Responsible AI Dashboard: A Tool for Operationalizing Responsible AI

Spread awareness of open source languages and tools within the data science and data-centric community.



As Artificial Intelligence is becoming part of user-facing applications and directly impacting society, deploying AI reliably and responsibly has become a priority for Microsoft and several other industry leaders. Rigorous model evaluation and debugging and responsible decision-making are at the heart of responsible machine learning development and deployment. 

The Responsible AI Dashboard is an open-source framework for helping engineers to build excellent products that are responsible and reliable. It provides a single pane of glass that integrates together ideas and technology from several open-source tools in the areas of error analysis (Error Analysis), interpretability (InterpretML),  fairness (Fairlearn)counterfactual analysis (DiCE), and causal decision making (EconML).

The main goal is to further accelerate engineering processes in machine learning by enabling practitioners to design customizable workflows and tailor RAI dashboards that best fit with their scenario. Through the tool engineers can create end to end and fluid debugging experiences and are able to navigate seamlessly through error identification and diagnosis by using interactive visualizations that identify errors, inspect the data, generate global and local explanations models, and potentially inspect problematic examples. They can also customize the dashboard and use it to explore causal relationships in the data and take informed decisions in the real world. The dashboard is a central part the Responsible AI Toolbox, a larger open-source effort at Microsoft for aligning together Responsible AI tools and facilitating future tooling extensions from the data science community. 

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Dec 21 2021


1:00 pm - 2:00 pm