Customer data analytics: privacy settings for 'Big Data' business

Abstract

At the heart of a current global debate as to privacy regulation and ‘Big Data’ debate lie four questions:— Can national privacy laws and regulation facilitate socially beneficial uses and applications of Big Data while precluding ‘Big Brother’ or unduly ‘spooky, ‘creepy’, or otherwise socially or culturally unacceptable Big Data practices?— Can diverse national privacy laws and regulation be applied or adapted so as to accommodate socially beneficial uses and applications of Big Data, or is a more fundamental overhaul of privacy law required?— If fundamental design precepts of privacy regulation require adaptation or supplementation to address Big Data, can those changes be made without threatening broader consistency and integrity of privacy protections for individuals?— Can any adaptation or changes be made quickly enough to address growing citizen concerns about unacceptable or hidden Big Data practices? Responsible governance of data analytics affecting citizens, whether by businesses or government, requires a new dialogue and community understanding about appropriate transparency and ethical boundaries to uses of data analytics. This requires both businesses and government to acknowledge that for many citizens, privacy still matters and that many citizens have a deficit of trust as to uses of their personal information by government and at least some businesses. A nuanced debate about good Big Data and bad Big Data and transparency as to acceptable data analytics practices is necessary for a dialogue between citizens and data users. This paper examines how to build transparency and engender trust through good business practices in data analytics. The paper considers developing regulatory policy concerning the de-identification of personal information and how to embed privacy impact assessment practices and privacy by design and security by design principles as operational (administrative, security, and contractual) safeguards within data analytics service providers, governments, and businesses.