A screen shows a demonstration of SenseTime Group's SenseVideo pedestrian and vehicle recognition system at the company's showroom in Beijing. Facial recognition supporters in the US often argue that the surveillance technology is reserved for the greatest risks -- to help deal with violent crimes, terrorist threats and human trafficking. And while it's still often used for petty crimes like shoplifting, stealing $12 worth of goods or selling $50 worth of drugs, its use in the US still looks tame compared with how widely deployed facial recognition has been in China. A database leak in 2019 gave a glimpse of how pervasive China's surveillance tools are -- with more than 6.8 million records from a single day, taken from cameras positioned around hotels, parks, tourism spots and mosques, logging details on people as young as 9 days old. The Chinese government is accused of using facial recognition to commit atrocities against Uyghur Muslims, relying on the technology to carry out "the largest mass incarceration of a minority population in the world today."

A screen shows a demonstration of SenseTime Group's SenseVideo pedestrian and vehicle recognition system at the company's showroom in Beijing. Facial recognition supporters in the US often argue that the surveillance technology is reserved for the greatest risks -- to help deal with violent crimes, terrorist threats and human trafficking. And while it's still often used for petty crimes like shoplifting, stealing $12 worth of goods or selling $50 worth of drugs, its use in the US still looks tame compared with how widely deployed facial recognition has been in China. A database leak in 2019 gave a glimpse of how pervasive China's surveillance tools are -- with more than 6.8 million records from a single day, taken from cameras positioned around hotels, parks, tourism spots and mosques, logging details on people as young as 9 days old. The Chinese government is accused of using facial recognition to commit atrocities against Uyghur Muslims, relying on the technology to carry out "the largest mass incarceration of a minority population in the world today."

There is a logic behind a newly revealed use of data by federal immigration authorities. Many states welcome people who are in the U.S. without legal status to obtain a driver's license. Now researchers have found that Immigration and Customs Enforcement, along with the FBI, have been running databases filled with driver's license photos through facial recognition software, looking for immigrants of interest. Jake Laperruque is here to talk about this. He is senior counsel at the Project on Government Oversight, an independent group that focuses on corruption and abuse of power.

A Florida state appellate court ruled last week that Willie Allen Lynch, who was convicted in 2016 for selling crack cocaine, had no right to view photos of other suspects identified by the facial recognition search that led to his arrest. In 2015, undercover agents working with the Jacksonville Sheriff's Office photographed a man selling $50 of cocaine. Detectives were unable to identify him, so they decided to turn to the Face Analysis Comparison Examination System, known as FACES, which draws from a database consisting of more than 33 million driver's license and law enforcement photos. The software, which is designed to return multiple potential matches for a given image, named Lynch and four other suspects. Upon further investigation, detectives arrested Lynch for the crime.

Over the past week, the #2009vs2019 meme challenge, alternately known as the #10yearchallenge and #HowHardDidAgeHitYou, has become the latest social media trend ripe for think piece fodder. While the challenge inspired a host of discussions about social media narcissism and gendered norms, author and consultant Kate O'Neill put her own spin on the meme in a tweet raising the privacy implications of posting age-separated photos of oneself on Facebook. The post generated enough buzz and discussion on Twitter that O'Neill expanded it into an article in Wired, in which she argued that Facebook or another data-hungry entity could exploit the meme to train facial recognition algorithms to better handle age-related characteristics and age progression predictions. She noted that the clear labeling of the year in which the pictures were taken, along with the volume of pictures explicitly age-separated by a set amount of time, could be quite valuable to a company like Facebook. "In other words, thanks to this meme, there's now a very large data set of carefully curated photos of people from roughly 10 years ago and now," O'Neill wrote.