Law / Frameworks / Crosswalk / NIST AI RMF to NIST AI 200-2

The NIST AI Risk Management Framework, mapped to the NIST TEVV-Athlon Framework for Evaluating AI Systems

20 of NIST AI RMF's controls connect to 4 of NIST AI 200-2's through 88 laws in 40 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
NIST TEVV-Athlon Framework for Evaluating AI Systems, initial public draft, August 2026 (NIST AI 200-2 ipd), National Institute of Standards and Technology
See also
NIST AI 200-2 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--nist-ai-200-2.csv · nist-ai-rmf--nist-ai-200-2.json

NIST AI RMFNIST AI 200-2LawsJurisdictionsWhere the laws stand
GOVERN 1.1Legal and regulatory requirements involving AI are understood, managed, and documented. 2.3Apply & Measure 38 20 28 in force, 9 not yet in force, 1 proposed
The 38 laws behind GOVERN 1.1 and 2.3

and 28 more, every one in the free file.

4.3Composing a TEVV Toolbox 38 20 28 in force, 9 not yet in force, 1 proposed
The 38 laws behind GOVERN 1.1 and 4.3

and 28 more, every one in the free file.

GOVERN 1.4The risk management process and its outcomes are established through transparent... 2.3Apply & Measure 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and 2.3

and 7 more, every one in the free file.

4.3Composing a TEVV Toolbox 17 12 11 in force, 6 not yet in force
The 17 laws behind GOVERN 1.4 and 4.3

and 7 more, every one in the free file.

GOVERN 1.6Mechanisms are in place to inventory AI systems and are resourced according to... 2.3Apply & Measure 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and 2.3
4.3Composing a TEVV Toolbox 7 6 6 in force, 1 not yet in force
The 7 laws behind GOVERN 1.6 and 4.3
GOVERN 2.1Roles and responsibilities and lines of communication related to mapping, measuring,... 2.3Apply & Measure 7 6 7 in force
The 7 laws behind GOVERN 2.1 and 2.3
4.3Composing a TEVV Toolbox 7 6 7 in force
The 7 laws behind GOVERN 2.1 and 4.3
GOVERN 2.3Executive leadership of the organization takes responsibility for decisions about... 2.3Apply & Measure 4 4 4 in force
The 4 laws behind GOVERN 2.3 and 2.3
4.3Composing a TEVV Toolbox 4 4 4 in force
The 4 laws behind GOVERN 2.3 and 4.3
MAP 2.3Scientific integrity and TEVV considerations are identified and documented, including... 2.3Apply & Measure 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and 2.3

and 2 more, every one in the free file.

4.3Composing a TEVV Toolbox 12 9 8 in force, 4 not yet in force
The 12 laws behind MAP 2.3 and 4.3

and 2 more, every one in the free file.

MAP 3.3Targeted application scope is specified and documented based on the system’s... 4.3Composing a TEVV Toolbox 4 3 4 in force
The 4 laws behind MAP 3.3 and 4.3
2.3Apply & Measure 3 2 3 in force
The 3 laws behind MAP 3.3 and 2.3
MAP 3.5Processes for human oversight are defined, assessed, and documented in accordance with... 2.3Apply & Measure 25 18 17 in force, 8 not yet in force
The 25 laws behind MAP 3.5 and 2.3

and 15 more, every one in the free file.

4.3Composing a TEVV Toolbox 25 18 17 in force, 8 not yet in force
The 25 laws behind MAP 3.5 and 4.3

and 15 more, every one in the free file.

MAP 5.1Likelihood and magnitude of each identified impact (both potentially beneficial and... 2.4Synthesize & Interrogate 9 8 3 in force, 1 not yet in force, 5 proposed
The 9 laws behind MAP 5.1 and 2.4
2.3Apply & Measure 3 3 3 in force
The 3 laws behind MAP 5.1 and 2.3
4.3Composing a TEVV Toolbox 3 3 3 in force
The 3 laws behind MAP 5.1 and 4.3
MEASURE 2.4The functionality and behavior of the AI system and its components – as identified in... 2.3Apply & Measure 22 11 12 in force, 10 not yet in force
The 22 laws behind MEASURE 2.4 and 2.3

and 12 more, every one in the free file.

