Explore best practices for building responsible AI systems across the product development lifecycle in this 44-minute talk. Learn how to operationalize abstract concepts like fairness into concrete assessment plans, and discover key features of responsible AI to evaluate at each stage of development. Gain insights on organizational processes supporting ethical AI systems, with a focus on fairness as an exemplar. Follow along as the speaker shares tactical approaches and demonstrates open-source assessment tools, concluding with a Q&A session. Enhance your understanding of integrating responsible AI considerations into machine learning development for more ethical and effective AI products.
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
