MAP 3.3 - AI Application Scope

NIST AI RMF (in the playbook companion) states:

MAP 3.3

Targeted application scope is specified, narrowed, and documented based on established context and AI system classification.

About

Systems that function in a narrow scope tend to enable better mapping, measurement, and management of risks in the learning or decision-making tasks and the system context. A narrow application scope also helps ease oversight functions and related resources within an organization.

For example, open-ended chatbot systems that interact with the public on the internet have a large number of risks that may be difficult to map, measure, and manage due to the variability from both the decision-making task and the operational context. Instead, a task-specific chatbot utilizing templated responses that follow a defined “user journey” is a scope that can be more easily mapped, measured and managed.

Actions

• Consider narrowing contexts for system deployment, including factors related to:

  • How outcomes may directly or indirectly impact users and stakeholders.

  • Length of time the system is deployed in between re-trainings.

  • Geographical regions in which the system operates.

• Engage AI actors from legal and procurement functions when specifying target application scope.

Transparency and Documentation

Organizations can document the following:

• To what extent has the entity clearly defined technical specifications and requirements for the AI system?

• How do the technical specifications and requirements align with the AI system’s goals and objectives?