Interdisciplinary Education
The challenges posed by artificial intelligence span multiple domains, from societal and environmental to technological, geopolitical, and economic. Our educational initiative aims to develop well-rounded professionals who can navigate these interconnected and intersecting challenges through:
- Integrating diverse knowledge domains to develop AI systems that are more intelligent, adaptable, and universally beneficial.
- Understanding technical challenges through varied lenses: cultural, philosophical, economic, and historical.
- Building collaborative competency by equipping technologists with the shared vocabulary and interdisciplinary understanding needed to work effectively with social scientists, legal experts, and business leaders.
Interdisciplinary MS in AI Safety
Glenn Renwick challenged us to educate students who can provide answers to the pressing ethical questions facing AI today. To meet this challenge, we are developing the first interdisciplinary Master’s program in AI Safety: a two-year degree designed to bridge technical expertise with ethical reasoning and policy literacy.

- Certificate 1 (Socio-Technical Systems) examines the ethics of emerging technologies, equipping future technology leaders to understand AI as deeply intertwined with social, political, and environmental contexts.
- Certificate 2 (Safe AI) addresses the technical and philosophical foundations of AI safety, from risk assessment to building provably safe systems.
- Certificate 3 (AI Governance) prepares students at three different levels of governance: organizational, national and global.
The program culminates in a capstone project developed in partnership with industry, giving students hands-on experience translating principles into practice. Beyond the graduate program, we are also developing undergraduate courses and secondary education resources to build a pipeline of ethically informed AI practitioners at every level.

Interdisciplinary Research
Developing safe and beneficial AI demands collaboration across disciplines and sectors. While high-level ethical principles provide essential guidance, we recognize that ethical challenges must be understood within their specific, local contexts.
In partnership with industry and nonprofit organizations, we focus on four core research areas:
- Information Integrity: How do we maintain trust in our information ecosystems? What tools and educational approaches can preserve institutional credibility and help the public evaluate information quality?
- AI Alignment and Safety: How do we ensure that AI systems and agents behave in predictable, interpretable, and transparent ways?
- Global Ethics: How do we develop culturally intelligent and socially grounded AI experiences that serve diverse communities? What are different conceptual differences to data rights?
- AI Governance and Accountability: What research is needed to support regulatory frameworks and ethical standards that protect individuals from harm and preserve human autonomy?
Distinguished Speakers Series: AI Ethics in Practice
The Engineering Leadership Institute’s graduate course “AI Ethics for Technology Leaders” (ENG6933) equips future technology leaders with a comprehensive understanding of critical ethical considerations in AI development and deployment.
During the Fall 2024 and Spring 2025 semesters, students heard from leading industry experts, ethicists, and researchers who shared valuable insights on navigating the complex ethical landscape of artificial intelligence. Below is a curated selection of recorded guest lectures, providing diverse perspectives on pressing ethical challenges in AI.

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