Tag: Facial Recognition

Tech News : Meta Pulls Facial Recognition Code From Smart Glasses App

Posted on by Paul Stradling

It’s been reported that Meta has quietly removed facial recognition code from the companion app used by its AI-powered smart glasses, reigniting concerns about how far wearable technology companies may be willing to go in their pursuit of always-on artificial intelligence.

What Was Removed?

The controversy centres on an internal system called NameTag, which was discovered inside the Meta AI smartphone app that works alongside the company’s Ray-Ban smart glasses. According to reporting first published by WIRED, the code appeared to support facial recognition capabilities that had never been publicly released.

The system was reportedly designed to convert faces captured by the glasses into unique biometric identifiers, often referred to as faceprints, and compare them against a database stored on the user’s device. Evidence within the software also suggested that faces the system could not identify would be cropped, indexed, and stored locally for future processing.

Most notably, the code was present inside an application installed on tens of millions of devices despite Meta repeatedly stating that no final decision had been made about introducing facial recognition to its smart glasses platform.

Just one day after the findings became public, Meta released an updated version of the app that removed almost all traces of the NameTag system.

Meta’s Response

Meta says the facial recognition system was an internal exploratory project rather than a planned product feature. However, the speed with which the code was removed has inevitably attracted attention.

Reports indicate that the original software contained multiple AI models dedicated to detecting faces, cropping facial images, and converting them into biometric signatures. The app also reportedly contained a “Person recognised” alert that would have been displayed if someone was successfully identified.

Meta has not publicly explained why the code was removed immediately after the discovery or whether the changes had already been planned before the reporting appeared.

Why Facial Recognition In Glasses Is Different

The debate is not really about facial recognition itself. The technology has existed for many years and is already widely used in smartphones, airports, security systems, and consumer applications.

What makes smart glasses different is that they allow facial recognition to move from fixed locations and deliberate actions into everyday social interactions.

Unlike a phone, which requires someone to consciously point a camera at another person, smart glasses can continuously capture information while being worn. Combined with AI, cameras, microphones, and internet connectivity, they create the possibility of real-time identification in public spaces without the knowledge of the people being observed.

Supporters argue that such technology could have legitimate uses. For example, facial recognition could help visually impaired users identify friends, family members, or colleagues. It could also assist people with memory difficulties or cognitive impairments.

Critics, however, have raised concerns that the same technology could be misused for stalking, harassment, surveillance, or the identification of strangers without consent.

Those concerns become even more significant when combined with generative AI systems capable of searching, analysing, and contextualising information automatically.

Part Of A Bigger Strategy

The discovery also provides an insight into Meta’s longer-term ambitions for wearable AI. For example, chief executive Mark Zuckerberg has repeatedly described smart glasses as a future computing platform where AI assistants become constantly available throughout the day. The company’s recent investments in Ray-Ban and Oakley smart glasses reflect a belief that future digital interactions will increasingly move away from smartphones and towards wearable devices.

Facial recognition could potentially play an important role in that vision. An AI assistant capable of recognising people, understanding context, remembering previous interactions, and providing relevant information could become far more useful than one that simply responds to voice commands.

However, it is precisely that capability which raises difficult questions about privacy, consent, and personal data.

The Wider Privacy Challenge

The incident arrives at a time when regulators in Europe, the UK, and the United States are paying closer attention to biometric technologies.

Unlike passwords or usernames, biometric identifiers are linked directly to an individual’s physical characteristics. If compromised or misused, they cannot simply be changed or reset.

Privacy campaigners have long argued that facial recognition requires stronger safeguards than many other forms of personal data because of its potential to identify individuals at scale and without their active participation.

The rapid removal of the NameTag code suggests that Meta recognises the sensitivity of the issue, even if the company insists the feature was only exploratory.

What Does This Mean For Your Business?

For businesses, the story highlights how quickly AI is beginning to move beyond software and into the physical world.

Many organisations are already evaluating AI tools for productivity, automation, and customer service. The next wave of AI innovation is likely to involve wearable devices that can see, hear, interpret, and respond to the environment around them in real time.

That creates new opportunities, particularly in areas such as accessibility, training, field services, logistics, and hands-free information access. At the same time, it introduces new questions around privacy, data governance, consent, and the collection of biometric information.

