Proficiency Dashboard System

A computer-implemented method comprising:

• logging user actions and task outcomes during operation of an AI model;
• selecting training-relevant interactions;
• incrementally updating the AI model with the selected interactions to form successive versions;
• evaluating each version on predefined tasks and computing a proficiency score relative to a human benchmark;
• storing each proficiency score in association with a corresponding version identifier and timestamp;
• and displaying, via a dashboard, a current proficiency score and a historical trend across versions together with interactive simulation of user-specified scenarios.

A proficiency monitoring system for an AI model, comprising:

• an evaluation module configured to administer predefined tasks to the AI model and to generate performance data;
• a data repository configured to store performance data and task-level proficiency metrics keyed to a version identifier;
• a dashboard interface module configured to display the proficiency metrics;
• and a version comparison component configured to present a comparative visualization of proficiency metrics for at least two versions of the AI model.

A method for monitoring proficiency of an AI model, comprising:

• providing predefined tasks to the AI model;
• evaluating model outputs to compute task-level results;
• computing proficiency metrics from the results;
• storing the metrics in a repository keyed to a version identifier;
• and generating a dashboard display that presents the proficiency metrics.

A non-transitory computer-readable medium storing instructions that, when executed, cause processors to:

• administer predefined tasks;
• record performance results;
• calculate task-level proficiency metrics;
• store the metrics keyed to a version identifier;
• and generate a dashboard interface displaying the metrics.