Re: Where is Proxmire Golden Fleece award when we need it -- Was -- Big Brother

[David Farber <dfarber () cs cmu edu>]

Begin forwarded message:

From: Ross Stapleton-Gray <ross () stapleton-gray com>
Date: October 7, 2007 11:41:12 PM EDT
To: dave () farber net
Subject: Re: [IP] Where is Proxmire  Golden Fleece award when we need  
it -- Was -- Big Brother

At 01:43 PM 10/7/2007, David Farber wrote:
> ps I would like to see the proposal.

Here's the public abstract from FastLane, with other award information:
http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0731115

"ABSTRACT
[]

One of the most important goals for our military and homeland  
security personnel is to catch people who are planning to attack our  
military and civilian facilities before they strike. This project  
proposes to identify, interpret, and develop procedures for  
automatically measuring the types of behavioral clues exhibited by  
people who intend on attacking, particularly when they attempt to  
conceal or fabricate their true intentions. Although research has  
shown that there is no one signal or behavior that reveals whether a  
person is concealing his or her intentions or telling a lie,  
researchers agree that most behavioral clues to deceit are person  
specific, which require determining a baseline reading of the  
person's normal behavior and calibrating changes from that baseline.  
This project improves on prior research because it will examine  
behaviors that are elicited in more realistic, high stake scenarios,  
and will do it without attaching any instruments to the person, while  
applying automatic machine learning systems to take each indicator  
behavior and identify which changes are best able to identify a  
person as truthful or lying. This procedure will then produce a  
prototype that examines video of both checkpoint and 'sit down'  
interrogation sessions and automatically produces a single integrated  
score of deception/malfeasance likelihood.

The broader impact of this project is that it will bring together  
behavioral, computer, and engineering scientists to apply their state  
of the art tools to creating a system with the potential for  
identifying a potential terrorist before he or she attacks. The  
synergy generated by this rare combination of skills and knowledge  
between the researchers will advance knowledge not only in this  
specific topic but also in areas of research such as social  
psychology, computer vision and automatic machine learning. Finally,  
this project will maintain this synergy momentum by training future  
generations of not only Ph.D. and Postdoctoral students, but will  
also be applied to ongoing counter-terrorism training programs."

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