Location and phone-sensor data reveal individuals and moods even when anonymized

Evidence

In 2013 a group of MIT and Harvard computer scientists demonstrated that because individuals tend to have idiosyncratic mobility signatures, any analyst with the right tools can easily extract the mobility pattern of a specific individual within a large anonymized data set of location meta-data. Another research team demonstrated that data collected by seemingly “innocuous” smartphone-embedded sensors, such as accelerometers, gyroscopes, and magnetometers, can be used to infer “an ever-growing range of human activities and even moods.” — Shoshana Zuboff, The Age of Surveillance Capitalism, 766

Categorization

• XREF: connects to: Supposedly anonymized location data can identify individuals’ home addresses — Shoshana Zuboff, The Age of Surveillance Capitalism, 543; Fitness trackers leak geolocation data that serves no user benefit — Shoshana Zuboff, The Age of Surveillance Capitalism, 779; Anonymous meta-data can be reliably de-anonymized with only three public data points — Shoshana Zuboff, The Age of Surveillance Capitalism, 765 (+5 more)

Broader Connections

• Pentland frames ubiquitous behavioral data as a radically new mode of social self-knowledge #corroborates (0.82) — Shoshana Zuboff, The Age of Surveillance Capitalism, 1374