No-frills tech news

Who polices policing AI?

In April, the Home Office announced £115m of new funding to create the “Police.AI” centre. Its aim is to introduce a “rapid and responsible” rollout of AI tools across all 43 forces in England and Wales. The National Police Chief Council (NPCC) claims it will establish UK policing as “a global leader in applied, responsible AI”. Currently, each police force in the UK largely determines for itself how and when to procure, trial and deploy AI tools, leading to a lack of standardisation and inefficient, costlier procurement practices. This has inevitably led to concerns being raised regarding policy, ethics and accountability – and nowhere has the debate been more pointed than around the use of Live Facial Recognition (LFR). This is because LFR is already being used at scale. More than 25,000 “retrospective” facial recognition (RFR) searches are carried out per month, with images from CCTV, mobile phones, dashcams, video doorbells and social media compared against a police national database of custody mugshots. In London, between January 2024 and September 2025, over 1,300 suspects were arrested with the help of live facial recognition technology (FRT). In February, the government concluded a consultation on legislation to govern the use of the technology by police. The Home Office signalled its intentions plainly: “The consultation will pave the way for new laws so all police forces can use this new technology with greater confidence and more often.” Up to this point, police advocates have stressed that the patchwork of checks and balances in place, such as the AI covenant in policing, and the Surveillance Camera Code of Practice, are sufficient for regulating the use of LFR. Critics counter that the public are being asked to rely on police assurances in what remains a legal grey area. Questions are also being raised about the

Smart cameras and AI: Are we being watched?

AI-powered image processing enhances daily life in Malaysia, from phone cameras to hospital scans and smart security systems. EVERY time you take a selfie and your phone magically enhances the lighting or when you walk past a security camera that seems to follow your movement, you are witnessing the quiet power of digital image-processing combined with artificial intelligence. These technologies are no longer just part of science fiction; they are part of our everyday lives, often working behind the scenes without us even noticing. Digital image-processing is a way for computers to “see” and “understand” pictures. It helps machines clean up blurry images, recognise faces and even detect objects. When paired with artificial intelligence, which allows computers to learn and make decisions, the results are impressive. Your phone knows where your face is in a photo. A hospital scanner can highlight signs of illness and a traffic camera can identify a speeding car in seconds. All of this is possible because of the way computers process images and learn from them. In Malaysia, these technologies are already being used in many sectors. Hospitals use AI to help doctors read X-rays more accurately. Security systems in shopping malls and offices use smart cameras to detect suspicious behaviour. Even agriculture is benefiting, with drones flying over fields to check crop health using image analysis. It is clear that AI and image processing are helping us live safer, healthier, and more efficient lives. But as these systems become smarter, they also raise important questions. Who controls the data collected by these cameras? How is your face being stored and used? Can these systems make mistakes? These are not just technical issues; they are ethical ones. For example, facial recognition can help catch criminals but it can also be used to track innocent people

Disneyland becomes more reliant on <b>facial recognition</b> despite privacy concerns | National

Photos are an expected part of almost any visit to Disneyland. Whether it’s first-time international visitors or longtime returnees, just about everyone is clicking photos at some point. That everyone, however, is extending more and more to Disneyland personnel. My colleague Hannah Fry documented the growing use of facial recognition technology at the Happiest Place on Earth. Privacy experts are sounding the alarm, while some patrons are trying their best to avoid the technology. Let’s dive into her reporting to see what’s going on. Under the mouse’s eye Photographs of guests’ faces taken at the entrances to Disneyland and sister park California Adventure are run through biometric technology to convert the images into unique numerical values. The images can then be compared with pictures taken when a customer first used the ticket or annual pass. “Pretty much every other place is doing the same thing,” said John LeSchofs, 73, who visits the park roughly every six weeks with his wife. “The police, the government, they’re all using facial recognition. I don’t think it’s going to stop.” Disney officials say the technology helps make entering and reentering the park easier and prevents fraud. Sounding the alarm The rapid growth of facial recognition over the last decade has raised concerns among privacy experts who caution that such data can easily be turned over to law enforcement entities or make companies hacking targets. “The normalization of facial surveillance is really problematic,” said Ari Waldman, a professor of law at UC Irvine. “We can’t go around life hiding our faces, so this isn’t just [the] next step in surveillance; it’s qualitatively different. In a world of facial recognition, when people leave their house, it automatically means they’re identified.” Following a familiar pattern Venues over the last decade have increasingly relied on facial recognition to

