On June 22, Western Australian police became the nation’s first law enforcement agency to use live facial recognition technology to find persons of interest. The trial involves a clearly marked van with cameras driving around Perth and Mandurah. It scans the faces of everyone it passes, comparing them against a watchlist of about 4,000 people. It includes those with outstanding arrest warrants, reportable offenders, people subject to lawful exclusion orders, and missing persons. The exercise is overt and widely publicised, with the dates of deployments posted in advance. In its first week, media reports put the trial at more than 130,000 faces scanned and 33 alerts. It led to 18 arrests, along with engagements with registered sex offenders. Work that would have taken weeks of conventional investigative effort has been done in days by a single van. But harder questions surround its governance. Can we really call it a “trial”? Who gets to authorise such deployments? And who checks the safeguards? Can we actually call it a ‘trial’? Any trial of new technology requires success criteria defined in advance, independent evaluation, and the possibility the technology won’t be deployed on a permanent basis after the trial completes. That’s not what seems to be happening in WA. WA police both runs the deployment and compiles the results it publishes, and no independent evaluator has been named. Its own privacy impact assessment says funding is not yet determined, and lists event security among the intended uses. Arrests are an incomplete measure of success, because everyone arrested was already wanted. These are not crimes solved, but simply a known watchlist being worked through more quickly. And an arrest count only records the hits, not the misses. What remains undisclosed is the human cost – any innocent people the system might misidentify and send
Aug 12, 2026 · via theconversation.com
A camera and its software labeled Bill Swearingen as a person. Then it suddenly wasn’t sure — all because of some weird pattern that he held up to disguise himself. I watched it happen from my seat at annual hacker convention Defcon. Swearingen, a longtime cybersecurity professional and founder of the Kansas City security community SecKC, stood onstage in front of a live camera feed as a person-detection system analyzed him. On the giant screen behind him, the software’s confidence score cleared 0.75, the threshold it needed to declare that, yes, there was a human being in the frame. Then Swearingen raised a flat panel covered in a bizarre black-and-white pattern. The score started falling. It slipped below the threshold, eventually landing at 0.21. “No person detected,” the screen announced in bright green letters. It felt like a low-budget magic trick. Swearingen was still standing there, plainly visible to everyone in the room. The software was still receiving the camera image, but it no longer detected a person above the configured confidence threshold. Swearingen has spent the past year searching for patterns that can confuse the computer-vision systems used to identify people. His project is called noRecognition, and its end goal is to create clothing that makes the wearer harder for AI surveillance systems to detect. It’s a fascinating project, but it’s still a work in progress. The camera wasn’t trying to identify him We tend to call this kind of technology “facial recognition,” but surveillance systems can involve several separate layers of AI-based detection. A person detector asks whether a human body is in the frame. A face detector finds and isolates a face. Facial recognition then compares that face with a database and asks whether it knows who the person is. The demonstration I saw targeted the first
Aug 12, 2026 · via cnet.com
ERWIN, N.C. (WTVD) -- The debate over Flock surveillance cameras is intensifying in Harnett County, as citizens and law enforcement clash over the balance between public safety and personal privacy. When the topic came up on a local Facebook group, Erwin resident Mary Henkes says the response was immediate and loud. "When it was brought up on our Facebook group, it just blew up. What, no, we don't want those here. Get them out of here," Henkes recalled. For drivers passing through Erwin, the cameras are easy to miss. Yet, 11 Flock cameras now monitor busy intersections and the town's main entrances, quietly scanning every passing car. The Flock system captures still images of vehicles, recording color, make, and model, and can alert police if a car is reported stolen, a tag matches a wanted person, or a missing individual is in the area. Not everyone is on board. "I don't like it," Henkes said, noting her discomfort with the cameras watching daily comings and goings. She's lived in Erwin for 21 years and questions the need for such technology in rural areas. "I can see having them maybe in a few places, maybe strategic places, but way out here in the country, on country back roads and things, I don't really see a need for it," she said. Another resident, Nashia Ray, echoed those concerns: "I have one, like, right directly close to my kids' daycare. Take them down or just don't make any more," she said. With just 11 officers on staff, Erwin Police Chief Jonathan Johnson says the cameras are a necessary tool in a small department's arsenal. "I know the concerns, you know, and we've got some pretty strict policies in place," Johnson said. Johnson says the department audits camera usage weekly, and Flock's own system
