I am a principal researcher at the Adaptive Systems and Interaction Group at Microsoft Research. I earned my PhD in computer science from Harvard University where I was advised by Prof. Barbara Grosz. My research spans several subfields of AI, including planning, machine learning, multi-agent systems and human-computer teamwork, and is inspired by real-world applications that can benefit from the complementary abilities of people and AI. I am particularly interested in the impact of AI on society and developing AI systems that are reliable, unbiased, and trustworthy.
You can find information about my research and recent publications on my personal website.
Episode 9, January 24, 2018-
As the reality of artificial intelligence continues to capture our imagination, and critical AI systems enter our world at a rapid pace, Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research, is working to help us understand AI’s far-reaching implications, both as we use it, and as we build it.
Today, Dr. Kamar talks about the complementarity between humans and machines, debunks some common misperceptions about AI, reveals how we can overcome bias and blind spots by putting humans in the AI loop, and argues convincingly that, despite everything machines can do (and they can do a lot), humans are still “the real deal.”
The webinar will present examples of how these learnings are shaping our research on developing principles and tools for bringing the AI principle of reliability and safety to reality. In particular, it will showcase an ecosystem of open-source tools that are intended to accelerate the machine learning (ML) development life cycle by identifying and mitigating failures in a faster, systematic, and rigorous way.