Data Science and Evidence Based Policy
Data Science and Evidence Based Policy


Access to high-quality information to make good decisions is necessary for society to function. Good data level the playing field for businesses and individuals alike. It is necessary at every level of economy and society—to help small businesses succeed, schools serve parents and students, and central banks make sound policy. Those data must be an accurate reflection of the people in our country.
The need is also clear. Costs continue to increase and quality continues to decrease. Our data should represent American economic and social activity, and our current system is not up to the job. Indeed, the Federal Data Strategy, the passage of the Foundations for Evidence-Based Policymaking Act, the Artificial Intelligence Executive Order, and the Information Quality Act all provide agencies with principles and practices to change the way in which they make use of data
We must design a new system that will produce public data that are useful at all levels—and make scientific, careful, and responsible use of many newly available data, such as administrative records from agencies that administer government programs, data generated from the digital lives of citizens, and even data generated within the private sector. This presentation will paint a picture of what this new system could look like, focusing on the innovations necessary to change the existing system, with the goal of providing useful and timely data from trusted sources so that we, the people, have the information necessary to make better decisions.
The presentation particularly focuses on the role of data science and computer science in driving data innovation for evidence based policy.


Julia Lane is a Professor at the Wagner School of Public Policy at New York University. She is also a Provostial Fellow in Innovation Analytics and a Professor in the Center for Urban Science and Policy.
Previous to this, Julia was a Senior Managing Economist and Institute Fellow at American Institutes for Research. In this role, Julia co-founded the Institute for Research on Innovation and Science (IRIS) at the University of Michigan.
Julia has published over 80 articles in leading economics journals and authored or edited ten books. She is an elected fellow of the American Association for the Advancement of Science, the International Statistical Institute and a fellow of the American Statistical Association.
Julia received her PhD in Economics and a Master's in Statistics from the University of Missouri.