Daniel (Danny) Bobrow passed away peacefully at home with his wife Toni and daughters Kimberly and Deborah in Palo Alto, California, on March 20, 2017, having bravely fought a five-month battle with cancer. Danny was born to Ruth Gureasko Bobrow and Jacob Bobrow on November 29, 1935, in the Bronx, New York City. A gifted student, he attended Bronx High School of Science and went on to earn a BS from Rensselaer Polytechnic Institute, an MS from Harvard, and a PhD in Mathematics from Massachusetts Institute of Technology under the supervision of Marvin Minsky. His was one of the first MIT doctoral theses in Artificial Intelligence. A pioneer with a long and distinguished research career in Artificial Intelligence as a Research Fellow in the System Sciences Laboratory of the Palo Alto Research Center (PARC), he is remembered as a mentor, friend, and role model for many.

The past year has seen a growing public awareness of the privacy risks of social networking through personal information that people voluntarily disclose. A spotlight has accordingly been turned on the disclosure policies of social networking sites and on mechanisms for restricting access to personal information on Facebook and other sites. But this is not sufficient to address privacy concerns in a world where Web-based data mining tools can let anyone infer information about others by combining data from multiple sources. To illustrate this, we are building a demonstration data miner, GlobalInferencer, that makes inferences about an individual?s lifestyle and other behavior. GlobalInferencer uses linked data technology to perform unified searches across Facebook, Flickr, and public data sites. It demonstrates that controlling access to personal information on individual social networking sites is not an adequate framework for protecting privacy, or even for supporting valid inferencing. In addition to access restrictions, there must be mechanisms for maintaining the provenance of information combined from multiple sources, for revealing the context within which information is presented, and for respecting the accountability that determines how information should be used.