How explainable, predictive decision making can help us trust our AI models
Daniele Zonca, Architect, Red Hat and Matteo Mortari, Principle Software Engineer, Red Hat
About this talk
In this webinar, you’ll hear about the latest research in eXplainable AI (XAI), an approach that combines AI/ML and traditional business rules to better understand the factors that contribute to an automated decision. We’ll introduce you to the latest standards for representing decision logic, and we’ll demonstrate an XAI solution built from open source components that will show how we can finally answer questions about why an automated decision was made.
Join this channel to learn best practices and insights on how to: containerize existing apps for increased cost efficiency, deliver new cloud-native and process-driven apps using microservice architectures, take an agile approach to integrate APIs and data, and do it all in a culture of collaboration using DevOps best practices.…