Program Overview
The MS in AI Ethics & Governance prepares professionals to navigate the complex intersection of artificial intelligence, society, and law. The program is deliberately interdisciplinary: students develop both technical literacy (enough to audit AI systems and evaluate technical claims) and deep knowledge of regulatory frameworks, fairness metrics, organizational risk management, and international AI policy.
Curriculum Highlights
- Technical Literacy: How AI systems work, common failure modes, interpretability tools, bias measurement
- Ethics & Philosophy: Value alignment, moral philosophy, AI rights and personhood, existential risk
- Regulation & Policy: EU AI Act, US Executive Orders, NIST AI RMF, sector-specific regulation (healthcare, finance, hiring)
- Organizational Practice: AI governance frameworks, algorithmic auditing, red-teaming, impact assessments
- International Dimensions: Comparative AI policy (US, EU, China, UK), standards bodies (ISO, IEEE)
The Tag1 Governance Case Study
The program includes a case study unit on how technology organizations embed AI governance into their operations, drawing on Tag1 Consulting's published work on the Drupal AI Initiative and responsible AI deployment practices.
Sample Courses
- ETH-401: Foundations of AI Ethics
- ETH-410: Algorithmic Fairness: Metrics and Mitigation
- ETH-420: AI Regulation: EU AI Act and Global Frameworks
- ETH-430: Interpretability and Algorithmic Auditing
- ETH-440: Organizational AI Governance
- ETH-450: International AI Policy
- ETH-490: Capstone: AI Impact Assessment