The Chicago Police Department made its first arrest based solely on facial recognition technology last week.

Pierre D. Martin, 35, was arrested for armed robbery on board a Chicago’s Transit Authority vehicle. According to The Chicago Sun-Times, the police obtained images of the thief from surveillance cameras and used NeoFace, a facial-recognition program the department purchased using a part of a $5.4 million federal grant, to compare the surveillance images to the department’s 4.5 million criminal booking shots on file. Martin, who was in the database due to his previous criminal activities, which include assault and burglary, came up first in the list of possible matches.

“This case is a great example that these high-tech tools are helping to enhance identification and lead us to defendants that might otherwise evade capture,” Cook County State’s Attorney Anita Alvarez said in a statement.

Elizabeth Joh, a criminal law professor at the University of California Davis told Ars Technica that to her knowledge, this is the first time a police department has claimed to have caught a suspect solely through the use of facial recognition technology. 


The technology has been used for years with varying degrees of success, but Anil Jain, a biometrics expert and professor of computer science at Michigan State University, told Ars Technica these systems are improving and becoming more useful for law enforcement purposes. However, he says probability of getting a solid match still depends on the quality of the image scanned.

“If the face in video is close to frontal and the image quality is good, matching accuracy is very high,” he told Ars Technica. “We can further filter the large mugshot database by specifying the gender, race and age group of the suspect. This filtering step also improves the matching success.”

But Joh warns that facial recognition software is not a catchall. One issue is that most images taken from surveillance footage are low resolution, which could lead to false matches. “The greatest concern with any big data tool, whether facial recognition technology or [license plate readers], is its accuracy and the amount of error we should tolerate when the police decide to interfere with individual liberty,” Joh told Ars Technica.


The ACLU agrees with these concerns. Jay Stanley, a policy analyst with the American Civil Liberties Union, told Ars Technica that his organization is not opposed to the use of this technology, but it does raise complex issues.

“The question that needs to be asked is: for every success, how many other situations are there?,” he told Ars Technica. “How many times has this technology been used and not resulted in a prosecution? How many people have been scrutinized by the police when their face came up in a false match?”

Martin, a previously convicted felon, was sentenced to 22 years in prison for the robbery, The Chicago Sun-Times reports. 

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