Patra ModelCards: AI/ML Accountability in the Edge-Cloud Continuum

This paper introduces a framework for Model Cards, Patra ModelCards, that embeds model cards in the edge-cloud continuum for semi-automated information capture with the objective of greater trustworthiness and accountability for AI/ML models. Information captured includes fairness, explainability, and behavior of a model in different deployed environments. Our evaluation is of the framework’s claim of greater accountability. We evaluate the use of embedded vectors and similarity analysis to distinguish between deployed models that are duplicates of each other from those that represent a revision of an earlier developed model. The evaluation shows promising outcomes and good performance.