MAP-5.1 Likelihood and magnitude of each identified impact (both potentially beneficial and harmful) based on expected use, past uses of AI systems in similar contexts, public incident reports, feedback from those external to the team that developed or deployed the AI system, or other data are identified and documented.

NIST AI Risk Management Framework 1.0 · 1.0

NIST AI Risk Management Framework 1.0 states this control in a single sentence, which is the title above — reproduced verbatim from NIST AI Risk Management Framework (AI RMF 1.0).

Maps to 2 controls in 2 other frameworks

Framework	Control
ISO/IEC 42001:2023	A.5.4 Assessing AI-System Impact on Individuals or Groups
NIST Cybersecurity Framework 2.0	ID.RA-04 Potential impacts and likelihoods of threats exploiting vulnerabilities are identified and recorded

Mappings are CMDash’s own, seeded with the product and shown on both frameworks they connect. In the product they mean evidence you attach here also counts against the controls listed above.

Integrations that carry evidence for this family

GitHub Advanced Security

Vulnerabilities

These connectors produce data relevant to NIST AI Risk Management Framework 1.0’s MAP family, which is the granularity CMDash publishes — there is no pre-built per-control mapping, and claiming one would be inventing it. You decide which evidence answers which control.

Track MAP-5.1 with evidence behind it

In CMDash this control is a row with an owner, a status, uploaded evidence kept with its full history, and an export an assessor can read.

Start free trial All NIST AI Risk Management Framework 1.0 controls