Building a Responsible AI Program: Context, Culture, Content, and Commitment

Introduction

• Actionable steps to responsible AI
• Moving from principles to practice
• Introducing the Landon Hotel

1. Context: Law, Ethics, and AI Risk

• 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

2. Context: AI in Your Organization

• Documenting AI
• Procurement and Shadow AI

3. Culture: Establishing Governance Structures

• Connector: From context to culture
• Tone at the top
• Existing roles
• The AI ethics committee
• Diversity and stakeholders

4. Content: Managing Data and AI Models

• 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

5. Commitment

• Connector: Moving to commitment
• Model drift and monitoring
• The role of independent audit
• Nurturing a responsible AI culture

Conclusion

• The journey of responsible AI