Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Foundations of Ethics in Autonomous Systems
- Defining the concept of autonomy within AI agents.
- Applying key ethical theories to machine behavior.
- Considering stakeholder perspectives and value-sensitive design.
Societal Risks and High-Stakes Applications
- Deployment of autonomous agents in public safety, healthcare, and defense.
- Collaboration between humans and AI, and establishing trust boundaries.
- Scenarios involving unintended consequences and the amplification of risks.
Legal and Regulatory Environment
- Overview of AI legislation and policy trends (including the EU AI Act, NIST, and OECD).
- Accountability, liability, and the legal personhood of AI agents.
- Global governance initiatives and existing gaps.
Explainability and Decision-Making Transparency
- Challenges presented by black-box autonomous decision-making.
- Designing agents that are explainable and auditable.
- Tools and frameworks for transparency (such as model cards and datasheets).
Alignment, Control, and Moral Accountability
- Strategies for aligning AI behavior.
- Control paradigms: human-in-the-loop vs. human-on-the-loop.
- Distributing 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 underlying responsible AI governance.
- Multi-stakeholder oversight models and audit processes.
- Creating compliance frameworks for autonomous agents.
Summary and Future Directions
Requirements
- A solid grasp of AI systems and machine learning fundamentals.
- Proficiency in understanding autonomous agents and their practical applications.
- Acquainted with ethical and legal frameworks within technology policy.
Target Audience
- AI ethicists
- Policy makers and regulators
- Senior AI practitioners and researchers
