By Sam Biddle
You’re rarely allowed to know exactly what’s keeping you safe. When you fly, you’re subject to secret rules, secret watchlists,
hidden cameras, and other trappings of a plump, thriving surveillance
culture. The Department of Homeland Security is now complicating the
picture further by paying a private Virginia firm to build a software
algorithm with the power to flag you as someone who might try to blow up
the plane.
The new DHS program will give foreign airports around the world free
software that teaches itself who the bad guys are, continuing society’s
relentless swapping of human judgment for machine learning. DataRobot, a
northern Virginia-based automated machine learning firm, won a contract
from the department to develop “predictive models to enhance
identification of high risk passengers” in software that should “make
real-time prediction[s] with a reasonable response time” of less than
one second, according to a technical overview that was written for
potential contractors and reviewed by The Intercept. The contract
assumes the software will produce false positives and requires that the
terrorist-predicting algorithm’s accuracy should increase when
confronted with such mistakes. DataRobot is currently testing the
software, according to a DHS news release.
The contract also stipulates that the software’s predictions must be
able to function “solely” using data gleaned from ticket records and
demographics — criteria like origin airport, name, birthday, gender, and
citizenship. The software can also draw from slightly more complex
inputs, like the name of the associated travel agent, seat number,
credit card information, and broader travel itinerary. The overview
document describes a situation in which the software could “predict if a
passenger or a group of passengers is intended to join the terrorist
groups overseas, by looking at age, domestic address, destination and/or
transit airports, route information (one-way or round trip), duration
of the stay, and luggage information, etc., and comparing with known
instances.”
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Source: The Intercept_
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