System-Level Transparency of Machine Learning

February 22, 2022


Specialized documentation techniques have been developed to communicate key facts about machine-learning (ML) systems and the datasets and models they rely on. Techniques such as Datasheets, FactSheets, and Model Cards began the journey towards model documentation that provides ML explainability and transparency. Our proposal, called System Cards, aims to increase the transparency of ML systems by providing stakeholders with an overview of different components of an ML system, how these components interact, and how different pieces of data and protected information are used by the system.

Download the Paper


Written by

Bilal Alsallakh

Adeel Cheema

Chavez Procope

David Adkins

Emily McReynolds

Erin Wang

Grace Pehl

Nekesha Green

Polina Zvyagina


Meta AI

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.