Aug 12, 2026 · via abc11.com
In brief - Bill Swearingen’s noRecognition project generates patterns that stop camera software from classifying what it covers—people, faces, or cars. - The patterns defeated all 11 open-source detection algorithms he tested, including the software behind Flock license plate readers, Axon body cameras, and Clearview AI. - The first public test came Friday at Def Con in Las Vegas: a 2009 Toyota Yaris wrapped in the pattern, driven past a Flock camera. Bill Swearingen spent the past year running one experiment over and over from his home in Kansas City, where he co-founded the SecKC security meetup. About 31 million tests later, he says he can produce patterns on demand that hide whatever they cover from the detection software wired into Flock cameras—the controversial surveillance system being rolled out across America. He showed it in public for the first time Friday at Def Con, working with the YouTube channel Donut Media to cover a 2009 Toyota Yaris in one of his newest patterns and roll it past a Flock camera. “We proved it was effective,” Swearingen told TechCrunch, though he said the wheels were a challenge. Donut Media said video of the demo lands in the next few weeks. The pattern doesn’t blind the camera. Footage still records normally, and a human watching the screen sees a car. What breaks is the layer on top—the object-detection model that decides “that’s a vehicle, that’s a plate, log it.” So basically, feed an AI detector with enough visual noise engineered against its own math and it logs nothing. The car goes back to being a needle in a haystack. That’s adversarial machine learning, and it works because computer vision doesn’t see what you see. A wrap that reads as loud graphic design to a person can read as nothing at all to
Aug 12, 2026 · via decrypt.co
NORTH PORT — The North Port Police Department is seeking a contract with a facial recognition software firm to help in investigations. The software uses artificial intelligence. On Tuesday, a notice of intent to acquire facial recognition software from Clearview AI was announced by the city of North Port in an email. The cost of the service, according to the announcement, is $11,400 for the first year. The second year’s rate is $28,500. Clearview AI, according to its website, is an “American technology company that provides a powerful facial recognition search engine primarily to law enforcement and government agencies.” More than 3,100 law enforcement agencies across the globe use the service, according to the Clearview website. “Clearview AI works by matching an uploaded photo of a face against a massive database of tens of billions of publicly available images scraped from social media, news sites, and the internet,” Clearview AI’s website states. “It converts facial features into unique mathematical vectors to find similar matches within seconds.” Some residents saw the news about the intention of NPPD to acquire the new service and voiced concerns on social media. Concerns over surveillance has become prevalent with the subject of Flock cameras, for example, growing in popularity. The city of North Port does not have Flock cameras; however, it does have other types of cameras across the municipality. NPPD Deputy Chief Chris Morales said facial recognition software is not uncommon, and Clearview is an investigative tool used by law enforcement when a surveillance photo of a person cannot be made out. Clearview, he said, can be used to find characteristics of a person being investigated. Morales said NPPD is not “actively” using the software, but is using it “reactively.” The same practice, according to Morales, is used for surveillance cameras in the city.
Aug 12, 2026 · via yoursun.com
Police are set to deploy live facial recognition technology in Southend later this week as part of continued efforts to tackle crime and keep people safe.
Essex Police confirmed the vans will be in operation on Friday, August 14, and Saturday, August 15, alongside officers visible across the city.
The technology will be used to identify people suspected of serious offences, including drug, violent and sexual crime, as well as theft and breaches of court orders.
Officers say the system has already led to more than 170 arrests in connection with investigations.
Read more:
A spokesman for Essex Police said: "As part of our work to keep you safe and tackle crime in Southend we’ll be visible in the city this weekend.
"We have an obligation to make the public aware of a deployment before it takes place which is why we're letting you know."
Images of those not on police watchlists are deleted almost instantly.
