The Really Smart Phone
Researchers are harvesting a wealth of intimate detail from our cellphone data, uncovering the hidden patterns of our social lives, travels, risk of disease—even our political views. — ‘Phones can know,’ says an MIT researcher. 'People can get this god's-eye view of human behavior.'
Context & Ripple Effects
This piece extends a thread the Journal opened four months earlier with Your Apps Are Watching You, which documented how apps transmit personal data; here the lens shifts from what apps collect to what researchers can infer once that stream is aggregated. The named engine is MIT — the same campus behind the Senseable City Lab's realtime-cloud proposal with Google and Umberto Eco for the 2012 London Olympics, and behind the 2009 'Gaydar' term project that showed sexual orientation could be predicted from friendship networks alone.
First-order effects
- MIT and comparable labs gain a working method for extracting social ties, travel patterns, disease risk, and political leaning from ordinary handset data, making research subjects' phones into continuous observation instruments without any new hardware.
Second-order effects
- Carriers and app developers sit on the feed these methods depend on, so commercial pressure builds to license or monetize location and call metadata — turning a research capability into a product category others will race to supply.
Third-order effects
- If inference from phone data becomes routine, regulators face the question the 'Gaydar' project already raised: whether derived attributes like health status or political view deserve protection even when the underlying data was shared voluntarily, pushing mobile metadata toward treatment as sensitive personal information.
The trend: Mobile-phone metadata is becoming the raw material for a behavioral-inference industry that predicts intimate traits from patterns users never knowingly disclosed.