EvidenceDemonstrated real incidentv1.22.1
In plain English
This page shows what kind of support exists for each claim: real systems, experiments, early evidence, architectural reasoning, open questions, or speculative scenarios.
- Why this matters: AI risk can come from the whole arrangement, not one obvious model.
- What to look for: data, memory, routes, adapters, tools, evaluators, updates, and rollback paths.
- Technical version below: the expert terminology remains available and is linked through the glossary.
Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile
Evidence card
- Claim
- Generative AI risk management recognizes value-chain and component-integration concerns.
- Evidence level
- Demonstrated
- Source
- https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence
- Publication date
- 2024-07-26
- Authors or institution
- National Institute of Standards and Technology
- System tested
- Cross-sector GenAI risk profile; not a deployment study.
- Limitations
- Provides risk-management actions, not a proof of safety for adaptive systems.
- What the evidence does show
- Generative AI risk management recognizes value-chain and component-integration concerns.
- What the evidence does not show
- That existing profiles fully cover dynamic adapter/router/memory succession.
- Date last reviewed in UTC
- 2026-06-26T00:00:00Z
Site use
This source supports Cognivirus.com pages related to generative AI risk, value chain, component integration, information security. Its role is bounded by the limitations listed above.