• Clifford Lynch at UCLA: Stewardship in the Age of Algorithms

    2–4 p.m. Wednesday, April 26, 2017 Presentation Room, Charles E. Young Research Library Free admission; no reservations required The term “algorithms” is increasingly used as shorthand to describe complex, large-scale socio-technical systems such as social media platforms, analytic systems, recommendation engines, and personalization that depend on frequently opaque and constantly changing computational algorithms. With the explosion in analytic and…

  • UCLA Data Governance Task Force: final report and recommendations

    I am thrilled to announce that the Data Governance Task Force’s work has completed and its final report and recommendations are now available. We’d like to contribute some ideas for addressing questions about appropriate use of data shared by many of our higher ed colleagues. We’re also interested in thoughts about the report. NB. Availability…

  • DataLex: Privacy, Big Data & the Law

    UC Santa Cruz is holding a day-long event on Tuesday, October 13 at the intersection of big data, privacy, and the law. A diverse and renowned group of speakers and a format designed to engage the audience is going to make for a fascinating and fun day… (Full disclosure: I’m moderating one of the panels.)…

  • An invitation to meet the authors of graphic novella “Terms of Service”

    The graphic novella Terms of Service: Understanding Our Role in the World of Big Data examines the role of technology and the implications of sharing our personal information online. I am pleased to join the UCLA Library in presenting authors Michael Keller, a multimedia reporter at Al Jazeera America, and Josh Neufeld, a nonfiction cartoonist,…

  • Invitation to the book signing for Big Data, Little Data, No Data

    Christine Borgman’s brand-new book, Big Data, Little Data, No Data: Scholarship in the Networked World is for anyone who bandies about the words “big data”. Read this interview and come to the book signing 4-6pm February 25 (flyer)!  

  • Of course we can … but should we?

    Big Data: it’s big, messy, and fast-paced: and demand is endless for more data capture, more intertwingling of sources, more slicing, dicing, massaging, and filtering to reveal insights. These demands can result in uses perceived as mostly helpful (The year open data went worldwide) or mostly icky (How Companies Learn Your Secrets). Demand for new…