Dwork & Mulligan (2013). It's Not Privacy, and It's Not Fair

Cynthia Dwork & Deirdre K. Mulligan (2013). It's Not Privacy, and It's Not Fair; Stanford. Law Review Online (66:35) September 3, 2013.

Classification is the foundation of targeting and tailoring information and experiences to individuals. Big data promises — or threatens — to bring classification to an increasing range of human activity. 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. Both the datasets and the algorithms reflect choices, among others, about data, connections, inferences, interpretation, and thresholds for inclusion that advance a specific purpose. Like maps that represent the physical environment in varied ways to serve different needs — mountaineering, sightseeing, or shopping — classification systems are neither neutral nor objective, but are biased toward their purposes. They reflect the explicit and implicit values of their designers.