Dr. Milind Tambe is a Professor of Computer Science at Harvard University and Director of the Center for Research in Computation and Society. He is also the Director of AI for Social Good at Google Research in India. He has been leading and working on projects that are creating an impact, ranging from wildlife conservation, public health, and safety using AI techniques.
01:05 In concrete terms what projects are you currently working on?
03:18 Do you think there is a disconnect between the scientific/tech communities and the social sector while trying to make use of AI? If so, who should be taking more lead for making that gap small?
05:26 Do these applications in any way inspire novelty in the theoretical aspects of Machine Learning research?
08:15 How do you design and evaluate the impact of these projects?
11:20 How do you define Interpretable or Explainable AI, at the intersection of social sciences and AI?
16:50 Concern of AI usage and Automation. Where do you think the balance lies?
19:50 What bits students can do researchers to work on projects that have a real impact and just pure novelty?
23:45 Roadblocks to more widespread adoption of AI tools for social good?
29:18 What motivates you personally about using AI for social good and not just theoretical exploration of new techniques?
Prof. Milind Tambe's Homepage: https://teamcore.seas.harvard.edu/tambe
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
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