Why <b>Facial Recognition</b> Technology Demands A Warrant

Why Facial Recognition Technology Demands A Warrant Facial recognition technology (FRT) seems to be everywhere these days—it is in malls, airports, and our ever-present smartphones. First commercialized in the mid-1990s, FRT today is used widely in the police investigation process due to its efficiency. Despite how commonly the technology is used as an investigative tool, the legal protections to govern its use and avoid government overreach have not been updated accordingly due to a lack of federal FRT legislation. The Eighth District Court of Appeals case State v. Tolbert (2025) reveals this lack of judicial oversight over FRT. While the case is still active and ongoing, the facts established in the case and the rulings to date point to the need for clearer FRT regulations. In State v. Tolbert, the Cleveland Police Department used a facial recognition match from a fusion center to identify Qeyeon Tolbert as a suspect for a homicide case. From this identification match, Homicide Detective Michael Legg secured a search warrant of an apartment linked to Tolbert, resulting in Tolbert’s arrest. Although the Eighth District Court of Appeals found that the use of FRT to obtain a warrant did not violate Tolbert’s Fourth Amendment right to a truthful affidavit warrant, the court’s ruling overlooks an important concern that the defendant raises: the unregulated use of FRT to identify a suspect. Given that FRT is an efficient surveillance tool becoming more commonly used in criminal investigation, lack of government regulation can encourage unreasonable searches in violation of the Fourth Amendment. To protect citizens from unregulated mass surveillance, while also acknowledging the benefits of FRT, the use of FRT to verify or identify an individual should be treated as a search under the Fourth Amendment. State v. Tolbert focuses on defendant Qeyeon Tolbert, a twenty-three-year-old African American man

Police expand use of <b>facial recognition</b> apps for quick checks

Facial recognition apps that allow police officers to carry out on-the-spot identity checks with their phones are being quietly adopted by UK forces before a potential national rollout. At least one force has also discussed using facial recognition technology with live-streamed body-worn video footage and using drone-mounted cameras to identify people at protests. The developments mark a significant expansion of the police’s use of facial recognition which, has to date, largely relied on cameras in public spaces and searches using images taken from sources such as CCTV and social media. Merseyside police is one of several forces to give officers access to handheld facial recognition technology, known as operator-initiated facial recognition (OIFR). OIFR allows officers to take photos of faces and search for matches on police databases. It is typically used when someone refuses to provide their identity or officers believe they have given a false name, although forces say it can also be used to check the identities of those who are unconscious or otherwise unable to provide details. Operator-initiated facial recognition is one of three types available to police. Retrospective facial recognition is the oldest form and is used to search images from crime scenes against pictures taken of people on arrest. Polling has found it to be the most acceptable form of facial recognition among the public. Live facial recognition uses live video footage of people passing cameras and comparing their faces to wanted lists. In December the government announced an expansion of facial recognition technology with the aim for it to be used daily by all 43 police forces in England and Wales. More than a dozen already use it routinely. Sarah Jones, the policing minister, wants it adopted by all of the forces, likening the impact on crime to the breakthrough of DNA matching in

Disneyland becomes more reliant on <b>facial recognition</b> despite privacy concerns

