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FAST Program AIs Search For Human 'Malintent'

The FAST program (Future Attribute Screening Technology) seeks to passively gather biometric information about people in specific venues (like airports) to try to distinguish persons with "malintent" from people who just want to get on with their travel plans.


(FAST sensors perform covert sampling)

The system’s sensors will “non-intrusively collect video images, audio recordings, and psychophysiological measurements from the employees,” according to a description of the trial program used with employees.

FAST is designed to track and monitor body movements, voice-pitch and rhythm changes, eye movement, body heat, breathing patterns, blink rate and pupil variation.

“The department’s Science and Technology Directorate has conducted preliminary research in operational settings to determine the feasibility of using non-invasive physiological and behavioral sensor technology and observational techniques to detect signs of stress, which are often associated with intent to do harm,” according to a statement DHS gave CNET.

Science fiction readers recall the Vulcan 3 computer from Philip K. Dick's 1960 novel Vulcan's Hammer. This massive self-modifying artificial intelligence computer was provided with massive quantities of data gathered by humans. It also used its own sensors (including robot tracking devices) to gain additional information about individuals that it suspected of malintent.

Via CNET and Wired.

Scroll down for more stories in the same category. (Story submitted 10/11/2011)

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Index of related articles:

Automated Biometric Identification System (ABIS)
Automated Fingerprint Identification System (AFIS)
Behavioral Biometric Characteristic
Biological Biometric Characteristic
Biometrics
Biometric Data
Biometrics Algorithm
Biometric Match
Biometric Match Threshold
Biometric Sample
Biometric System
Capture
Common Biometric Exchange File Format (CBEFF)
Challenge Response
Closed-set Identification
Covert Sampling
Feature Extraction
Live Biometric Capture
Liveness Detection
Non-cooperative User
One-to-many
One-to-One
Open-set Identification
Overt Collection
Speaker Recognition
Spoofing
Template
Threshold
True Accept Rate
True Reject Rate
Uncooperative User
Verification

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