The wider lesson is that as AI becomes more deeply embedded into everyday devices, businesses will need to think not only about what these systems can do, but also about what employees, customers, and the public are comfortable allowing them to do. The reaction to Meta’s facial recognition experiment suggests those conversations are only just beginning.

Featured Article : Government Plans Major Expansion Of Facial Recognition

Posted on by Paul Stradling

The government has set out plans to expand the use of facial recognition and other biometrics across UK policing, describing it as the biggest breakthrough for catching criminals since DNA matching.

A National Strategy For Biometrics

The Home Office has launched a ten week consultation to establish a new legal framework covering all police use of facial recognition and biometric technologies. This would replace the current mix of case law and guidance with a single, structured system that applies consistently across forces.

The plan includes creating a dedicated regulator overseeing facial recognition, fingerprints and emerging biometric tools. The Home Office says a single body would provide clarity and help forces apply safeguards more confidently. It also proposes a national facial matching service, allowing officers to run searches against millions of custody images through one central system.

Breakthrough

Launching the consultation, Crime and Policing Minister Sarah Jones said, “Facial recognition is the biggest breakthrough for catching criminals since DNA matching,” adding, “We will expand its use so that forces can put more criminals behind bars and tackle crime in their communities.” Her view reflects the government’s belief that existing deployments have already demonstrated clear operational value, particularly in identifying violent offenders.

Why Now?

The push for expansion comes as police forces face increasing pressure to track offenders across regions and to manage high volumes of video supplied by retailers, businesses and members of the public. Also, recent cases of prisoners being released in error, or disappearing before arrest, have highlighted the difficulty of locating suspects quickly without technological support.

Public Tolerance For Certain Uses

Government research published alongside the consultation appears to suggest high public tolerance for certain uses. For example, according to the government’s figures, 97 per cent of respondents said retrospective facial recognition is at least sometimes acceptable, while 88 per cent said the same about live facial recognition for locating suspects. Ministers may see this as support for building a clearer framework, although rights groups argue that acceptability is dependent on strict safeguards and transparency.

The Need For Oversight

That said, independent accuracy testing has reinforced the need for stronger oversight. For example, the National Physical Laboratory found that earlier systems used in UK policing produced significantly higher false alert rates for Black and Asian people. The Home Office now acknowledges these disparities, noting that updated systems and reviews have since been introduced. Even so, the findings have shaped calls for clearer legal boundaries before expansion proceeds.

When These Changes Might Take Effect

The consultation runs through early 2026, after which ministers will draft legislation for parliamentary scrutiny. The Home Office estimates that introducing a new legal regime, establishing the regulator and deploying the national facial matching service will take around two years. During that period, existing deployments will continue under current guidance.

Police forces already using live facial recognition, including the Metropolitan Police and South Wales Police, will continue targeted deployments. Trials using mobile facial recognition vans across multiple forces are also expected to continue, and the national facial matching service is scheduled for testing in 2026.

How The Technology Works Across UK Forces Today

Police currently rely on three distinct facial recognition tools, each supporting different operational needs, which are:

1. Retrospective facial recognition. Used during investigations, this compares still images from CCTV, doorbell cameras, mobile footage or social media against custody images. It is the most widely used form, and police say it speeds up identification in cases where investigators have a clear image but no confirmed identity.

2. Live facial recognition. These systems scan faces in real time as people pass a camera. The software compares each face to a watchlist of individuals wanted for specific offences or subject to court conditions. When a possible match arises, officers decide whether to stop the person. Deployments are usually short, targeted and focused on high footfall areas.

3. Operator initiated facial recognition. This mobile app allows officers to check identity during encounters by comparing a photo to custody images, avoiding unnecessary trips to a station solely for identification.

Police leaders say these tools allow forces to locate wanted individuals more efficiently. Lindsey Chiswick, the National Police Chiefs’ Council lead for facial recognition, says the technology “makes officers more effective and delivers more arrests than would otherwise be possible”, adding that “public trust is vital, and we want to build on that by listening to people’s views”.