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Aug 12, 2026 · via echo-news.co.uk
San Francisco Bars Reverse Course on Face Scanning Machines at Bars After Community Concerns Around 2,000 people had signed a petition calling out the face-scanning technology. A couple of bars in San Francisco’s legendary Castro neighborhood, which had been using facial-scanning machines, have announced they’ll stop doing so after backlash from the local LGBTQ+ community. Back in June, at least three bars in the historically LGBTQ+ district were using something called a Patronscan Guard+, which is a device by a Canadian company that collects biometric and personal data. The devices collect names, addresses, genders, and patron behavior. That data is then stored in a database and shared within a network of subscribers. “We have heard the concerns regarding the use of PatronScan at Badlands and Toad Hall in San Francisco, and we are listening,” Toad Hall announced on Instagram. “Effective immediately, we are pausing the use of PatronScan while we review our ID verification and security practices.” The devices had caused some bar patrons to be concerned about their privacy. “I was just kind of taken aback,” Har Owen told local outlet Gazetteer SF after going to one of the bars on Memorial Day weekend. “Why is this at a gay bar, of all places?” She explained that at this political moment, “it’s really not great to have lists of gay people.” A petition on Fight for the Future against the technology in the Castro bars had gathered around 2,000 signatures, according to SF Gate. “LGBTQ+ venues that use biometric surveillance technology, including facial recognition, must remove it, scrap the data, and apologize to their patrons. All others should commit to keeping their community safe by rejecting surveillance technology—now and forever,” the petition states. A spokesperson from Patronscan told SF Gate that they do not use facial recognition technology but
Aug 12, 2026 · via gomag.com
ICE seeks expanded LexisNexis investigative data access with Palantir integration ICE intends to award LexisNexis Risk Solutions a sole-source contract worth an estimated $6.7 million to continue supplying investigative data services to thousands of agency users and feed commercial identity data into ICE applications, including Palantir. The August 10 notice of intent describes a short-term bridge contract covering a seven-month base period and five one-month options. ICE says only LexisNexis can provide continued access to its LexID identity-resolution technology and Accurint Virtual Crime Center within the time available. While structured as a bridge contract, the accompanying procurement documents show ICE is seeking considerably more than continued access to a commercial investigative database. The requirements describe an enterprise investigative platform that integrates commercial identity data with agency analytics through APIs, expands identity resolution capabilities and introduces broader AI and facial recognition requirements, pointing to the agency’s longer-term technical direction. The notice is not an executed contract or a competitive solicitation. Other companies have until August 14 to submit capability statements challenging ICE’s conclusion that LexisNexis is the only responsible source. A July 22 Performance Work Statement (PWS) was attached to ICE’s August 10 notice for a planned interim Law Enforcement Investigative Database Subscription contract. A DHS acquisition forecast identifies the procurement as a follow-on to LexisNexis contract 70CMSD21C00000001, which is scheduled to expire August 31. The PWS is not a modification of that contract but sets out requirements ICE associated with its proposed successor acquisition. Those requirements show that ICE is seeking considerably more than access to a stand-alone commercial database. The system must connect through application programming interfaces, or APIs, to ICE applications “such as but not limited to” the Palantir platform, PenLink and ICE Data Analytics. It must also provide a system-to-system connection making public and proprietary data available
Aug 12, 2026 · via biometricupdate.com
Facial detection technologies have gone from commonplace to near-ubiquitous in major cities, prompting some privacy researchers to look for ways to thwart them. Hacker and former CISO Bill Swearingen's noRecognition project can now generate patterns that hide a wearer from cameras, making them useful for t-shirts, face coverings, hats, and other garments to help maintain your privacy. People have been using makeup and specific clothing patterns to trick smart cameras for years, but with improvements in AI and image recognition, this has grown increasingly difficult. The noRecognition project wants to both enhance these apparel countermeasures and make them more readily available, hence the crowdfunding campaign. "Privacy is a fundamental right," Swearingen told TechCrunch, saying he wanted people to be able to opt out of being tracked with something as simple as a choice of clothing. These patterns will be sold in two different tiers: Standard and One of One. The former will include the mainstream patterns the project generates, giving you broad-spectrum coverage against detection by security and surveillance systems. However, it's possible that AI developers will one day buy these prints and train their models to track them, making them less useful as protective measures. One of One, however, will only be sold in extremely limited numbers: 50 of each pattern across the various clothing options. Once those 50 are sold, that pattern will never be sold again, in theory, making it almost impossible for an AI model developer to use it for training, as its supply and use would be too limited. Swearingen is also releasing his team's numbers to keep the campaign honest. You can see which vision systems the patterns were tested against, how well they work when worn by different people with different builds and facial structures, and dig into the research they've conducted over
Aug 12, 2026 · via extremetech.com
Face recognition cameras to scan Oxford Street, Sadiq Khan suggests The technology is expected to be expanded from the West End in a crackdown on street crime by the Met Previous Article Next Article
Aug 12, 2026 · via thetimes.com
Facial recognition helps Hyderabad Police identify eight offenders during Bonalu
Hyderabad Police detained 116 suspicious persons during the Lal Darwaza Bonalu celebrations on August 9 and 10. Facial recognition technology helped identify eight people with previous criminal records, while no theft, mobile phone theft or chain-snatching cases were reported.