Photos are an expected part of almost any visit to Disneyland. Whether it’s first-time international visitors or longtime returnees, just about everyone is clicking photos at some point. That everyone, however, is extending more and more to Disneyland personnel. My colleague Hannah Fry documented the growing use of facial recognition technology at the Happiest Place on Earth. Privacy experts are sounding the alarm, while some patrons are trying their best to avoid the technology. Let’s dive into her reporting to see what’s going on. Under the mouse’s eye Photographs of guests’ faces taken at the entrances to Disneyland and sister park California Adventure are run through biometric technology to convert the images into unique numerical values. The images can then be compared with pictures taken when a customer first used the ticket or annual pass. “Pretty much every other place is doing the same thing,” said John LeSchofs, 73, who visits the park roughly every six weeks with his wife. “The police, the government, they’re all using facial recognition. I don’t think it’s going to stop.” Disney officials say the technology helps make entering and reentering the park easier and prevents fraud. Sounding the alarm The rapid growth of facial recognition over the last decade has raised concerns among privacy experts who caution that such data can easily be turned over to law enforcement entities or make companies hacking targets. “The normalization of facial surveillance is really problematic,” said Ari Waldman, a professor of law at UC Irvine. “We can’t go around life hiding our faces, so this isn’t just [the] next step in surveillance; it’s qualitatively different. In a world of facial recognition, when people leave their house, it automatically means they’re identified.” Following a familiar pattern Venues over the last decade have increasingly relied on facial recognition to

AI road safety cameras are fuelling a surge in driver fines. Are they fair?

Artificial intelligence (AI) road safety cameras have been rolling out across Australia, resulting in a large number of fines. For example, roughly 184,000 infringements have been issued in Western Australia since the cameras were launched in October last year. In New South Wales, more than 130,000 fines were issued in 2024-2025, the first year the technology was used. In Queensland, about 114,000 fines based on AI image recognition technology were issued in 2024. But it is the size of the penalties that has drawn much attention and criticism. In WA, penalties start at A$550 and four demerit points for seatbelt infringements. These can add up quickly in cases where people get repeated fines. For example, one WA driver with a seatbelt exemption was issued almost A$20,000 in fines after multiple seatbelt infringements. Although fines can be challenged, there are growing concerns about the accessibility and fairness of the appeal process, especially at scale. The technology also raises the question of whether AI camera systems are the best way to promote safe driving. How do AI road safety cameras work? AI road safety cameras use computer vision systems to identify patterns in still images captured by roadside cameras. AI software initially reviews all images. Where no infringement is detected, the image is automatically deleted. Where potential infringements are detected, the images are then flagged for human review before an infringement is sent out to a driver. The approach is intended to increase efficiency, as it saves officers from having to manually review large volumes of images. Drivers can challenge these fines where they believe an error occurred, or in cases where a valid excuse can be established. In Queensland, a driver successfully challenged a fine he received after his passenger shifted their seatbelt under their arm mid-trip. Representing himself in court,

Disneyland becomes more reliant on <b>facial recognition</b> despite privacy concerns | Tribune

Photos are an expected part of almost any visit to Disneyland. Whether it’s first-time international visitors or longtime returnees, just about everyone is clicking photos at some point. That everyone, however, is extending more and more to Disneyland personnel. My colleague Hannah Fry documented the growing use of facial recognition technology at the Happiest Place on Earth. Privacy experts are sounding the alarm, while some patrons are trying their best to avoid the technology. Let’s dive into her reporting to see what’s going on. Under the mouse’s eye Photographs of guests’ faces taken at the entrances to Disneyland and sister park California Adventure are run through biometric technology to convert the images into unique numerical values. The images can then be compared with pictures taken when a customer first used the ticket or annual pass. “Pretty much every other place is doing the same thing,” said John LeSchofs, 73, who visits the park roughly every six weeks with his wife. “The police, the government, they’re all using facial recognition. I don’t think it’s going to stop.” Disney officials say the technology helps make entering and reentering the park easier and prevents fraud. Sounding the alarm The rapid growth of facial recognition over the last decade has raised concerns among privacy experts who caution that such data can easily be turned over to law enforcement entities or make companies hacking targets. “The normalization of facial surveillance is really problematic,” said Ari Waldman, a professor of law at UC Irvine. “We can’t go around life hiding our faces, so this isn’t just [the] next step in surveillance; it’s qualitatively different. In a world of facial recognition, when people leave their house, it automatically means they’re identified.” Following a familiar pattern Venues over the last decade have increasingly relied on facial recognition to

