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Duration 14 hours
Course Outline
Core Ethical Principles in Autonomous Systems
- Defining the scope of autonomy in AI agents
- Application of major ethical theories to machine behavior
- Stakeholder insights and value-sensitive design approaches
Societal Implications and Critical Use Cases
- Deploying autonomous agents in public safety, health, and defense
- Defining trust boundaries in Human-AI collaboration
- Analyzing scenarios involving unintended consequences and risk escalation
The Legal and Regulatory Environment
- Overview of AI legislation and policy developments (EU AI Act, NIST, OECD)
- Issues of accountability, liability, and legal status of AI agents
- Global governance initiatives and existing regulatory gaps
Explainability and Transparency in Decision-Making
- Overcoming challenges posed by opaque, black-box autonomous decisions
- Designing agents that are explainable and subject to audit
- Leveraging transparency tools and frameworks (e.g., model cards, datasheets)
Alignment, Control, and Moral Accountability
- Strategies for aligning AI behavior with intended outcomes
- Comparing human-in-the-loop versus human-on-the-loop control models
- Distributing responsibility among designers, end-users, and institutions
Ethical Risk Evaluation and Mitigation Strategies
- Mapping risks and analyzing critical failures in agent architecture
- Implementing safeguards and emergency shutdown mechanisms
- Auditing for bias, discrimination, and fairness
Governance Architecture and Institutional Supervision
- Key principles of responsible AI governance
- Multistakeholder oversight models and auditing procedures
- Developing compliance frameworks specific to autonomous agents
Conclusion and Strategic Next Steps
Requirements
- A solid grasp of AI systems and fundamental machine learning concepts
- Acquaintance with autonomous agents and their practical applications
- Knowledge of ethical and legal frameworks governing technology policy
Target Audience
- AI ethicists
- Policy makers and regulatory authorities
- Senior AI practitioners and researchers
