Ethics and Governance of Autonomous AI Agents Training Course

Foundations of Ethics in Autonomous Systems

• Defining autonomy in AI agents
• Key ethical theories applied to machine behavior
• Stakeholder perspectives and value-sensitive design

Societal Risks and High-Stakes Use Cases

• Autonomous agents in public safety, health, and defense
• Human-AI collaboration and trust boundaries
• Scenarios of unintended consequences and risk amplification

Legal and Regulatory Landscape

• Overview of AI legislation and policy trends (EU AI Act, NIST, OECD)
• Accountability, liability, and legal personhood of AI agents
• Global governance initiatives and gaps

Explainability and Decision Transparency

• Challenges of black-box autonomous decision making
• Designing for explainable and auditable agents
• Transparency tools and frameworks (e.g., model cards, datasheets)

Alignment, Control, and Moral Responsibility

• AI alignment strategies for agent behavior
• Human-in-the-loop vs. human-on-the-loop control paradigms
• Shared responsibility between designers, users, and institutions

Ethical Risk Assessment and Mitigation

• Risk mapping and critical failure analysis in agent design
• Safeguards and off-switch mechanisms
• Bias, discrimination, and fairness auditing

Governance Design and Institutional Oversight

• Principles of responsible AI governance
• Multistakeholder oversight models and audits
• Designing compliance frameworks for autonomous agents

Summary and Next Steps