Organizations who use AI need to ensure they do so in a socially responsible way. Learn how in this course.
Overview
Syllabus
Introduction
- Actionable steps to responsible AI
- Moving from principles to practice
- Introducing the Landon Hotel
- Connector: Start with context
- The AI legal landscape
- Understanding ethical AI risks
- Getting clear on organizational values and AI risks
- The AI ethics statement, policies, and metrics
- Documenting AI
- Procurement and Shadow AI
- Connector: From context to culture
- Tone at the top
- Existing roles
- The AI ethics committee
- Diversity and stakeholders
- Connector: From culture to content
- The big three: Privacy, bias, and explainability
- Addressing privacy, bias, and explainability in your AI program
- Data done right
- Document, document, document
- Environmental impacts
- A brief word about cybersecurity
- Connector: Moving to commitment
- Model drift and monitoring
- The role of independent audit
- Nurturing a responsible AI culture
- The journey of responsible AI
Taught by
Katrina Ingram