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?
