PMI Cognitive Project Management For AI (CPMAI) Practice Test

Explainability for end-users in AI deployments refers to

Limiting user access Reducing data collection Increasing model opacity Providing understandable reasons for predictions to users

Correct Answer:

Providing understandable reasons for predictions to users

Explanation:

Explainability for end-users means providing clear, understandable reasons for predictions that users can interpret. This helps people see why a decision was made, what factors influenced it, and what they might do if they disagree, which in turn builds trust and enables accountability in the deployment. For example, if a loan application is denied, an end-user-facing explanation would describe that the decision was influenced by factors like credit score or income rather than presenting the result as a mysterious black box. It isn’t about restricting access or collecting less data, and it isn’t about making the model harder to understand; it’s about communicating the reasoning in plain language so users can comprehend and respond appropriately.

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