Machine Learning in a Data-Driven World: What Does It Mean for Public Policy?
From Google searches to Fitbit tracking and everything in between, our lives are inundated with data. At the same time, computers are getting smarter about how to handle it. Machine learning (the science of programming computers to better perform tasks as they gain experience) holds tremendous possibilities to better inform public policy research. Currently, machine learning is used to predict global health epidemics like Ebola and prevent childhood lead poisoning.
As the world’s population grows and cities become more connected and data driven, how can we harness data for evidence-based public policy research? What are the limitations and challenges? How might machine learning change the way we approach public policy research?
On July 14th, our expert panel from the field explored these questions and more.