Legal And Ethical Issues

Legal concerns have followed facial recognition since its earliest deployments, and several landmark rulings continue to shape how police use the technology. For example, back in 2020, a Court of Appeal ruling in the Ed Bridges case remains the most significant legal challenge to date. In this case, the court found that South Wales Police’s early use of live facial recognition breached privacy rights because of inadequate safeguards, incomplete assessments and insufficient checks on whether the system discriminated against particular groups.

Also, the Equality and Human Rights Commission has criticised aspects of earlier Metropolitan Police deployments, saying forces must demonstrate necessity and proportionality each time. The Information Commissioner’s Office has also warned forces to ensure accuracy and justify the retention of custody images belonging to people never convicted of an offence.

Accuracy Problems

Accuracy remains central to the ethical debate. For example, the National Physical Laboratory found that in one system previously used operationally, Asian faces were wrongly flagged around four per cent of the time and Black faces around five and a half per cent, compared with around 0.04 per cent for white faces. For Black women, false alerts rose to nearly ten per cent. These figures show how demographic disparities can emerge in real deployments and highlight the importance of system configuration.

Rights groups warn that these issues could lead to wrongful stops or reinforce existing inequalities. They also argue that routine scanning in public spaces risks creating a sense of constant surveillance that may influence how people move or gather. Liberty has said it is “disappointed” that expansion is being planned before the risks are fully resolved, while Big Brother Watch has urged a pause during the consultation.

Support Strong From Police

It’s worth noting here that, perhaps not surprisingly, support within policing remains strong. For example, former counter terror policing lead Neil Basu says live facial recognition is “a massive step forward for law enforcement, a digital 21st century step change in the tradition of fingerprint and DNA technology”, while noting that it “will still require proper legal safeguards and oversight by the surveillance commissioner”. Police forces repeatedly stress that every alert is reviewed by an officer rather than acted on automatically.

Industry Supports Structured Rollout

Industry organisations also appear to support a structured rollout. For example, Sue Daley, Director of Tech and Innovation at techUK, says “regulation clarity, certainty and consistency on how this technology will be used will be paramount to establish trust and long term public support”. The technology sector argues that clear rules will help build confidence both inside and outside policing.

Charities

Charities focused on vulnerable people have also highlighted some potential benefits. For example, Susannah Drury of Missing People says facial recognition “could help to ensure more missing people are found, protecting people from serious harm”, though she also stresses the need to examine ethical implications before expanding use.

That said, civil liberties groups continue to call for stronger limits, arguing that wider deployment risks normalising biometric scanning in everyday spaces unless strict rules are imposed regarding watchlists, retention and operational necessity.

Areas For Further Debate

The proposals raise questions that will remain live throughout the consultation period. For example, these include how forces will define and maintain watchlists, how the new regulator will enforce safeguards, what thresholds will apply before live facial recognition can be deployed, and how demographic accuracy will be monitored over time. Businesses that operate high footfall environments, such as shopping centres and transport hubs, are also likely to face questions about how their video systems might interact with police requests as adoption increases.

What Does This Mean For Your Business?

It seems that, following this announcement from the government, policymakers now face a moment where practical policing needs, public confidence and legal safeguards must be aligned in a way that has not been achieved before. The consultation sets out an ambition for national consistency and clearer rules, although the evidence presented across this debate shows that accuracy, oversight and transparency will determine whether expansion strengthens trust or undermines it. The range of views from policing, civil liberties groups, industry and charities illustrates how differently this technology is experienced, and why the government will need to resolve issues that sit well beyond technical capability alone.

The implications extend into policing culture, investigative practice and public space management, which will all look different if facial recognition becomes a mainstream tool. Forces anticipate faster identifications, clearer procedures and more reliable ways to locate individuals who pose a genuine risk. Civil society groups, by contrast, point to the potential for overreach unless firm limits are embedded in law. These competing priorities will shape how the regulator operates and how the Home Office interprets proportionality in real deployments.

Businesses also sit at the centre of this discussion because they capture and provide a significant volume of the video footage used in retrospective searches. Retailers, transport hubs and major venues may face new expectations about how they store, secure and share images, and these responsibilities may grow as facial matching becomes more accurate and more widely used. Clearer rules could help organisations understand how to cooperate with investigations without exposing themselves to unnecessary compliance risks, particularly around data protection and equality duties.

