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Course Outline

Core Ethical Principles in Autonomous Systems

  • Establishing the definition of autonomy in AI agents
  • Applying major ethical theories to machine conduct
  • Considering stakeholder viewpoints and value-sensitive design

Societal Impacts and Critical Application Scenarios

  • Deployment of autonomous agents in public safety, healthcare, and defense
  • Defining trust boundaries in human-AI collaboration
  • Exploring scenarios of unintended outcomes and risk escalation

Regulatory and Legal Context

  • Surveying AI legislative developments and policy trends (EU AI Act, NIST, OECD)
  • Discussing accountability, liability, and the concept of legal personhood for AI agents
  • Reviewing global governance efforts and existing gaps

Decision Transparency and Explainability

  • Navigating the challenges of opaque, black-box autonomous decisions
  • Creating agents that are auditable and explainable
  • Utilizing transparency tools and frameworks (e.g., model cards, datasheets)

Control, Alignment, and Moral Accountability

  • Strategies for aligning AI agent behavior
  • Comparing human-in-the-loop and human-on-the-loop control models
  • Distributing responsibility among designers, users, and institutions

Ethical Risk Management and Mitigation

  • Conducting risk mapping and critical failure analysis in agent architecture
  • Implementing safeguards and override mechanisms
  • Auditing for bias, discrimination, and fairness

Structuring Governance and Institutional Supervision

  • Core principles of responsible AI governance
  • Multistakeholder oversight structures and auditing processes
  • Developing compliance frameworks specific to autonomous agents

Conclusion and Future Directions

Requirements

  • Foundational grasp of AI systems and machine learning principles
  • Working knowledge of autonomous agents and their practical applications
  • Proficiency in ethical and legal structures related to technology policy

Target Audience

  • AI ethicists
  • Policy officials and regulators
  • Senior AI practitioners and researchers
 14 Hours

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