Everyone should have the right to protest. And, if done legally, to do so without fear of having things like their future job prospects ruined because they’ve been snapped at a demonstration – from which a select few may have gone on to do criminal acts such as arson and looting.

With images from the protests being widely shared on social media to raise awareness, police have been using the opportunity to add the people featured within them to facial recognition databases.

“Over the past weeks, we have seen an increasing number of arrests at BLM protests, with images circulating around the web enabling automatic identification of those individuals and subsequent arrests to hamper protest activity,” the researchers explain.

Software has been available for some time to blur faces, but recent AI advancements have proved that it’s possible to deblur such images.

Researchers from Stanford Machine Learning set out to develop an automated tool which prevents the real identity of those in an image from being revealed.

The result of their work is BLMPrivacyBot:

Rather than blur the faces, the bot automatically covers them up with the black fist emoji which has become synonymous with the Black Lives Matter movement. The researchers hope such a solution will be built-in to social media platforms, but admit it’s unlikely.

The researchers trained the model for their AI bot on a dataset consisting of around 1.2 million people called QNRF. However, they warn it’s not foolproof as an individual could be identified through other means such as what clothing they’re wearing.

To use the BLMPrivacyBot, you can either send an image to its Twitter handle or upload a photo to the web interface here. The open source repo is available if you want to look at the inner workings.

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Clearview AI has repeatedly made headlines, and rarely for good reason. The company’s facial recognition technology is impressive but relies on scraping billions of people’s data from across the web.

“Common law has never recognised a right to privacy for your face,” Clearview AI lawyer Tor Ekeland argued recently.

Regulators in the UK and Australia seem to have a different perspective than Ekeland and have announced a joint probe into Clearview AI’s practices.

“The Office of the Australian Information Commissioner (OAIC) and the UK’s Information Commissioner’s Office (ICO) have opened a joint investigation into the personal information handling practices of Clearview Inc., focusing on the company’s use of ‘scraped’ data and biometrics of individuals,” the ICO wrote in a statement.

“The investigation highlights the importance of enforcement cooperation in protecting the personal information of Australian and UK citizens in a globalized data environment.”

A similar probe was launched by the EU’s privacy watchdog last month.

The European Data Protection Board ruled that any use of the service by law enforcement in Europe would “likely not be consistent with the EU data protection regime” and that it “has doubts as to whether any Union or Member State law provides a legal basis for using a service such as the one offered by Clearview AI.”

Clearview AI’s facial recognition system is used by over 2,200 law enforcement agencies around the world. A recent leak suggests it’s even being used by commercial businesses like Best Buy and Macy’s. In May, Clearview said it would stop working with non–law enforcement entities.

The American Civil Liberties Union (ACLU) launched a lawsuit against Clearview AI in May after calling it a “nightmare scenario” for privacy.

Aside from the company’s practices, concerns have been raised about Clearview AI’s extensive ties with the far-right. Ekeland himself has gained notoriety as “The Troll’s Lawyer” for defending clients such as neo-Nazi troll Andrew Auernheimer.

“Companies like Clearview will end privacy as we know it, and must be stopped,” said Nathan Freed Wessler, senior staff attorney with the ACLU’s Speech, Privacy, and Technology Project.

(Photo by The Creative Exchange on Unsplash)

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“If we would use the software only [for subject identification], we would not solve the case 95-97 percent of the time,” Craig said. “If we were just to use the technology by itself to identify someone, I would say 96 percent of the time it would misidentify.”

Craig’s comments arrive just days after the ACLU (American Civil Liberties Union) lodged a complaint against the Detroit police following the harrowing wrongful arrest of black male Robert Williams due to a facial recognition error.

Detroit Police arrested Williams for allegedly stealing five watches valued at $3800 from a store in October 2018. A blurry CCTV image was matched by a facial recognition algorithm to Williams’ driver’s license photo.

Current AI algorithms are known to have a racism issue. Extensive studies have repeatedly shown that facial recognition algorithms are almost 100 percent accurate when used on white males, but have serious problems when it comes to darker skin colours and the fairer sex.