Disneyland becomes more reliant on <b>facial recognition</b> despite privacy concerns | National

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Smart Vision <b>Processing</b> Chips Market in China - IndexBox

China Smart Vision Processing Chips Market 2026 Analysis and Forecast to 2035 Executive Summary Key Findings - The China Smart Vision Processing Chips market is projected to grow from approximately USD 4.5–5.5 billion in 2026 to over USD 14–18 billion by 2035, representing a compound annual growth rate (CAGR) of roughly 13–16% driven by the country's dominant position in surveillance, automotive, and consumer electronics manufacturing. - China's reliance on imported advanced-node chips (7nm and below) remains high, with over 60–70% of high-performance Smart Vision Processing Chips sourced from Taiwan, South Korea, and the United States, creating a structural supply vulnerability amid ongoing export control restrictions. - Domestic fabless design houses and integrated device manufacturers (IDMs) have captured an estimated 30–40% of the Chinese market by volume in 2025–2026, primarily in mid-range and edge-deployed vision SoCs, but remain constrained by limited access to leading-edge foundry capacity and advanced packaging substrates. Market Trends Observed Bottlenecks Access to advanced semiconductor foundry capacity Licensing of critical AI/vision IP blocks Long OEM qualification cycles (especially automotive) Shortage of specialized chip design engineers Supply of advanced packaging substrates - Edge AI inference is rapidly displacing cloud-centric vision processing: by 2026, over 55–65% of all Smart Vision Processing Chips shipped in China are expected to perform real-time inference on-device, driven by latency requirements in autonomous driving, industrial inspection, and smart city surveillance. - Automotive ADAS and in-cabin monitoring has become the fastest-growing application segment, with China's vehicle production exceeding 28 million units annually and regulatory mandates for driver monitoring systems (DMS) accelerating adoption of dedicated vision processors. - Integration of Convolutional Neural Network (CNN) accelerators and Tensor core engines directly onto vision SoCs has become standard, with chip prices for mid-range edge AI vision processors declining by 8–12% per year as competition intensifies among domestic and international

Google Photos wardrobe feature scans your closet and lets you try it on

Google announced on April 29, 2026, a new feature for Google Photos that uses artificial intelligence to automatically scan a user's photo library, extract the clothing items that appear across those images, and assemble them into a dedicated digital wardrobe. The feature is scheduled to begin rolling out during the summer of 2026, first on Android and then on iOS, according to Tommy Meaney, Senior Product Manager at Google Photos. The announcement arrives as Google has spent nearly two years expanding AI-powered visual tools across its product line - from Google Lens shopping integrations to virtual try-on inside AI Mode in Search and, most recently, Circle to Search gaining the ability to identify every item in a complete outfit at once. The Google Photos wardrobe feature is distinct from all of those because it operates entirely on clothing the user already owns, not on items for sale elsewhere. How the AI wardrobe cataloging works According to the announcement, the wardrobe feature constructs its catalog by analyzing the photos already stored in a user's Google Photos library. The AI identifies clothing items visible in those images and classifies them by category. The categories listed in the announcement include jewelry, tops, and bottoms - suggesting the classification system covers a broad range of garment types rather than a narrow subset. Once the library has been processed, the resulting collection becomes browsable by category. A user can filter to see all tops together, all bottoms together, or all jewelry, rather than only having access to images organized by date or location as the current interface provides. The intended effect, according to the announcement, is that items buried deep in a photo archive become discoverable again, even if they appear in a photo taken years earlier. The depth of that library scan is notable.

