • MEASURE 2.13 Effectiveness of the employed TEVV metrics and processes in the MEASURE function are...
  • MEASURE 3.2 Risk tracking approaches are considered for settings where AI risks are difficult to...
  • MEASURE 4.1 Measurement approaches for identifying AI risks are connected to deployment context(s)...
  • MEASURE 4.2 Measurement results regarding AI system trustworthiness in deployment context(s) and...
  • MEASURE 4.3 Measurable performance improvements or declines based on consultations with relevant...
  • MANAGE 1.2 Treatment of documented AI risks is prioritized based on impact, likelihood, and...
  • MANAGE 1.4 Negative residual risks (defined as the sum of all unmitigated risks) to both...
  • MANAGE 2.2 Mechanisms are in place and applied to sustain the value of deployed AI systems.
  • MANAGE 3.2 Pre-trained models which are used for development are monitored as part of AI system...
  • MANAGE 4.2 Measurable activities for continual improvements are integrated into AI system updates...

Lines of the communications, age assurance and cybersecurity laws we track were not read against the NIST AI RMF, so none of them connects the two here (how each subject's lines were read).

How these connections are drawn

Each requirement line in the laws we track is read against the framework for its subject (the AI, scraping and news aggregation laws against the NIST AI RMF, the privacy, communications and age assurance laws against the NIST Privacy Framework, the cybersecurity laws against the NIST CSF 2.0); laws on liability and content moderation are not read against any framework yet. A line reaches the FINOS AIGF through a kind of duty its law carries, and only where that kind of duty also reaches, on that same line, the NIST framework for the line's own subject. Two controls connect when lines in at least 2 laws reach both. That says the same duties reach both; it does not say the two are alike, or that running either one does what a law asks.

A line placed on a control in the framework for its own subject, whose law carries a kind of duty that reaches another of the three frameworks read line by line, is read against that one as well: every such line, or only those whose wording reaches into it. For these two:

Laws onRead against the NIST AI RMF
privacysuch lines on automated decisions, profiling and AI
communicationsnot read
age assurancenot read
cybersecuritynot read

Every duty line in the AI, scraping, news aggregation and privacy laws we track has been read against the framework for its subject.

Sources and licenses

FINOS AI Governance Framework, copyright 2025 FINOS, licensed under CC BY 4.0. Titles and purpose text are quoted; markdown emphasis and links were removed.