Updated On - 12 August 2026, 01:42 PM
Hyderabad: The Hyderabad Police detained 116 suspicious persons during the Lal Darwaza Bonalu celebrations held on August 9 and 10, with facial recognition technology helping identify eight people with previous criminal records.
The CCS Special Crime Team and local police used facial recognition cameras linked to the criminal database as part of intensified surveillance to prevent pickpocketing, mobile theft and chain-snatching.
According to Additional CP (Crimes & SIT) M Srinivas, the eight identified offenders were handed over to the concerned police stations for further action.
Police said no theft, mobile phone theft or chain-snatching cases were reported during the two-day celebrations.
Aug 12, 2026 · via telanganatoday.com
The courts have been grappling with the use of artificial intelligence (AI) in litigation as its adoption has accelerated in recent years. Practitioners who have filed material containing hallucinated references have been sanctioned by the judiciary, and several jurisdictions have now published formal guidelines regulating the intersection of AI and the law. A 2025 UNSW report found 520 instances of generative AI misuse in legal proceedings across ten jurisdictions between January 2023 and September 2025, including 87 Australian cases, the majority of which involved self-represented litigants. While these cases have led to judicial frustration and court delays, they do not appear to have caused significant personal injustice or irrevocable damage to the parties involved in the legal proceedings. What will happen when AI tools cause real damage? A deepfake is an AI-generated video, image or recording that convincingly emulates a person's appearance or voice. Deepfakes are created using advanced machine learning and make it appear that a person is saying or doing things they never actually did. There are thousands of open-source platforms capable of generating deepfake content. This material can be produced easily, at little to no cost, and at scale. Lawyers and the courts need to consider the impact this may have on the way evidence is treated in litigation and the psychological and procedural burdens it may cause to individuals. When digital evidence can no longer be taken at face value The risk of fabricated evidence is not new. Litigants, practitioners and courts alike have historically encountered allegations of forged signatures, altered documents and manipulated records, and have relied on expert examinations, subpoenas and corroborating evidence to test their authenticity. The challenge today is that AI has made it easier, cheaper and more convincing than ever before. As synthetic content becomes increasingly realistic, distinguishing genuine evidence from
Aug 12, 2026 · via landers.com.au
FORM, the retail execution software company behind GoSpotCheck, has been named to the 2026 Inc. 5000 as it expands its artificial intelligence capabilities and international footprint following its merger with Trax. The recognition comes during a significant year for FORM as it combines GoSpotCheck’s retail execution capabilities with Trax’s image recognition technology. The company serves retailers, consumer packaged goods companies, food and beverage brands and distributors seeking greater visibility into how products are displayed, stocked and executed at the store level. FORM’s growth reflects a broader shift in retail technology toward using AI, computer vision and mobile software to connect corporate merchandising strategies with conditions inside individual stores. For brands managing thousands of products across large retail networks, gaps between planned and actual execution can affect product availability, promotional performance and sales. “2026 has already been a landmark year for FORM,” CEO Ali Moosani said. He pointed to the Trax merger, international expansion and product development combining augmented reality and AI as key developments shaping the company’s strategy. The Trax combination gives FORM a broader technology portfolio at a time when retail execution platforms are moving beyond task management toward automated analysis of physical store environments. Image recognition can help companies identify products and shelf conditions, while mobile workflows give field teams a way to act on that information. FORM’s GoSpotCheck platform uses AI and augmented reality to support frontline retail teams. Its capabilities are designed to improve on-shelf availability, monitor planogram compliance and help field employees identify and address execution problems. The company also offers FORM OpX, while the addition of Trax’s image recognition technology expands its ability to collect and interpret information from physical retail environments. Together, those products position FORM across both the intelligence and execution sides of frontline operations. That combination is increasingly relevant as retailers
Aug 12, 2026 · via citybiz.co
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Aug 11, 2026 · via youtube.com