AI <b>facial recognition</b> oversight lagging far behind technology, watchdogs warn

Britain’s biometrics watchdogs have warned that national oversight of AI-powered face scanning to catch criminals is lagging far behind the technology’s rapid growth. With the Metropolitan police almost doubling the number of faces they scan in London over the past 12 months and a rising use of the technology by retailers in the UK, Prof William Webster, the biometrics commissioner for England and Wales, said the “slow pace of legislation was trying to catch up with the real world” and “the horse had gone before the cart”. Dr Brian Plastow, who holds the same role in Scotland, warned the technology was “nowhere near as effective as the police claim it is” and said there was a “patchwork legal framework” throughout the UK. He said in England and Wales, police were “really just marking their own homework”. The watchdogs said new laws were needed to govern when and how police forces used live facial recognition technology, with a new regulator to clamp down on misuse. Several bodies have oversight of the technology, including the Information Commissioner’s Office (ICO) and the Equality and Human Rights Commission. The Home Office is considering a new legal framework for the technology as it also plans to introduce nationally what it calls “the biggest breakthrough for catching criminals since DNA matching”. Members of the public wrongly labelled as suspected criminals by shops using AI cameras said there was no accountability or recourse to complain. They said the system had left them feeling “guilty until proven innocent”. They described the ICO, which is responsible for monitoring facial recognition tech and the biometric data it uses, as “toothless” and unresponsive. British police forces and high street retailers claim the technology makes streets safer, but others criticise it as Big Brother-style mass surveillance, with risks for civil liberties and

Guilty until proven innocent: shoppers falsely identified by <b>facial recognition</b> system struggle ...

When Ian Clayton, a retired health and safety professional from Chester, popped into Home Bargains one February lunchtime, he was suddenly approached by a stern-looking member of staff. “Excuse me, can you please put everything down and leave the shop now?” she said. Clayton recalled how he was stunned, and it was only as he was briskly walked past the tills towards the exit that he stopped to ask what he had done. “You’ve come up on our system called Facewatch as a shoplifter,” came the reply. “There’s a poster in the window.” With that, he was left outside the shop alone, with a QR code to scan and no idea what had happened. He is one of a number of people who have spoken to the Guardian after being falsely identified as a thief by shops using Facewatch, a live facial recognition system being rolled out across the UK to clamp down on retail crime. The company’s website claims that its system has a 99.98% accuracy rate and that last month it sent 50,288 alerts of “known offenders” to shops including B&M, Home Bargains, Sports Direct, Farm Foods and Spar, which all now use the software. But those who have been wrongly identified and forced to leave shops, either via the technology itself or human error, say they were given no support, and did not know how to complain about their treatment or prove their innocence. Clayton, 67, said that after he was ejected from Home Bargains he tried calling a phone number on a Facewatch poster, and was sent through to a message saying the company did not take calls and he had to send an email instead. He was only able to get answers after submitting a subject access request – a formal request under data protection

Anne Boleyn: the promise of a face, and what this new research actually reveals

490 years later, the question remains On May 19, 2026, it will be 490 years since the execution of Anne Boleyn, a death that not only ended a reign of roughly one thousand days but also inaugurated one of the most unstable narratives in the history of the English monarchy, shaped by fragile accusations, political rearrangements, and an almost immediate rewriting of who she was. Nearly five centuries later, what is striking is not only that her guilt or innocence, her ambition or her role in the break with Rome are still debated, but that an even more basic question remains unresolved: what did Anne Boleyn’s face look like? But Anne Boleyn’s story does not begin or end at the scaffold. It begins to be constructed days earlier. On May 2, 1536, Anne was formally accused of the crimes that, weeks later, would lead to her execution. The charges of adultery, incest, and treason did not merely organize her downfall in legal terms; they also established the version of her that would outlive her. This uncertainty is not an effect of time, but of how her story was shaped from the moment of her fall. Executed under accusations that are now widely considered politically constructed, removed in a context that involved the urgent need for a male heir and a reorganization of power within the court, Anne was not only eliminated as a political figure but also as an image. This uncertainty is not simply the effect of time, but of how her story was constructed from the moment of her fall. Executed under accusations that are now widely considered politically fabricated, removed in a context that involved the urgent need for a male heir and a reorganization of power within the court, Anne was not only eliminated as a

