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Webinar Details

AI for Social Good: Examples, Challenges, and Opportunities

Rayid Ghani

Thursday, April 16, 2020
1:00pm Eastern Time

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About This Course:

Can AI, ML and Data Science help prevent children from getting lead poisoning? Can it reduce infant and maternal mortality? Can it reduce police violence and misconduct? Can it help cities better target limited resources to improve lives of citizens and achieve equity? We're all aware of the potential of ML and AI but turning this potential into tangible social impact takes cross-disciplinary training, new methods, and scalable data and computational infrastructure. I'll discuss lessons learned from working on 50+ projects over the past few years with non-profits and governments on high-impact public policy and social challenges in criminal justice, public health, education, economic development, public safety, workforce training, and urban infrastructure. I'll highlight opportunities as well as challenges around explainability and bias/fairness that need to tackled in order to have social and policy impact in a fair and equitable manner. 

Learning objectives:
  • Get exposed to use cases and case studies in social good and public policy where AI can help
  • Understand what AI can do to tackle social and policy problems
  • Help understand challenges that need to be tackled to solve these problems
Webinar Level:
Introductory
 
About the Instructor:

RayidGhani-012.pngRayid Ghani is a Distinguished Career Professor in the Machine Learning Department and the Heinz College of Public Policy at Carnegie Mellon University. Rayid is a reformed computer scientist and wanna-be social scientist, and works on increasing the use of large-scale AI/Machine Learning/Data Science in solving public policy and social challenges in a fair and equitable manner. Among other areas, Rayid works with governments and non-profits in policy areas such as health, criminal justice, education, public safety, economic development, and urban infrastructure. Rayid is also passionate about teaching practical data science and started the Data Science for Social Good Fellowship that trains computer scientists, statisticians, and social scientists from around the world to work on data science problems with social impact. 

Before joining Carnegie Mellon University, Rayid was the Founding Director of the Center for Data Science & Public Policy, Research Associate Professor in Computer Science, and a Senior Fellow at the Harris School of Public Policy at the University of Chicago. Previously, Rayid was the Chief Scientist of the Obama 2012 Election Campaign where he focused on data, analytics, and technology to target and influence voters, donors, and volunteers.  In his ample free time, Rayid obsesses over everything related to coffee and works with non-profits to help them with their data, analytics and digital efforts and strategy.