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Duration 14 hours (2 days)
Course Outline
Core Ethical Principles in Autonomous Systems
- Establishing a definition of autonomy within AI agents
- Applying major ethical theories to machine behavior
- Incorporating stakeholder perspectives and value-sensitive design
Societal Impact and High-Stakes Applications
- Role of autonomous agents in public safety, healthcare, and defense
- Defining trust boundaries in human-AI collaboration
- Managing scenarios of unintended consequences and risk escalation
The Legal and Regulatory Environment
- Overview of global AI legislation and policy trends (including the EU AI Act, NIST, and OECD guidelines)
- Navigating accountability, liability, and the concept of legal personhood for AI
- Identifying gaps in current global governance initiatives
Explainability and Decision-Making Transparency
- Addressing challenges associated with black-box autonomous decisions
- Designing agents that are both explainable and auditable
- Leveraging transparency tools and frameworks (such as model cards and datasheets)
Alignment, Control, and Moral Duty
- Implementing AI alignment strategies for agent behavior
- Comparing human-in-the-loop versus human-on-the-loop control models
- Distributing responsibility among designers, users, and institutions
Conducting Ethical Risk Assessments and Mitigation
- Performing risk mapping and critical failure analysis in agent design
- Establishing safeguards and off-switch mechanisms
- Auditing for bias, discrimination, and fairness
Governance Architecture and Institutional Supervision
- Upholding principles of responsible AI governance
- Implementing multistakeholder oversight models and audit processes
- Constructing compliance frameworks specifically for autonomous agents
Conclusion and Future Directions
Requirements
- A solid grasp of AI systems and foundational machine learning concepts.
- Proficiency with autonomous agents and an understanding of their practical applications.
- Acquaintance with ethical and legal frameworks shaping technology policy.
Target Audience
- AI Ethics Specialists
- Policy Makers and Regulatory Bodies
- Senior AI Practitioners and Research Scientists
