A Visual Guide to Practical Data De-Identification Infographic

This FPF infographic provides a visual explanation of de-identification, the process of removing personally identifiable information from data collected, stored, and used by organizations, which was once viewed as a silver bullet allowing organizations to reap data benefits while at the same time avoiding risks and legal requirements.

The concept of de-identification has come under intense pressure to the point of being discredited by some critics. Computer scientists and mathematicians have created a re-identification tit for every de-identification tactic. At the same time, organizations worldwide continue to rely on a wide range of technical, administrative, and legal measures to reduce the identifiability of personal data to enable critical uses and valuable research while protecting individuals’ identity and privacy.

While not foolproof, de-identification techniques unlock value by enabling important public and private research, allowing for the maintenance and use – and, in certain cases, sharing and publication – of valuable information while mitigating privacy risk.

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Omer Tene, Kelsey Finch, and Jules Polonetsky have been working to address these thorny issues in a paper titled Shades of Gray: Seeing the Full Spectrum of Practical Data De-Identification. The paper is published in the Santa Clara Law Review.