Let's start with some comments about a recent ACLU blog in which they run a facial recognition trial. Using Rekognition, the ACLU built a face database using 25,000 publicly available arrest photos and then performed facial similarity searches of that database using public photos of all current members of Congress. They found 28 incorrect matches out of 535, using an 80% confidence level; this is a 5% misidentification (sometimes called'false positive') rate and a 95% accuracy rate. The ACLU has not published its data set, methodology, or results in detail, so we can only go on what they've publicly said. To illustrate the impact of confidence threshold on false positives, we ran a test where we created a face collection using a dataset of over 850,000 faces commonly used in academia.
When is it appropriate for police to conduct a face recognition search? To figure out who's who in a crowd of protesters? To monitor foot traffic in a high-crime neighborhood? To confirm the identity of a suspect -- or a witness -- caught on tape? According to a new report by Georgetown Law's Center on Privacy & Technology, these are questions very few police departments asked before widely deploying face recognition systems.
Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. The ACLU released a report on Thursday revealing that Rekognition, Amazon's facial recognition tool, had falsely matched 28 members of Congress to mug shots. Members of the ACLU purchased the version of Rekognition that Amazon offers to the general public and ran public photos of every member of the House and Senate against a database of 25,000 arrest photos. The entire experiment costed $12.33, which, as ACLU attorney Jake Snow writes in a blogpost, is "less than a large pizza." Almost 40 percent of the representatives that Rekognition falsely matched were people of color, even though they make up only 20 percent of Congress.
For the last few years, police forces around China have invested heavily to build the world's largest video surveillance and facial recognition system, incorporating more than 170 million cameras so far. In a December test of the dragnet in Guiyang, a city of 4.3 million people in southwest China, a BBC reporter was flagged for arrest within seven minutes of police adding his headshot to a facial recognition database. And in the southeast city of Nanchang, Chinese police say that last month they arrested a suspect wanted for "economic crimes" after a facial recognition system spotted him at a pop concert amidst 60,000 other attendees. These types of stories, combined with reports that computer vision recognizes some types of images more accurately than humans, makes it seem like the Panopticon has officially arrived. In the US alone, 117 million Americans, or roughly one in two US adults, have their picture in a law enforcement facial-recognition database.
Amazon investors are turning up the heat on CEO Jeff Bezos with a new letter demanding he stop selling the company's controversial facial recognition technology to police. The shareholder proposal calls for Amazon to stop offering the product, called Rekognition, to government agencies until it undergoes a civil and human rights review. It follow similar criticisms voiced by 450 Amazon employees, as well as civil liberties groups and members of Congress, over the past several months. 'Rekognition contradicts Amazon's opposition to facilitating surveillance,' the letter states. '...Shareholders have little evidence our company is effectively restricting the use of Rekognition to protect privacy and civil rights.