Technology for Responsible AI
Faculty
- Courant Institute School of Mathematics, Computing, and Data Science: Emily Black, Gautam Kamath (2026), Daniel Neill, Julia Stoyanovich;
- Robert F. Wagner Graduate School of Public Service: Daniel Neill;
- Tandon School of Engineering: Emily Black, Julia Stoyanovich;
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Center for Responsible AI
Our goal is to build a future in which responsible AI is synonymous with AI. Our work centers around interdisciplinary research, technology policy, and education and training for AI practitioners, decision makers, and the public at large.
What is responsible AI? We use this term to refer to making the design, development and use of AI socially sustainable: using technology for good while controlling the risks. Responsible AI is about respecting human values, ensuring fairness, maintaining transparency, and upholding accountability. It’s about taking hype and magical thinking out of the conversation about AI. And about giving people the ability to understand, control and take responsibility for AI-assisted decisions.
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Computational Intelligence, Learning, Vision, and Robotics (CILVR)
The CILVR Lab (Computational Intelligence, Learning, Vision, and Robotics) regroups faculty members, research scientists, postdocs, and students working on AI, machine learning, and a wide variety of applications, notably computer perception, natural language understanding, robotics, and healthcare.
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Machine Learning for Good
Our lab is focused on development of novel machine learning methods for addressing critical urban problems. By creating, deploying, and evaluating new methods in collaboration with public sector partners, we hope both to advance the state of the art in machine learning and to improve the quality of public health, safety, and security.
