Program 5 · Responsible AI Engineering

Status: not started

Building AI systems that are safe, fair, accountable, and aligned with human values. Expected topics include:

• The principles of responsible AI (fairness, accountability, transparency, privacy, safety, inclusiveness, reliability)
• Bias and fairness — sources, measurement, mitigation
• Explainability and interpretability techniques
• Model cards, data sheets, and system documentation
• Evaluation harnesses for safety and harm
• Governance of AI systems in production
• Regulatory landscape (EU AI Act, NIST AI RMF, sector-specific rules)
• Practical patterns for developers: guardrails, human-in-the-loop, red-teaming

Modules and submodules will be added as the program is started.

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Feeds from

• Program 4 — data protection and AI security are prerequisites for responsible AI.
• Program 1 — governance, policy, and compliance vocabulary applied to the AI-specific regulatory landscape.