Role Models in AI: Ece Kamar

AI4ALL Team
Apr 25, 2018 · 7 min read

It is not a question of “can we build AI,” as we have a lot of successful examples of AI systems. Instead, there are questions of, “how should these systems be built and deployed? How should they be partnering with people?”

You’ve also done a lot of work looking at how humans and machines can collaborate.

If our focus is only automating what exists in the world, and not on complementarity of tasks, we won’t be utilizing the true power of human-machine partnership.

The combination of humans and machines will be more effective, efficient, and reliable than either is on their own.

A lot of computer science problems are practical and could have real-world impact. I see women who care about the impact of technology on the world. I cannot imagine girls not enjoying these beautiful problems if they are given the opportunity and support in exploring these areas.

When I got to grad school in the United States, I realized that this gender disparity existed. It was an interesting cultural shift for me.

Some of the issues we’re seeing in AI systems today have deep connections to the diversity problems in the field. Having diversity in our field is not only an issue about the culture. It is also about the reliability, robustness, and fairness of the systems we build. It is of practical importance to us that everybody’s voice gets represented in the systems we build.

About Ece Kamar

Ece Kamar is a Senior Researcher in the Adaptive Systems and Interaction Group at Microsoft Research. Ece received her Ph.D. in computer science from Harvard University in 2010. Her research is inspired by real-world applications that can benefit from the complementary abilities of people and AI. Since many real-world problems requires interdisciplinary solutions, her work spans several subfields of AI, including planning, machine learning, multi-agent systems and human-computer teamwork. She is passionate about investigating the impact of AI on society and studying ways to develop AI systems that are reliable, unbiased and trustworthy. She has over 40 peer-reviewed publications at the top AI and HCI venues and served in the first Study Panel of Stanford’s 100 Year Study of AI (AI100).

AI4ALL

AI4ALL is a nonprofit working to increase diversity and inclusion in artificial intelligence. Our vision is for AI to be developed by a broad group of thinkers and doers advancing AI for humanity's benefit.

AI4ALL Team

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AI4ALL is a US nonprofit working to increase diversity and inclusion in artificial intelligence.

AI4ALL

AI4ALL

AI4ALL is a nonprofit working to increase diversity and inclusion in artificial intelligence. Our vision is for AI to be developed by a broad group of thinkers and doers advancing AI for humanity's benefit.