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LinkedIn Learning

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

via LinkedIn Learning

Overview

Organizations who use AI need to ensure they do so in a socially responsible way. Learn how in this course.

Syllabus

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

Taught by

Katrina Ingram

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4.6 rating at LinkedIn Learning based on 112 ratings

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