Ethics and Governance of Autonomous AI Agents Training Course

Foundations of Ethics in Autonomous Systems

• Defining autonomy within AI agents
• Application of key ethical theories to machine behavior
• Stakeholder perspectives and value-sensitive design

Societal Risks and High-Stakes Use Cases

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

Legal and Regulatory Landscape

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

Explainability and Decision Transparency

• Challenges posed by black-box autonomous decision making
• Designing agents for explainability and auditability
• Transparency tools and frameworks (e.g., model cards, datasheets)

Alignment, Control, and Moral Responsibility

• AI alignment strategies for managing 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
• Implementation of safeguards and off-switch mechanisms
• Auditing for bias, discrimination, and fairness

Governance Design and Institutional Oversight

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

Summary and Next Steps