This racism issue was shown again this week after an AI designed to upscale blurry photos, such as those often taken from security cameras, was applied to a variety of people from the BAME communities.

Here’s a particularly famous one:

🤔🤔🤔 pic.twitter.com/LG2cimkCFm

— Chicken3gg (@Chicken3gg) June 20, 2020

And some other examples:

Last week, Boston followed in the footsteps of an increasing number of cities like San Francisco, Oakland, and California in banning facial recognition technology over human rights concerns.

“Facial recognition is inherently dangerous and inherently oppressive. It cannot be reformed or regulated. It must be abolished,” said Evan Greer, deputy director of the digital rights group Fight for the Future.

Over the other side of the pond, facial recognition tests in the UK so far have also been nothing short of a complete failure. An initial trial at the 2016 Notting Hill Carnival led to not a single person being identified. A follow-up trial the following year led to no legitimate matches but 35 false positives.

An independent report into the Met Police’s facial recognition trials, conducted last year by Professor Peter Fussey and Dr Daragh Murray, concluded that it was only verifiably accurate in just 19 percent of cases.

The next chilling step for AI in surveillance is using it to predict crime. Following news of an imminent publication called ‘A Deep Neural Network Model to Predict Criminality Using Image Processing,’ over 1000 experts signed an open letter last week opposing the use of AI for such purposes.

“Machine learning programs are not neutral; research agendas and the data sets they work with often inherit dominant cultural beliefs about the world,” warned the letter’s authors.

The acknowledgement from Detroit’s police chief that current facial recognition technologies do not work in around 96 percent of cases should be reason enough to halt its use, especially for law enforcement, at least until serious improvements are made.

(Photo by Joshua Hoehne on Unsplash)

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While it’s been suspected that documented racial bias with facial recognition algorithms has led to false arrests, it’s been difficult to prove.

On Wednesday, the ACLU lodged a complaint against the Detroit police after black male Robert Williams was arrested on his front lawn “as his wife Melissa looked on and as his daughters wept from the trauma”. Williams was held in a “crowded and filthy” cell overnight without being given any reason.

Detroit Police arrested Williams for allegedly stealing five watches valued at $3800 from a store in October 2018. A blurry CCTV image was matched by a facial recognition algorithm to Williams’ driver’s license photo.

During an interrogation the day after his arrest, the police admitted that “the computer must have gotten it wrong”. Williams was kept incarcerated until after dark “at which point he was released out the front door, on a cold and rainy January night, where he was forced to wait outside on the curb for approximately an hour while his wife scrambled to find child care for the children so that she could come pick him up.”

Speaking to the NY Times, a Detroit police spokesperson said the department “does not make arrests based solely on facial recognition,” and claims witness interviews and a photo lineup were used.

However, a response from the Wayne County prosecutor’s office confirms the department used facial recognition to identify Williams using the security footage and an eyewitness to the crime was not shown the alleged photo lineup.

In its complaint, the ACLU demands that Detroit police end the use of facial recognition “as the facts of Mr. Williams’ case prove both that the technology is flawed and that DPD investigators are not competent in making use of such technology.”

This week, Boston became the latest city to ban facial recognition technology for municipal use. Boston follows an increasing number of cities like San Francisco, Oakland, and California who’ve banned the technology over human rights concerns.

“Facial recognition is inherently dangerous and inherently oppressive. It cannot be reformed or regulated. It must be abolished,” said Evan Greer, deputy director of the digital rights group Fight for the Future.

“Boston just became the latest major city to stop the use of this extraordinary and toxic surveillance technology. Every other city should follow suit.”

Cases like Mr Williams’ are certainly strengthening such calls. Over 1,000 experts signed an open letter this week against the use of AI for the next chilling step, crime prediction.

(Photo by ev on Unsplash)

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Anyone who has watched the sci-fi classic Minority Report will be concerned about attempts to predict crime before it happens. In an ideal scenario, crime prediction could help determine where to allocate police resources – but the reality will be very different.

The researchers are speaking out ahead of an imminent publication titled ‘A Deep Neural Network Model to Predict Criminality Using Image Processing’. In the paper, the authors claim to be able to predict whether a person will become a criminal based on automated facial recognition.

