AI Accountability Essential Training

Introduction

• Accountable artificial intelligence

1. The Context for AI

• The promise of AI
• General and narrow AI

2. Technical Challenges of AI

• The challenge of classification errors
• The causes of classification errors
• Bias in AI
• Supervised and unsupervised learning
• Biased labeling of data
• Construct validity
• Seeing the wrong thing
• The absence of meaning
• Vulnerability to attacks
• Attacking AI
• Protecting AI

3. Social Challenges of AI

• Dimensions of justice
• Justice and AI
• Moral reasoning
• Relational ethics
• Issues of authenticity

4. Legal Challenges of AI

• General Data Protection Regulation (GDPR)
• Spurious discrimination
• The right to explanation
• Discrimination in data
• Discrimination in implementation
• Liability
• Accountability laws

5. Safety Challenges of AI

• AI in life and death situations
• AI in the military
• The challenges of military AI

6. Confronting the Challenges of AI

• Strategies for developers
• Strategies for executives
• Strategies for public relations
• Strategies for regulators
• Strategies for consumers

Conclusion

• Next steps