Ethics in big data

About

Governments, corporations, and organizations in civil society now routinely create massive repositories of raw data whose size and complexity pose major technical, analytic, and ethical challenges. As policy makers have come to realize recently in domains as diverse as genetics and counter-intelligence, successful resolution of the challenges of Big Data requires broad and varied public consultation. A diverse group of experts should collaborate on, and help guide, iterative consultation for how best to collect, archive, and utilize Big Data in the most ethical manner possible. In collaboration with partners from several disciplines, organizations and institutional sectors, Georgetown has launched a project to facilitate the consultation process evolving as a collaborative engagement of technical, computational, societal, and subject matter experts in Big Data. The creation of the Massive Data Institute within the McCourt School of Public Policy at Georgetown University is an opportunity to support the integration of this consultation process as an intrinsic component of this new Big Data initiative that could transform policy-oriented research and public policy-making in the nation’s capitol.

The Team

  • Isabel Bradburn, Virginia Technological University
  • Jeff Collmann, Georgetown University
  • Kevin FitzGerald, Georgetown University
  • James Giordano, Georgetown University
  • Sorin Matei, Purdue University
  • Douglas Richardson, Association of American Geographers
  • Andrew Russell, Stevens Institute of Technology
  • Michael Steinmann, Stevens Institute of Technology
  • Rochelle Tractenberg, Georgetown University

Outcomes

Conference on Privacy in the Infosphere: Developing ethical guidelines for managing Big Data in research, April 16-17, 2015, Georgetown University, sponsored by the National Science Foundation under Grant No. SMA-1338507.

Acknowledgement

This material is based upon work supported by the National Science Foundation under Grant No. 1338507. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.