About the Guest Editors | Computer vision for animal studies

Song-Quan Ong, PhD, Universiti Malaysia Sabah, Malaysia Dr. Song-Quan Ong is a Senior Researcher at Universiti Malaysia Sabah. His research integrates artificial intelligence, computer vision, and data science to advance biodiversity monitoring, animal ecology, and vector-borne disease surveillance. His research also focuses on developing computer vision systems and curated image and video datasets for automated species identification and ecological monitoring. By bridging ecology with artificial intelligence and FAIR data practices, his research supports the development of high-quality datasets that enable reproducible and scalable computer vision applications in animal studies. Dr. Ong has been working as an Editorial Board Member for Scientific Data since 2024. Linlin Shen, PhD, Shenzhen University, China Dr. Linlin Shen is a Professor at the School of Artificial Intelligence, Shenzhen University, Shenzhen, China. He is also an Honorary Professor at the School of Computer Science, University of Nottingham, U.K. He is the Deputy Director of the National Engineering Laboratory of Big Data Computing Technology and the Director of the Computer Vision Institute, the AI Research Center for Medical Image Analysis and Diagnosis, and China–UK Joint Research Laboratory on Visual Information Processing. His research interests include deep learning, facial recognition, analysis/synthesis, and medical image processing. Dr. Shen has been working as an Editorial Board Member for Scientific Data since 2024.

Erie County lawmakers pass ban on private-sector biometric data use | News

The Erie County Legislature on Thursday approved the Erie County Biometrics Transparency and Privacy Act in a 7-4 vote, prohibiting private businesses from collecting, storing or selling consumers’ biometric data, including facial recognition, fingerprints and iris scans. The measure carves out exemptions for government agencies, financial institutions and personal device authentication. Violations carry penalties ranging from $1,000 to $5,000 per day and will be enforced by the county’s Division of Consumer Protection. Businesses cited under the law will have 30 days to come into compliance. Legislator Lawrence Dupre, Dist. 1, who sponsored the bill, described the measure as a necessary step to “protect the citizens of Erie County,” noting that unlike passwords, biometric identifiers cannot be changed. He argued that private companies should not be building databases of such sensitive information that could later be sold. Supporters said the law draws a clear line between legitimate security uses and the unauthorized collection of personal data. Opponents, including Legislator Lindsay Lorigo, criticized the measure as overly broad. Lorigo instead backed an alternative proposal, the Customer Biometric Privacy Act, which would have required businesses to notify customers of data collection through posted signage rather than banning the practice outright. The legislation follows confirmations from retailers such as Wegmans that they have recently started used facial recognition technology in stores. The law will take effect upon filing with the New York secretary of state.