“By automating the identification of potential threats without bias, our aim is to produce tools for crime prevention, law enforcement, and military applications that are less impacted by implicit biases and emotional responses,” says Harrisburg University Professor and co-author of the paper Nathaniel J.S. Ashby.

“Our next step is finding strategic partners to advance this mission.”

Finding willing partners may prove to be a challenge. Signatories of the open letter include employees working on AI from tech giants including Microsoft, Google, and Facebook.

In their letter, the signatories highlight the many issues of today’s AI technologies which make dabbling in crime prediction so dangerous.

Chief among the concerns is the well-documented racial bias of algorithms. Every current facial recognition system is more accurate when detecting white males and often incorrectly flags members of the BAME community as criminals more often when used in a law enforcement setting.

However, even if the inaccuracies with facial recognition algorithms are addressed, the researchers highlight the problems with the current justice system which have been put in the spotlight in recent weeks following the murder of George Floyd.

In their letter, the researchers explain:

“Research of this nature — and its accompanying claims to accuracy — rest on the assumption that data regarding criminal arrest and conviction can serve as reliable, neutral indicators of underlying criminal activity. Yet these records are far from neutral.

As numerous scholars have demonstrated, historical court and arrest data reflect the policies and practices of the criminal justice system. These data reflect who police choose to arrest, how judges choose to rule, and which people are granted longer or more lenient sentences.

Countless studies have shown that people of color are treated more harshly than similarly situated white people at every stage of the legal system, which results in serious distortions in the data. Thus, any software built within the existing criminal legal framework will inevitably echo those same prejudices and fundamental inaccuracies when it comes to determining if a person has the ‘face of a criminal.’”

Among the co-authors of the disputed paper is Jonathan W. Korn, a Ph.D. student who is highlighted as an NYPD veteran. Korn says that AI which can predict criminality would be “a significant advantage for law enforcement agencies.”

While such a system would make the lives of law enforcement officers easier, it would do so at the cost of privacy and the automation of racial profiling.

“Machine learning programs are not neutral; research agendas and the data sets they work with often inherit dominant cultural beliefs about the world,” warn the letter’s authors.

“The uncritical acceptance of default assumptions inevitably leads to discriminatory design in algorithmic systems, reproducing ideas which normalise social hierarchies and legitimise violence against marginalised groups.”

You can find the full open letter here.

(Photo by Bill Oxford on Unsplash)

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Clearview AI’s facial recognition system is used by over 2,200 law enforcement agencies around the world and even commercial businesses like Best Buy and Macy’s, according to a recent leak.

The EDPB has now ruled that any use of the service by law enforcement in Europe would “likely not be consistent with the EU data protection regime.”

Furthermore, the watchdog “has doubts as to whether any Union or Member State law provides a legal basis for using a service such as the one offered by Clearview AI.”

Clearview AI scrapes billions of photos from across the internet for its powerful system, a practice which has come under fire by privacy campaigners. “Common law has never recognised a right to privacy for your face,” Clearview AI lawyer Tor Ekeland argued recently.

The American Civil Liberties Union (ACLU) launched a lawsuit against Clearview AI last month after calling it a “nightmare scenario” for privacy.

“Companies like Clearview will end privacy as we know it, and must be stopped,” said Nathan Freed Wessler, senior staff attorney with the ACLU’s Speech, Privacy, and Technology Project.

Aside from the company’s practices, concerns have been raised about Clearview AI’s extensive ties with the far-right. Ekeland himself has gained notoriety as “The Troll’s Lawyer” for defending clients such as neo-Nazi troll Andrew Auernheimer.

Backlash over Clearview AI forced the company to announce it will no longer offer its services to private companies. The EU’s ruling will limit Clearview AI’s potential customers even further.

Concerns have grown in recent weeks about facial recognition services amid protests over racial discrimination. Facial recognition services have been repeatedly found to falsely flag minorities; stoking fears they’ll lead to automated racial profiling.

