Students master ethics and legal compliance in data/AI systems, embedding reliability, transparency, fairness, security, and democratic safeguards across data lifecycles and algorithmic design.

At the end of this module students know how to

• Apply GDPR principles and data lifecycle ethics to ensure legal compliance and privacy protection in AI systems 
• Detect and mitigate algorithmic bias using fairness metrics and technical tools
• Implement explainability techniques, understand applicability to different technologies and models and establish accountability frameworks for AI decisions
• Analyze and audit algorithmic amplification, social media manipulation, and threats to democratic processes
• Design ethical guardrails for agentic AI systems and conduct comprehensive ethical AI audits

Classes will be a mix of lectures, discussions, coding labs and deep dives/clinics for project support.

• 80% Projects
• 20% Participation