4.3Composing a TEVV Toolbox 22 11 12 in force, 10 not yet in force
The 22 laws behind MEASURE 2.4 and 4.3

and 12 more, every one in the free file.

MEASURE 2.5The AI system to be deployed is demonstrated to be valid and reliable. Limitations of... 4.3Composing a TEVV Toolbox 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.5 and 4.3
2.2Define & Construct 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.5 and 2.2
MEASURE 2.6The AI system is evaluated regularly for safety risks – as identified in the MAP... 2.2Define & Construct 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and 2.2
4.3Composing a TEVV Toolbox 3 2 2 in force, 1 not yet in force
The 3 laws behind MEASURE 2.6 and 4.3
MEASURE 2.7AI system security and resilience – as identified in the MAP function – are evaluated... 4.3Composing a TEVV Toolbox 4 3 2 in force, 2 not yet in force
The 4 laws behind MEASURE 2.7 and 4.3
2.3Apply & Measure 2 2 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and 2.3
2.2Define & Construct 2 1 1 in force, 1 not yet in force
The 2 laws behind MEASURE 2.7 and 2.2
MEASURE 2.9The AI model is explained, validated, and documented, and AI system output is... 2.3Apply & Measure 4 4 4 in force
The 4 laws behind MEASURE 2.9 and 2.3
4.3Composing a TEVV Toolbox 4 4 4 in force
The 4 laws behind MEASURE 2.9 and 4.3
MEASURE 2.10Privacy risk of the AI system – as identified in the MAP function – is examined and documented. 2.4Synthesize & Interrogate 4 4 3 in force, 1 not yet in force
The 4 laws behind MEASURE 2.10 and 2.4
MEASURE 2.11Fairness and bias – as identified in the MAP function – are evaluated and results are... 2.3Apply & Measure 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and 2.3
4.3Composing a TEVV Toolbox 6 5 4 in force, 2 not yet in force
The 6 laws behind MEASURE 2.11 and 4.3
MEASURE 3.3Feedback processes for end users and impacted communities to report problems and... 2.3Apply & Measure 2 2 2 in force
The 2 laws behind MEASURE 3.3 and 2.3
4.3Composing a TEVV Toolbox 2 2 2 in force
The 2 laws behind MEASURE 3.3 and 4.3
MANAGE 1.1A determination is made as to whether the AI system achieves its intended purposes and... 4.3Composing a TEVV Toolbox 2 1 1 in force, 1 not yet in force
The 2 laws behind MANAGE 1.1 and 4.3
MANAGE 1.3Responses to the AI risks deemed high priority, as identified by the MAP function, are... 2.4Synthesize & Interrogate 5 5 5 proposed
The 5 laws behind MANAGE 1.3 and 2.4
MANAGE 2.4Mechanisms are in place and applied, and responsibilities are assigned and understood,... 2.3Apply & Measure 4 3 4 in force
The 4 laws behind MANAGE 2.4 and 2.3
4.3Composing a TEVV Toolbox 4 3 4 in force
The 4 laws behind MANAGE 2.4 and 4.3
Not connected to the NIST AI 200-2: 52 of NIST AI RMF's controls

Short of 2 laws

The same duties reach these and a NIST AI 200-2 step, in fewer than 2 of the laws we track.

No NIST AI 200-2 step on the same duties

Laws reach these, but no duty that reaches one of them also reaches a NIST AI 200-2 step.

  • 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 3.2 Policies and procedures are in place to define and differentiate roles and..., 5 laws
  • GOVERN 4.1 Organizational policies and practices are in place to foster a critical thinking and..., 3 laws
  • GOVERN 4.3 Organizational practices are in place to enable AI testing, identification of..., 3 laws
  • GOVERN 5.1 Organizational policies and practices are in place to collect, consider, prioritize,..., 1 law
  • GOVERN 6.1 Policies and procedures are in place that address AI risks associated with third-party..., 14 laws
  • 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 2.3 Procedures are followed to respond to and recover from a previously unknown risk when..., 1 law
  • MANAGE 3.1 AI risks and benefits from third-party resources are regularly monitored, and risk..., 3 laws
  • MANAGE 4.3 Incidents and errors are communicated to relevant AI actors, including affected..., 17 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...

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 NIST AI 200-2 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.

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