Map intended purpose: Which NIST AI RMF MAP conclusion is most | AIGP
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Map intended purpose: Which NIST AI RMF MAP conclusion is most appropriate?

AIGP Understanding How Laws, Standards and Frameworks Apply to AI Easy

MAP should clarify purpose, users, affected people, system limits, and foreseeable use beyond the intended itinerary function.

The question

A travel-support chatbot performs well for logged-in customers seeking itinerary information. Reviewers also find that users sometimes ask it to resolve visa eligibility questions, which the system was not designed to answer. Which NIST AI RMF MAP conclusion is most appropriate?

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  1. Map intended purpose, affected users, and foreseeable out-of-scope use. ✓
    MAP establishes context, intended purpose, users, affected people, system limits, and foreseeable use outside intended conditions.
  2. Certify the chatbot’s terminology before expanding its scope.
    Terminology alignment does not substitute for contextual analysis of intended purpose, users, limits, and foreseeable misuse.
  3. Manage the chatbot by accepting every customer request.
    MANAGE concerns risk treatment and deployment decisions; accepting unsupported requests ignores the contextual boundary identified by MAP.
  4. Measure accuracy only for itinerary questions.
    Accuracy testing may be useful, but it does not establish context, foreseeable out-of-scope use, or resulting risks.
The trap
When a system is used beyond its design purpose, first identify the changed context and system limits.

How to remember it

MAP should clarify purpose, users, affected people, system limits, and foreseeable use beyond the intended itinerary function.

How many of these would you get right?

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