The first session from the Big Data & Privacy: Making Ends Meet conference held on September 10, 2013. Event was co-hosted by the Future of Privacy Forum and Stanford Law School’s The Center for Internet and Society.
The proceedings are available in this issue of Stanford Law review. The whole symposium is worth reading but three in particular stand out:
Prediction, Preemption, Presumption by Ian Kerr & Jessica Earle
Contrary to the received view, our central concern about big data is not about the data. It is about big data’s power to enable a dangerous new philosophy of preemption…. [which]…. renders individuals unable to observe, understand, participate in, or respond to information gathered or assumptions made about them.
It’s Not Privacy, and It’s Not Fair by Cynthia Dwork & Deirdre K. Mulligan
While many companies and government agencies foster an illusion that classification is (or should be) an area of absolute algorithmic rule—that decisions are neutral, organic, and even automatically rendered without human intervention—reality is a far messier mix of technical and human curating….
Big Data and Its Exclusions by Jonas Lerman
Big data has the potential to solidify existing inequalities and stratifications and to create new ones. It could restructure societies so that the only people who matter—quite literally the only ones who count—are those who regularly contribute to the right data flows.