Explore the Responsible AI Dashboard, an open-source framework designed to help engineers build responsible and reliable AI products, in this 53-minute webinar. Learn how this tool integrates various open-source technologies for error analysis, interpretability, fairness, counterfactual analysis, and causal decision-making. Discover how to create customizable workflows and tailor RAI dashboards to fit specific scenarios, enabling seamless debugging experiences through interactive visualizations. Gain insights into identifying errors, inspecting data, generating model explanations, and exploring causal relationships. Understand the dashboard's role within the larger Responsible AI Toolbox and its importance in aligning AI tools and facilitating community extensions. Follow along with a house pricing prediction example to see practical applications of error analysis, counterfactual demos, and causal inference in action.
Responsible AI Dashboard - A Tool for Operationalizing Responsible AI
Overview
Syllabus
Introduction
Microsoft Responsible AI Principles
Challenges
Tools
Tools fragmentation
Debugging Machine Learning Models
House Pricing Prediction
Error Analysis
Model Statistics
Counterfactual Demo
Historical Data
Econ ML
causal inference demo
Summary
Collaboration
Counterfactual
Taught by
Open Data Science
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