IBM and Amazon have both announced this week they’ll no longer provide facial recognition services to law enforcement and have called on Congress to increase regulation to help ensure future deployments meet ethical standards.

(Photo by Christian Lue on Unsplash)

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“Companies like Clearview will end privacy as we know it, and must be stopped,” said Nathan Freed Wessler, senior staff attorney with the ACLU’s Speech, Privacy, and Technology Project.

“The ACLU is taking its fight to defend privacy rights against the growing threat of this unregulated surveillance technology to the courts, even as we double down on our work in legislatures and city councils nationwide.”

Clearview AI has repeatedly come under fire due to its practice of scraping billions of photos from across the internet and storing them in a database for powerful facial recognition services.

“Common law has never recognised a right to privacy for your face,” Clearview AI lawyer Tor Ekeland said recently.

The company’s facial recognition system is used by over 2,200 law enforcement agencies around the world – and even commercial businesses like Best Buy and Macy’s, according to a recent leak.

In a press release, the ACLU wrote:

“The New York Times revealed the company was secretly capturing untold numbers of biometric identifiers for purposes of surveillance and tracking, without notice to the individuals affected.

The company’s actions embodied the nightmare scenario privacy advocates long warned of, and accomplished what many companies — such as Google — refused to try due to ethical concerns.”

However, even more concerning is Clearview AI’s extensive ties with the far-right.

Clearview AI founder Hoan Ton-That claims to have since disassociated from far-right views, movements, and individuals. Ekeland, meanwhile, has gained notoriety as “The Troll’s Lawyer” for defending clients such as neo-Nazi troll Andrew Auernheimer.

The ACLU says its lawsuit represents the first “to force any face recognition surveillance company to answer directly to groups representing survivors of domestic violence and sexual assault, undocumented immigrants, and other vulnerable communities uniquely harmed by face recognition surveillance.”

Facial recognition technologies have become a key focus for the ACLU.

Back in March, AI News reported the ACLU was suing the US government for blocking a probe into the use of facial recognition technology at airports. In 2018, the union caught our attention for highlighting the inaccuracy of Amazon’s facial recognition algorithm – especially when identifying people of colour and females.

“Clearview’s actions represent one of the largest threats to personal privacy by a private company our country has faced,” said Jay Edelson of Edelson PC, lead counsel handling this case on a pro bono basis.

“If a well-funded, politically connected company can simply amass information to track all of us, we are living in a different America.”

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The Australian Federal Police (AFP) admitted to using Clearview AI’s system despite not having a legislative framework in place for the technology.

Deputy commissioner Karl Kent said that the AFP trialled the facial recognition system but has not entered any formal arrangements with Clearview AI to procure their technology.

In a statement, opposition party Labor called for Home Affairs Minister Peter Dutton to explain whether the AFP’s investigations into child exploitation were jeopardised by the use of Clearview AI’s technology without legal authorisation:

“Peter Dutton must immediately explain what knowledge he had of Australian Federal Police officers using the Clearview AI facial recognition tool despite the absence of any legislative framework in relation to the use of identity-matching services.”

Clearview AI’s facial recognition was used specifically by the AFP-led Australian Centre to Counter Child Exploitation (ACCCE) to support their vital work.

“The trial was to assess the capability of the Clearview AI system in the context of countering child exploitation,” wrote the AFP.

ACCCE’s testing took place between 2nd November 2019 and 22nd January 2020.

“Searches included images of known individuals, and unknown individuals related to current or past investigations relating to child exploitation,” the AFP said. “Outside of the ACCCE Operational Command there was no visibility that this trial had commenced.”

Clearview AI’s facial recognition has come under stiff opposition due to its controversial practices and extensive links to the far-right.

Hoan Ton-That, founder of Clearview AI, claims to have disassociated from far-right views, movements, and individuals. Ton-That told Huffington Post recently that growing up on the internet did not “serve him well” and “there was a period when I explored a range of ideas—not out of belief in any of them, but out of a desire to search for self and place in the world.”

Clearview AI’s facial recognition system uses a large database consisting of billions of scraped images from across the web. Activists believe the system infringes on people’s right to privacy as they never gave permission for their images to be stored and used in such a way.