- DHS has approved Helix surveillance platform for use by Secret Service - USSS conducted a privacy impact assessment to compare privacy risks versus advantages of the platform - DHS has reported a decrease in PIA releases in 2026, despite being a prerequisite for deploying surveillance technology The Department of Homeland Security has approved a new Secret Service surveillance platform even as the agency’s broader pace of privacy impact assessments has slowed significantly this year, FedScoop reported Friday. The system, known as Helix, pulls together video feeds, facial recognition capabilities and license plate reader data drawn from cameras at protected sites and existing image databases. The platform is used by Secret Service personnel to watch for potential threats near sensitive locations, including the White House complex and the area surrounding the Capitol. Don’t miss your chance to sit down with DHS leadership as the department navigates a record 65-percent budget boost and reshapes its artificial intelligence, cyber and border security priorities. Save your seat at the 2026 Homeland Security Summit on November 10, when top agency voices and industry leaders will map out exactly where the next wave of opportunity is headed. Why Was the PIA for the Helix Platform Necessary? In its privacy impact assessment, the Secret Service explained that Helix’s ability to link identifiable information — including video imagery, facial data, biometric templates, and license plate numbers tied to time and location — created a greater privacy risk than any of the underlying data sources posed on their own, making a formal review necessary. A Secret Service spokesperson characterized Helix as part of the agency’s ongoing modernization efforts rather than an entirely new capability, though the agency declined to specify when the platform was first put into use, citing operational security around its protective mission. What Do Privacy
Aug 11, 2026 · via executivegov.com
Large language models guess well and explain poorly. Rule-based systems explain perfectly and struggle with messy real-world data. Neurosymbolic AI tries to get both at once, pairing a neural network’s pattern recognition with a symbolic engine’s hard logic, so a system can read a natural-language question and still get the math exactly right. Google, IBM, Amazon, and a wave of funded start-ups are already shipping it. We walk through how the architecture works, who’s building it, and what the market actually looks like once you cut through wildly different forecasts. Neurosymbolic AI combines two eras of AI research that used to run on separate tracks: neural networks and symbolic AI. Neural networks power today’s large language models and image generators, and they excel at pattern recognition, reading messy data, and producing probabilistic guesses. They also struggle with strict math, hallucinate facts, and operate as black boxes, systems that produce an answer without exposing how they got there. Symbolic AI runs the older playbook: hard-coded rules, knowledge graphs, strict logic. It delivers full accuracy and full transparency and handles math cleanly, and it falls apart on messy real-world data or natural human language. Neurosymbolic systems combine the two directly: A neural network perceives and parses messy input, a natural-language prompt included, then hands the extracted information to a symbolic logic engine that reasons through facts, runs the math, and checks the rules. The combination needs far less training data than a pure neural approach, stays explainable at every step, and holds up against hallucination whenever the task involves verifiable facts or logic. Three architectural patterns show up repeatedly. In the first, a neural model extracts structured information, objects, relations, and tokens, and passes it to a symbolic or logic engine for reasoning; large language models like the GPT family fit this
Aug 11, 2026 · via jonpeddie.com
NEW YORK--Facial recognition and liveness detection have become standard defenses against digital identity fraud, but fraud experts say a new generation of inexpensive artificial intelligence tools is rapidly eroding those protections, allowing organized criminal rings to create synthetic borrowers capable of evading detection for months—or even years. During a recent interview with BankInfoSecurity, Matt Vega, chief fraud strategist at Point Predictive, said one of the most alarming developments is the emergence of "camera injection" kits that allow criminals to bypass facial liveness checks altogether. "Facial liveness checks are the foundation for mobile device verification. But now injection kits selling for about $30 enable fraud rings to hot-wire a mobile device's camera feed or inject a deepfake stream into the verification process, bypassing checks many institutions still rely on," Vega said. Unlike earlier deepfake attacks that attempted to fool a camera by mimicking facial movements, camera injection attacks feed manipulated video directly into a device's camera pipeline, preventing many liveness detection systems from ever seeing a genuine image. According to Point Predictive's