video, podcastJune 14 2017

Data Science Reasoning

Anne Washington

Databite No. 101

Anne Washington talks about the risks of efficiency and optimization, and the need for a common language when speaking about data science and public policy. It is often difficult for technology experts to have conversations with policy makers due to the failure of a common language when talking about data science.



Washington explains why overcoming technical jargon would promote productivity and forge new alliances among policy makers and those working in the tech industry.

Data & Society’s Fellows Talks is a three-part Databite series showcasing our 2016-2017 fellows cohort. Each talk features 3 fellows speaking about their work, wide-ranging interdisciplinary connections, and a few of the provocative questions that have emerged this year.

Data & Society Executive Director Janet Haven moderated the conversation.

Anne L. Washington is a computer scientist and a librarian who specializes in public sector technology management and informatics. She is an Assistant Professor at George Mason University. As a digital government scholar, her research focuses on the production, meaning, and retrieval of public sector information. She developed her expertise on government data working at the Congressional Research Service within the Library of Congress. She also served as an invited expert to the W3C E-Government Interest Group and the W3C Government Linked Data Working Group. She completed a PhD from The George Washington University School of Business. She holds a degree in computer science from Brown University and a Master’s in Library Information Science from Rutgers University. Before completing her PhD, she had extensive work experience in the private sector including the Claris Software division of Apple Computers and Barclays Global Investors.

About Databites

Data & Society’s “Databites” speaker series presents timely conversations about the purpose and power of technology, bridging our interdisciplinary research with broader public conversations about the societal implications of data and automation.