The Collaboration

The Trustworthy and Robust AI collaboration (TRAC) between MIT CSAIL and Microsoft Research is working towards fostering advances on robustness and trustworthy AI, which spans safety & reliability, intelligibility, and accountability. The collaboration seeks to address concerns about the trustworthiness of AI systems, including rising concerns with the safety, fairness, and transparency of technologies.

“By quantifying uncertainty, we’re getting closer to designing the novel transparent systems that can function in high-stakes environments. Our goal here is to create a principled approach for robust machine learning – in theory and practice.” – Daniela Rus, MIT CSAIL Director

The collaboration leverages the mutual interests of Microsoft and MIT CSAIL on achieving AI systems in both the autonomous, semi-autonomous, and collaborative realms, but centered on the vision of extending and augment the abilities and intellect of people.

“We’re excited about bringing together leading intellects at MIT CSAIL and Microsoft Research to collaborate on intriguing and important opportunities ahead — and to develop trustworthy AI systems that are safe, reliable, understandable, and fair.” – Eric Horvitz, MSR Labs Director

Program Committee

Eric Horvitz, Technical Fellow and Director, Microsoft Research

Eric Horvitz Technical Fellow and Director, Microsoft Research

Aleksander Madry, Professor, MIT CSAIL

Aleksander Madry Professor and TRAC Faculty Lead, MIT CSAIL

Daniela Rus, Director, MIT CSAIL

Daniela Rus Director, MIT CSAIL

Evelyne Viegas, Senior Director – Research Engagement, Microsoft Research

Evelyne Viegas Senior Director – Research Engagement, Microsoft Research