Bills banning the use of facial recognition by police have recently been introduced in New York and Washington. And Clearview received a letter from Sen. Edward Markey, D-Mass., asking for a list of law enforcement agencies that have used the app and whether biometric information has been collected for children under 13 years old.
Clearview has attracted a whirlwind of attention for claiming it had built unprecedented facial recognition trained on an ever-increasing database of more than 3 billion photos ripped from Facebook, Instagram, YouTube, and other websites. In a January interview with the New York Times, Ton-That said the company was working with 600 law enforcement agencies across the country and had provided the software, which can be used on a desktop computer or through a mobile app, to the FBI and Department of Homeland Security.
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There are currently no federal laws regulating the use of facial recognition, though several elected officials have proposed bills. States including Illinois have developed regulations on the corporate use of biometric data, and some cities have outright banned the technology. In that regulatory vacuum, Clearview has thrived, doling out free trials seemingly at will and encouraging law enforcement officers and officials to invite their colleagues and perform as many searches as possible.
Those two, Central Montco Technical High School in Pennsylvania and Somerset Berkley Regional High School in Massachusetts, did not respond to a request for comment. Somerset Police Department, which appears on the list with Somerset Berkley Regional, initially denied ever using Clearview or any facial recognition software, but later stated that a detective had received a 30-day free trial. The documents show that each school was only associated with one account. Neither had run more than five searches.
While the music industry paused, Major League Baseball stole a base by rolling out biometric ticketing in the US, usually involving fingerprints or iris scans to get into ballparks. Authorities in some parts of Europe have bounced around the idea of using either facial or voice recognition to keep tabs on unruly soccer fans, such as those participating in racist chants. Police agencies in China have used facial recognition at concerts featuring pop singer Jacky Cheung to identify and arrest people wanted as criminal suspects.
American music event promoters this fall have been pressured to disclose their facial recognition plans by digital rights group Fight for the Future, which asked dozens of festival organizers to pledge not to use a technology it describes as invasive and racially biased.
The objective of the current study is to examine the contribution of intellectual abilities, executive functions (EF), and facial emotion recognition to difficulties in Theory of Mind (ToM) abilities in children with a traumatic head injury. Israeli children with a traumatic head injury were compared with their non-injured counterparts. Each group included 18 children (12 males) ages 7-13. Measurements included reading the mind in the eyes, facial emotion recognition, reasoning the other's characteristics based on motive and outcome, Raven's Coloured Progressive Matrices, similarities and digit span (Wechsler Intelligence Scale for Children - Revised 95 subscales), verbal fluency, and the Behaviour Rating Inventory of Executive Functions. Non-injured children performed significantly better on ToM, abstract reasoning, and EF measures compared with children with a traumatic head injury. However, differences in ToM abilities between the groups were no longer significant after controlling for abstract reasoning, working memory, verbal fluency, or facial emotion recognition. Impaired ToM recognition and reasoning abilities after a head injury may result from other cognitive impairments. In children with mild and moderate head injury, poorer performance on ToM tasks may reflect poorer abstract reasoning, a general tendency to concretize stimuli, working memory and verbal fluency deficits, and difficulties in facial emotion recognition, rather than deficits in the ability to understand the other's thoughts and emotions. ToM impairments may be secondary to a range of cognitive deficits in determining social outcomes in this population.
In early May, a press release from Harrisburg University claimed that two professors and a graduate student had developed a facial-recognition program that could predict whether someone would be a criminal. The release said the paper would be published in a collection by Springer Nature, a big academic publisher.
A Google engineer, Blaise Aguera y Arcas, blasted the original study early last year, and pointed out various reasons why software should struggle or fail to classify human sexuality correctly. He believed neural networks were latching onto things like whether a person was wearing certain makeup or a particular fashion of glasses to determine sexual orientation, rather than using their actual facial structure.
And guess what? The software was still able predict sexual orientation. In fact, it was accurate about 63 per cent for males and 72 per cent for females, pretty much on par with the non-blurred VGG-Face and facial morphology model.
"Not just color as we know it but it could be differences in the brightness or saturation of the images. The CNN may well be generating features that capture these types of differences. The facial morphology classifier on the other hand is very unlikely to contain this type of signal in its output. It was trained to accurately find the positions of the eyes, nose, [or] mouth."
Also in 2017, Thiel was one of the first outside investors in Clearview AI, a facial recognition technology startup that has raised concerns in the tech world and media for its risks of weaponization.[71][72]
Despite the concerns over privacy, face recognition technology offers a wealth of possibilities that no one can ignore. The facial recognition market is expected to reach $6.84 billion in value by 2021, according to data compiled by the MarketsandMarkets research company: twice the $3.35 billion it was worth last year.
Bodycams are just one way that what officers on the street can see, store and search is changing. These new technologies help in investigations and also offer benefits such as accountability. They make it more difficult for police and citizens to lie about contested encounters, or whether a person or car was at the scene of a specific incident. Yet they are still controversial. Evidence of whether bodycams reduce bad behaviour by police officers is ambiguous. And the potential for abuse of facial-recognition technology is vast, allowing, as it does, real-time deep surveillance.
ANPRs raise concerns similar to those about facial-recognition databases. Police drive around, collecting and storing images of number plates registered to people not suspected of any crime. Vigilant Solutions, an ANPR firm, has a database of at least 7bn data points from number plates, most of which presumably belong to the innocent. If they become suspects, police can then trawl through ANPR data to create detailed portraits of their lives.
Such vigilance must extend to the sellers of these systems as well as their users. Some regimes have embraced emerging technologies the better to control and surveil people: China, for instance, has blanketed its restive regions of Xinjiang and Tibet with facial-recognition cameras, iris scanners and other such kit. In January the European Parliament, following popular concern, imposed export controls on surveillance technology that regimes can use to spy on citizens.
Is this A.I. okay to use? Google announced last week the creation of an advisory council to provide perspective about using A.I. technologies like facial-recognition software ethically. The council, which will meet four times annually, is made up of outside experts from fields like public policy, foreign policy, privacy, and computer science. Since the announcement, Bloomberg News reported that the council has faced some setbacks, including one council member dropping out for unspecified reasons and a group of over 300 Google employees publicly petitioning for the removal of another member who has "fought against equal-rights laws for gay and transgender people."
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