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Katz is out of the Bag:
Katz’s Weaknesses & the Rapidly Emerging Technology of Today and the Future. 

Robert Keates                                                                                     Spring, 2005

 

Section III – Developing Technologies and Law Enforcement Devices
Over the past 10 years, an onslaught of groundbreaking technological advances have been making their way into the hands of the government and law enforcement agencies worldwide.  These sophisticated devices are able to aquire information from afar, without even alerting the suspect.  This section will discuss five types of the latest technological developments used by law enforcement in the fight against crime.   Each item will be explained and described, and then the section will examine where the technology has been put to use.

A.        Facial Recognition Systems
To understand the power of facial recognition, it is useful to briefly discuss its origin in video surveillance.  Video surveillance was first introduced in 1956, and has rapidly been incorporated into American society. With the advent of digital imaging, video surveillance became more effective, less expensive, and more advanced.   Multiple cameras are able to be linked together to a main computing center, leaving hundreds of areas observable to law enforcement from a single room.   Baltimore boasts the most expansive video surveillance system currently in place, while Washington D.C. police departments operate cameras that overlook the downtown streets, parks, and subways.   Many other cities have followed suit.  
When these complex surveillance networks are paired with biometrics, the result is a system of identification that can be used to pick out individuals in a large crowd.  Biometrics involves the techniques and methods used to identify an individual based on physical characteristics.   Generally, this involves scanning a physical characteristic, converting the scan to a digital image, entering the image in a database, and then later accessing the database to compare codes.   Facial recognition software takes this concept and applies it to facial features.  Video cameras are used to take a snapshot of an individual’s face.   Most software takes into account aging, hair, lighting, as well as accessories such as glasses, wigs, and even plastic surgery.   This image is then scanned through facial recognition software, where translating the contours of the face into mathematical formulas creates a digital map of the face.   Law enforcement agents can then use the digital face map to search through databases of known or suspected criminals who have had their mug shots scanned.   Present software, running on a newer computer, can scan almost 70 million images per minute, with an error rate of less than 1 percent.   The only operational drawback is that the camera must capture both of an individual’s eyes, and the face cannot be turned more than 45 degrees from the camera.
Software can be linked to databases capable of providing a wide variety of information.  When a face is recognized, the mathematical code is scanned through these databases to reveal the person’s criminal record and pedigree information.   Databases may be programmed to contain any information at all, from friends and employment to eating habits.
England was the first country to use facial recognition software, where over 300 cameras were placed in crime-ridden sections of London in 1998.   The system was praised when crime rates dropped 34 percent.   Other countries that have used this technology include Israel, Mexico, and Uganda.   So far, facial recognition has been utilized in a variety of locations in the United States, and not always by law enforcement.  Casinos routinely use the system to monitor cheats and card counters.   Banks use the software to forgo passwords and personal ID numbers in an attempt to thwart identity theft.   The Department of Defense, Justice, State, and Energy all utilize the system to promote public safety and access to certain secure buildings.  
In January 2001, facial recognition was used at Super Bowl XXXV in Tampa, Florida.   Cameras were placed throughout the stadium to scan the unsuspecting crowds for criminals.   Out of almost 100,000 fans, the software identified 19 criminals, although no arrests were made.   Tampa officials also opted to use the software at the Ybor Entertainment Center, notorious for high crime rates.   After a few weeks of use, and 14 incorrect identifications, the project was suspended by the city.   Virginia Beach still runs their facial recognition program. Airports that use facial recognition software include Fresno International, St. Petersburg-Clearwater International, Dallas-Fort Worth, Boston Logan, and Palm Beach International.   The Winter Olympics in Salt Lake City spent $310 million on facial recognition software, to scan the crowds for terrorists, although only at some of the events.
This technology is rapidly advancing.  Software stores sell home use facial recognition software for about $100; the same software that was classified six years ago. Newer systems utilize infrared patterns of the face, allowing the system to work in the dark.

B.            Concealed Weapon Detectors
Concealed Weapon Detectors were developed in the early 1990’s, although they have been rapidly developing.   Weapon detectors are like smaller, portable metal detectors, allowing officers to view weapons under clothing, regardless of the number of layers or material.   Detectors measure the electromagnetic radiation emitted by all objects, and then analyze that radiation, converting the readings into a visible form.
Currently there are at least four types of weapon detectors under development, funded by the National Institute of Justice.   Raytheon’s detector uses a low intensity electromagnetic pulse to measure the time decay of radiated energy emitting from an object carried by a subject. This device produces no images and detects only metal objects.   Idaho National Engineering Laboratory is developing a similar device that uses multiple magnetic sensors, coupled with target recognition software that signals the presence of any objects fitting the signature of a weapon.   This device cannot detect the presence of nonmetallic objects or the body.   The Millitech Corporation’s Millimeter utilizes a passive wave meter designed to detect natural emissions from a person’s body, rather than electromagnetic or artificial radiation.   These wave signals are weaker when forced to pass through metal of other objects.   The Millimeter can peer through briefcases and purses, and also has the capacity to detect plastic explosives and drugs, in solid, liquid, and powder form.   It has been noted that this device is capable of producing a relatively precise picture of the human body, including anatomical details. A detector developed by Pacific Northwest National Laboratory, uses a high frequency radar, rather than passive technology. This device produces a holographic image of the body and all objects found in the subject’s clothing.   Like the Millimeter, Pacific’s device has the capacity to reveal anatomical details, easily distinguishing between males and females.
Although mainstream use has been extremely limited, it has been suggested that officers use weapon detectors in place of a pat down during terry frisks.   It has also been suggested, albeit with great criticism, that officers use these devises on the street in high crime areas, with unrestricted discretion as to whom they inspect.

