The World Privacy Forum submitted public comments today to the National Science Foundation in response to its request for information about a national privacy research strategy. WPF urged a research focus on statistical parity and its implementation. Statistical parity is a term WPF’s Pam Dixon coined at the FTC’s Big Data, Tool For Inclusion or Exclusion? workshop in September 2014. Here is Dixon’s definition of the term:
Big Data and its potential for inclusion and exclusion was on center stage this past September as the FTC held a day-long workshop with experts from industry, technology, privacy, civil liberties, and academia. World Privacy Forum’s Executive Director Pam Dixon, a panelist at the event, spoke about Big Data and privacy, emphasizing several key points, including the need for statistical parity, fairness, and the need for keeping existing consumer protection regulation.
The World Privacy Forum’s recent public comments to the White House regarding Big Data focus on using a foundation of Fair Information Principles to address issues connected to bias, error, and privacy regarding big data as applied to vulnerable populations. The comments also discuss large medical research data sets, and stress the importance of applying
Chris Hoofnagle of Berkeley Law has just published arguably the single most important archive in privacy today: it is the transcripts of six of the HEW meetings in the early 197os that formed the origins of today’s Fair Information Practices. FIPs have now for 40 years formed the cornerstone of most of the privacy laws passed globally. Long lost to the dust of time, the original hearing transcripts have never been available online, and even access to the paper versions have not been widely available.
Visiting Scholar: Privacy in a Modern Era — Pam Dixon is a visiting scholar at Portland’s PNCA. She is scheduled to speak with students in a round of interdisciplinary classes, and she will also be giving a public keynote at 7 pm in Swigert Commons. Her public lecture is on Modern Privacy.