Apple reportedly accelerates its ambitious three-year plan

Apple reportedly accelerates its ambitious three-year plan Apple wants to get its most exciting new devices to your hands even faster than originally planned. The iPhone 17 Pro redesign was just the beginning. | Image by PhoneArena Apple has a three-year plan, or so many reports over the last half a year or so have confidently claimed. The company wanted to break free from its annual monotony and shake up the entire industry, something that it now reportedly plans to do in just a year and a half instead. What is this three-year plan? Mostly, it was focused on the iPhone. You saw it come into action with the redesign of the iPhone 17 Pro, a move that made the iPhone 17 the most popular iPhone in the company’s history. After the iPhone 17, the iPhone 18 Pro is supposed to ship with an under-display Face ID and a smaller Dynamic Island. Apple is still working on this, as preliminary reports indicate that the company is struggling with sluggish facial recognition. Lastly, the iPhone 20 Pro is slated for 2027 to celebrate the 20th anniversary of the iPhone. An iPhone model with no cutouts across the display at all. With said display ever so gently melding into the chassis to give it a feeling of floating above the phone. Those are just Apple’s plans for the iPhone. There are other exciting projects in the works too. For example, an iPad Air with an OLED display or touchscreen MacBook models also with OLED panels. The company is also working on an iPhone Air 2 and already has plans for a successor to this year’s upcoming foldable iPhone Ultra. Then there’s the new stuff. A robot with an arm, a smart home hub, AirPods with cameras, smart glasses without a display and

Lawyer for wrongly accused woman says 'reckoning' due for police reliance on AI <b>facial recognition</b>

FARGO — Attorneys for a Tennessee woman who was wrongly accused and jailed for months based on artificial intelligence evidence are working to file a civil rights lawsuit on her behalf. Despite a slow-going investigative process, the attorney for Angela Lipps said information gathered so far indicates the case "should strike fear in every law-abiding citizen" about the real-world implications of law enforcement's use of facial recognition technology. ADVERTISEMENT The story of Lipps' arrest last July in her rural hometown in the foothills of Appalachia in east Tennessee, and subsequent months-long incarceration after Fargo police relied on AI to identify her as the suspect in a bank fraud case, spread like wildfire after it was first reported by WDAY News last month. The New York Times, CNN and People Magazine covered the case. International outlets breathlessly reported the most egregious details, including that Lipps had never been on an airplane until she was extradited to North Dakota based on Fargo's arrest warrant, and that she was released from the Cass County Jail into frigid weather on Christmas Eve without a coat or money, and local defense attorneys had to cobble together donated personal funds to help her get back home. The case against Lipps Lipps' saga began after Fargo police started investigating a series of crimes at banks around Fargo and West Fargo that took place in late April and early May of last year. Court documents show investigators were attempting to locate two female suspects who presented fake military ID cards at seven different banks and credit unions to withdraw money from home equity line of credit accounts, resulting in a total loss of more than $67,000. By early June, Fargo detectives had honed in on Lipps as a prime suspect in their case, based, it is now known,

Scientists convinced they've just discovered Anne Boleyn's 'real face'

She may be one of the most famous royal spouses, but Anne Boleyn was never pictured in her lifetime. The second wife of Henry VIII has been the subject of fierce debate, with her physical appearance remaining shrouded in mystery. However computer scientists have now linked a sketch of an unknown woman to the famously beheaded royal using facial recognition technology. As Boleyn was never depicted while she was alive, our understanding of her appearance is shaped by several posthumously created paintings. These include a sketch by Hans Holbein the Younger, which is part of a collection held in Windsor by the Royal Collection Trust. Sign up for all of the latest stories Start your day informed with Metro's News Updates newsletter or get Breaking News alerts the moment it happens. While many scholars believe it is an accurate representation of Henry VIII’s second wife, the computer scientists from the University of Bradford believe it in fact could be her mother, Elizabeth née Howard. Professor Hassan Ugail, who specialises in visual computing said the team was comparing a series of drawings, including some of Boleyn’s first cousins and her daughter, Elizabeth I, using a computer algorithm. The cutting edge technology was used to analyse familiar similarities. But the method ‘shocked’ researchers when it appeared to match an unidentified sketch to Boleyn. Lead author Karen Davies long had a childhood obsession with Boleyn. However she was skeptical of the sketch named after the Tudor royal by Holbein, citing discrepancies between the artwork and descriptions of Boleyn, as well as the fact that the name was etched in an 18th century hand – several hundred years after Boleyn was executed. Not everyone is onboard with the methodology however. Some have questioned how such technology can be used to identify drawings, which are