'Anonymized Data' Is A Gibberish Term, And Rampant Location Data Sales Is Still A Problem
The article exposes the dangerous misconception that data stripping away direct identifiers like Social Security numbers truly protects user privacy. It highlights that location data, in particular, remains highly re-identifiable because movement patterns can easily reveal a person’s home, workplace, and daily habits. This reality contradicts the common industry and government claim that such information is harmless when "anonymized," as simple cross-referencing with other datasets allows for rapid identification of individuals. This lack of genuine anonymity fuels a non-transparent marketplace where data brokers buy and sell massive volumes of location records with minimal user consent or disclosure. Companies like Veraset operate without revealing their data sources, relying on public ignorance to maintain their business model. Despite the potential for abuse by stalkers or law enforcement, regulatory reforms have stalled due to intense lobbying, leaving users with little control over how their sensitive mobility information is traded, often without their knowledge. This issue is critically relevant to open data discussions because it illustrates the severe limitations of anonymization techniques often assumed to be sufficient for public dataset releases. The text demonstrates that even without explicit personal identifiers, seemingly general data can compromise individual privacy if not handled with rigorous de-identification standards. It serves as a cautionary tale for anyone publishing datasets, emphasizing that transparency and strong privacy safeguards are essential to prevent harm, rather than relying on the flawed premise that removing names equals safety.
Source: techdirt.comPublished on 2023-06-15