Ethics and Governance of Autonomous AI Agents Training Course

Foundations of Ethics in Autonomous Systems

• Defining autonomy within AI agents
• Applying major ethical theories to machine behavior
• Stakeholder perspectives and value-sensitive design

Societal Risks and High-Stakes Use Cases

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

Legal and Regulatory Environment

• Overview of AI legislation and policy trajectories (EU AI Act, NIST, OECD)
• Issues of accountability, liability, and legal personhood for AI agents
• Global governance initiatives and existing gaps

Explainability and Decision Transparency

• Challenges associated with 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 regulating agent behavior
• Control paradigms: human-in-the-loop vs. human-on-the-loop
• Shared responsibility among designers, users, and institutions

Ethical Risk Assessment and Mitigation

• Risk mapping and critical failure analysis in agent design
• Implementing safeguards and off-switch mechanisms
• Auditing for bias, discrimination, and fairness

Governance Design and Institutional Oversight

• Principles of responsible AI governance
• Multistakeholder oversight models and audit processes
• Building compliance frameworks for autonomous agents

Summary and Next Steps