This course focuses on incorporating ethics into AI/ML product development by discussing the key features of responsible AI at each stage of the lifecycle. It covers designing, developing, and deploying responsible AI systems, as well as using open-source assessment tools. The teaching method includes best practices sharing and tactical approaches. The intended audience includes AI/ML product teams and individuals interested in understanding and implementing responsible AI practices.
Building Responsible AI - Best Practices Across the Product Development Lifecycle
Overview
Syllabus
Introduction
Broadening our focus:Responsible AI
Principles to Practices- Operationalizing Responsible AI
Responsible AI considerations need to be integrated into the ML development lifecycle
Designing Responsible AI Systems
Developing Responsible AI Systems
Deploying Responsible AI Systems
Open Source Responsible AI Assessment tools
Demo
QnA
Taught by
Data Science Dojo