“Common law has never recognised a right to privacy for your face,” Clearview AI lawyer Tor Ekeland said recently. “It’s kind of a bizarre argument to make because [your face is the] most public thing out there.”

(Photo by Joey Csunyo on Unsplash)

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Met Commissioner Cressida Dick was speaking at the Royal United Services Institute think tank on Monday. Much of Dick’s speech was spent on making the case for British police to use modern technologies to tackle crime.

Dick accused critics of police facial recognition technology as being “highly inaccurate or highly ill-informed.”

Needless to say, this angered said critics who believe Dick is the one who is ill-informed by ignoring an independent report which suggests the technology in question only works in just 19 percent of cases.

“I would say it is for critics to justify to the victims of crimes why police should not be allowed to use tech lawfully and proportionally to catch criminals,” Dick argued.

Dick says she welcomes a public debate about facial recognition but attacked organisations such as Big Brother Watch and Liberty who brought the attention to the wider public.

“It’s unhelpful for the Met to reduce a serious debate on facial recognition to unfounded accusations of ‘fake news’,” Big Brother Watch tweeted. “Dick would do better to acknowledge and engage with the real, serious concerns – including those in the damning independent report that she ignored.”

Liberty tweeted a similar response: “Fact: Met started using facial recognition after ignoring its own review of two-year trial that said its use of the tech didn’t respect human rights. Another fact: scaremongering and deriding criticisms instead of engaging shows how flimsy their basis for using it really is.”

Met Police tests of facial recognition technology so far have been nothing short of a complete failure.

An initial trial, at the 2016 Notting Hill Carnival, led to not a single person being identified. A follow-up trial the following year led to no legitimate matches but 35 false positives.

Ironically, the legality of the trials has been called into question. An independent report by Professor Peter Fussey and Dr Daragh Murray last year concluded the six trials they were given access to were probably illegal since they had not accounted for human rights compliance.

Dr Murray said: “This report raises significant concerns regarding the human rights law compliance of the trials.

“The legal basis for the trials was unclear and is unlikely to satisfy the ‘in accordance with the law’ test established by human rights law.

“It does not appear that an effective effort was made to identify human rights harms or to establish the necessity of LFR.

“Ultimately, the impression is that human rights compliance was not built into the Metropolitan Police’s systems from the outset, and was not an integral part of the process.”

You can find a copy of the full report here (PDF)

(Image Credit: Met police helmet by Matt Brown under CC BY 2.0 license)

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Thermal imaging is often used to protect privacy because it obscures personally identifying details such as eye colour. In some places, like medical facilities, it’s often compulsory to use images which obscure such details.

AI is opening up many new possibilities so Intel’s researchers set out to determine whether thermal imaging still offers a high degree of privacy.

Intel’s team used two sets of data sets:

• The first set, known as SC3000-DB, was created using a Flir ThermaCam SC3000 infrared camera. The data set features 766 images of 40 volunteers (21 women and 19 men) who each sat in front of a camera for two minutes.

• The second set, known as IRIS, was created by the Visual Computing and Image Processing Lab at Oklahoma State University. It features 4,190 images collected by 30 people and differs from the first set in that it contains various head angles and expressions. 

Each image from the data sets were first cropped to only contain each person’s face. 

A machine learning model then sought to numerically label facial features from the images as vectors. Another model, trained on VGGFace2 – a model trained on visible light images – was used to validate whether it could be applied to thermal images.

Here’s the full results for each data set:

The model trained on visible image data performed well in distinguishing among volunteers by extracting their facial features. 99.5 percent accuracy was observed for the SC3000-DB data set and 82.14 percent for IRIS.

Intel’s research shows that thermal imaging may not offer the privacy that many currently believe it to and it’s already possible to distinguish people using it.

“Many promising visual-processing applications, such as non-contact vital signs estimation and smart home monitoring, can involve private and or sensitive data, such as biometric information about a person’s health,” wrote the researchers.

“Thermal imaging, which can provide useful data while also concealing individual identities, is therefore used for many applications.”

You can find Intel’s full research here.

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