Fraud Risk Intelligence Report, these attacks have evolved rapidly from specialized hacking techniques into inexpensive commercial products marketed through Telegram channels and underground forums. Point Predictive cited reporting by MIT Technology Review, which documented dozens of online marketplaces openly selling AI-powered camera injection tools and biometric bypass software, dramatically lowering the technical expertise required to conduct sophisticated identity fraud. Criminals Are Playing The Long Game Vega told BankInfoSecurity that bypassing onboarding is only the beginning of today's fraud schemes. "Once an injection kit clears that first gate, the fraud doesn't stop at onboarding and the identity keeps building," Vega said. "Synthetic profiles typically take six to 18 months to mature, using agentic artificial intelligence to automate payments on secured cards and micro trade lines to build a healthy repayment
Aug 11, 2026 · via cutoday.info
Violent crime rates dropped in major cities this year: Reports WASHINGTON (TNND) — Violent crime rates have dropped in major cities across the U.S. this year, according to reports. The Major Cities Chiefs Association released a report on Sunday that included 66 U.S. law enforcement agencies that saw rates of homicide, rape, robbery, and aggravated assault drop overall compared to last year, The Hill reported. According to the report, homicide rates dropped 17.2%, rape dropped 6.2%, robbery by 16.6%, and aggravated assault by 5.7% from January through June. The MCCA noted that the numbers are preliminary. The Council on Criminal Justice's mid-year update last month reported similar lows, noting a continued decline starting in the second half of 2022, following a peak during the COVID-19 pandemic and Black Lives Matter protests. “There is no single or easy explanation for these historic lows,” the CCJ wrote, but listed "changes in criminal justice operations and strategies, technological advances, and broad shifts in society and culture" as possible options. Last year, U.S. violent crime rates saw the largest decrease since 1937, according to FBI nationwide crime data. Overall, violent crime decreased by about 9.3% in 2025, according to the data. Rape dropped by nearly 8%, and robbery decreased by about 18.5%, the FBI reported. Starting last year, President Donald Trump sent the National Guard and federal agencies to several major cities to crack down on crime. "Under President Trump’s leadership, we’ve been able to help deliver the most historic run of crime reduction in American history – 20% decline in the murder rate, 184% increase in violent gang takedowns, 2,700 kilos of fentanyl seized (up 56% and enough to kill 203 million Americans), and more," FBI Director Kash Patel said in June. The Department of Homeland Security has been implementing new technology to
Aug 11, 2026 · via fox17.com
Mexico’s new banking rules signal a new era for biometric identity verification By Jesús Aragón, CEO and Co-founder of Identy.io Opening a bank account today looks very different than it did a decade ago. Behind each transaction is a growing reliance on advanced identity verification technologies that help protect both customers and banks. As AI-powered fraud becomes more sophisticated, financial institutions are under pressure to strengthen identity verification without adding friction for customers. AI-driven deepfake fraud is projected to increase 495 percent in 2026 compared to 2025, highlighting how quickly fraud techniques are evolving. Rather than isolated incidents, financial institutions are confronting a broader shift in which AI enables fraud to scale more rapidly, making it increasingly difficult for traditional authentication methods to keep pace. In Mexico, that effort has taken the form of new requirements issued by the National Banking and Securities Commission (CNBV). On July 1, 2026, the agency published amendments to the General Provisions Applicable to Credit Institutions, expanding existing identity verification requirements to include facial biometrics alongside fingerprint verification for in-person banking transactions. Previous regulations relied primarily on fingerprint verification for in-person identity confirmation. Under the new rules, financial institutions have 90 days to implement liveness verification methods while continuing to protect biometric information from being sold, shared or transferred to third parties. The amendments also require facial biometric verification to achieve a minimum 90 percent match against government identity records, strengthening identity authentication requirements across financial institutions. The update reflects a trend across Latin America. Governments are placing greater emphasis on the use of biometrics, financial services are becoming more digital and fraud is growing more sophisticated. Organizations such as the FIDO Alliance were founded to help advance stronger authentication standards as identity threats continue to develop. Together, regulations and industry standards reinforce the importance
Aug 11, 2026 · via biometricupdate.com