End-to-end measurement, grading and evaluation of pretrained artificial intelligence models via a graphical user interface (gui) systems and methods

Abstract

Systems and methods for measuring, grading, evaluating, and comparing AI models via a graphical user interface are disclosed. The technology obtains a set of application domains of the AI model in which an AI model will be used. The application domains are mapped to one or more guidelines to determine a set of guidelines that define operational boundaries of the AI model. The guidelines are used to generate assessment domains, each associated with specific benchmarks that include indicators of a degree of satisfaction with the guidelines. For each assessment domain, assessments are constructed to evaluate the AI model's degree of satisfaction with the corresponding guidelines. The AI model is then evaluated against the assessments. Based on these comparisons, grades are assigned to the AI model for each assessment domain. The application-domain-specific grades are generated and displayed at a GUI, reflecting the AI model's degree of satisfaction with the guidelines.