Data analytics and consumer profiling: Finding appropriate privacy principles for discovered data

Nancy J. King, Jay Forder

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

In Big Data, the application of sophisticated data analytics to very large datasets makes it possible to infer or derive (“to discover”) additional personal information about consumers that would otherwise not be known from examining the underlying data. The discovery and use of this type of personal information for consumer profiling raises significant information privacy concerns, challenging privacy regulators around the globe. This article finds appropriate privacy principles to protect consumers’ privacy in this context. It draws insights from a comparative law study of information privacy laws in the United States and Australia. It examines draft consumer privacy legislation from the United States to reveal its strengths and weaknesses in terms of addressing the significant privacy concerns that relate to Big Data's discovery of personal data and subsequent profiling by businesses.

Original languageEnglish
Pages (from-to)696-714
Number of pages19
JournalComputer Law and Security Review
Volume32
Issue number5
DOIs
Publication statusPublished - 1 Oct 2016

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privacy
Data privacy
privacy law
consumer information
Industry
personal data
Big data
Profiling
Privacy
legislation
Law
Privacy concerns
Information privacy
Personal information

Cite this

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Data analytics and consumer profiling: Finding appropriate privacy principles for discovered data. / King, Nancy J.; Forder, Jay.

In: Computer Law and Security Review, Vol. 32, No. 5, 01.10.2016, p. 696-714.

Research output: Contribution to journalArticleResearchpeer-review

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