 

C.            Heartbeat Detection Devices
The Enclosed Space Detection Systems, or heartbeat detector, is a surveillance tool designed to detect the presence of people hiding in an enclosed area by identifying the presence of their heartbeat.   The system originated as a way to detect people hiding in vehicles at border checkpoints and access roads to sensitive facilities.   Each beat of the human heart produces a small shock wave that travels through the body, causing an enclosed area to vibrate at a unique frequency.   A heartbeat detector can then monitor the frequency, and identify any vibrations from a hidden individual.   The system is virtually foolproof, operating at a 100% accuracy rate, even when individuals were wrapped in comforters and in the middle of a full trash truck.    The device has even been effective detecting the heartbeats of dogs, cat, and mice.
The potential uses for this technology are endless, including the monitoring of international borders, smuggling of endangered animals, protection of nuclear facilities, escapes from prison, and protection in airports.   Developers at the Oak Ridge National Laboratory loaned the system to the Atlanta Police Department during the 1996 Olympic Games.

 

 

Robert H. Thornburg, Facial Recognition Technology: The Potential Orwellian Implications and Constitutionality of Current Uses under the Fourth Amendment, 20 J. Marshall J. Computer & Info. L. 321, 323 (2002).

Id.

Marc Jonathan Blitz, Video Surveillance and the Constitution of Public Space: Fitting the Fourth Amendment to a World that Tracks Image and Identity, 82 Tex. L. Rev. 1349, 1353 (2004).

Thornburg, supra note 142, at 323.

Blitz, supra note 144, at 1352.

Slobogin, supra note 89, at 220; see also https://www.newsmax.com/archives/articles/2004/12/26/102308.shtml.

Thornburg, supra note 142, at 323-24.

Id. at 323.

Thornburg, supra note 142, at 325.

Alexander T. Nguyen, Here's Looking at you, Kid: Has Face-Recognition Technology Completely Outflanked The Fourth Amendment?, 7 Va. J. L. & Tech. 2, 6 (2002).

David McCormack, Can Corporate America Secure our Nation?  An Analysis of the Idetex Framework for the Regulation and Use of Facial Recognition Technology, 9 B.U. J. Sci. & Tech. L. 128, 131 (2003).

Id.

Id. at 131-32.

Nguyen, supra note 151, at 5.

McCormack, supra note 152, at 131.

Id. at 132.

Id.

McCormack, supra note 152, at 132.

Roberto Iraola, Lights, Camera, Action! Surveillance Cameras, Facial Recognition Systems and the Constitution, 49 Loy. L. Rev. 773,782 (2003).

Id.

Id. at 782-83.

Id. at 783.

Thornburg, supra note 142, at 326.

Id.

Id.

Id.

McCormack, supra note 152, at 134.

Id.

Thornburg, supra note 142, at 328.

Christopher S. Milligan, Facial Recognition Technology, Video Surveillance, and Privacy, 9 S. Cal. Interdis. L.J. 295, 304 (1999).

Iraola, supra 160, at 783.

David A. Harris, Superman’s X-Ray Vision and the Fourth Amendment: The New Gun Detection, 69 Temp. L. Rev. 1, 7-8 (1996).

Id. at 10.

Melissa Arbus, A Legal U-Turn: The Rehnquist Court Changes Direction and Steers Back to the Privacy Norms of the Warren Era, 89 Va. L. Rev. 1729, 1752 (2003).

Laura B. Riley, Concealed Weapon Detectors and the Fourth Amendment: The Constitutionality of Remote Sense-Enhanced Searches, 45 UCLA L. Rev. 281, 288 (1997).

Iraola, supra note 160, at 10.

Id.

Riley, supra note 176, at 289.

Id.

Alyson L. Rosenberg, Passive Millimeter Wave Imaging: A New Weapon in the Fight Against Crime or a Fourth Amendment Violation?, 9 Alb. L.J. Sci. & Tech. 135, 138-39 (1998).

Id. at 139.

Rosenberg, supra note 181, at 140.

Arbus, supra note 175, at 1753-54.

Id. at 1754.

Id.

Id.

Riley, supra note 176, at 289-90.

Id. at 293.

Iraola, supra note 160, at 13.

George M. Dery III, The Loss of Privacy is Just a Hearteat Away: An Exploration of Government Heartbeat Detection Technology and its Impact on Fourth Amendment Protections, 7 Wm. & Mary Bill of Rts. J. 401, 402 (1999).

Iraola, supra note 160, at 13.

Id.

Dery III, supra note 191, at 404.

Id.

Id. at 406-09.

Dery III, supra note 191, at 404.


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