The wider public interest lies in how these decisions affect everyday life. Public attitudes will depend on whether safeguards are visible, whether wrongful identifications are prevented, and whether live deployments remain tightly focused rather than becoming a routine feature of public spaces. A national framework could provide that reassurance if it genuinely addresses the concerns raised during testing and legal review. The coming months will show how far the government is prepared to go in defining those boundaries and whether the final model satisfies the mix of operational urgency and ethical caution that has defined this debate so far.

Featured Article : Sainsbury’s Facial Recognition Combats Shoplifting

Posted on by Paul Stradling

Sainsbury’s has begun testing facial recognition technology in selected stores to identify repeat offenders and reduce shoplifting, triggering a wave of privacy concerns from civil liberties groups.

Surveillance Trial Rolling Out in London and Bath

The supermarket chain confirmed that an eight-week pilot programme is underway at a small number of stores in London and Bath. The facial recognition cameras are supplied by Facewatch, a UK-based security technology firm that already provides similar services to a range of retailers.

The system captures the biometric data of individuals who are already on a watchlist for suspected theft or abuse. If someone flagged on this list enters a participating store, an alert is sent to staff in real time. Sainsbury’s says the trial is being used only at locations with a high incidence of repeat offending.

The trial began in late August and is expected to run through to October. Depending on results, it could be expanded to more branches across the UK. Facewatch claims its technology can help retailers cut shoplifting and abuse by deterring known offenders and giving staff more time to intervene safely.

Why Sainsbury’s Is Doing This Now

Retail crime has surged in recent years, with the British Retail Consortium (BRC) estimating the total cost to the sector at £1.76 billion in 2023, including £1.04 billion in customer theft alone. Also, physical assaults and abuse of shop workers have also been rising sharply, prompting calls for tougher enforcement and more robust security measures.

Sainsbury’s said in a statement: “We’re constantly looking at new ways to keep our colleagues and customers safe. We’re currently trialling facial recognition in a small number of stores where there is a high level of crime.”

Signage About It

The company emphasised that the technology is not being used for general customer surveillance or profiling, and that signage is in place at affected locations to notify shoppers that facial recognition is in use.

Powered by Facewatch (Controversially)

The system being used by Sainsbury’s is provided by Facewatch, a private facial recognition firm founded in 2010. Facewatch says it operates within UK GDPR and the Protection of Freedoms Act 2012, and only stores data on those individuals who have been involved in past incidents, as reported by retailers.

Its technology compares live CCTV footage to images held in its centralised database of “subjects of interest.” If there is a match, an alert is sent to store staff with a still-image and time-stamped location data.

While Facewatch has been used by independent retailers, petrol stations and other supermarket chains including Southern Co-op and Budgens, it has not previously been adopted by any of the UK’s four major supermarket brands at this scale.

It seems that the company has drawn some criticism from privacy campaigners for operating a privately managed watchlist system that can share biometric alerts between businesses, with concerns raised about accuracy, accountability, and the lack of independent oversight.

The move by Sainsbury’s essentially takes facial recognition further into the retail mainstream and puts the technology under new levels of public and regulatory scrutiny. It also raises the stakes for how and where this kind of surveillance may be used next across the sector.

Privacy Groups Push Back

Civil liberties organisations were quick to voice concerns. For example, Big Brother Watch, a UK privacy campaign group, accused Sainsbury’s of introducing “unnecessary and Orwellian” surveillance under the guise of crime prevention.

“Facial recognition surveillance is extreme, and Sainsbury’s customers should not be subjected to identity checks to buy milk,” said Madeleine Stone, Senior Advocacy Officer at Big Brother Watch. “This sets a dangerous precedent not just for retail, but for everyday public life.”

The group also raised concerns about transparency and consent, arguing that biometric surveillance in shops blurs the line between policing and commerce. It warned that the use of facial recognition could result in misidentifications, discrimination, and the over-policing of vulnerable groups.

The Information Commissioner’s Office (ICO) has previously cautioned organisations using facial recognition to ensure legal compliance and necessity. It has not commented directly on the Sainsbury’s trial but is likely to monitor developments closely.

Facewatch’s Role in Expanding Everyday Surveillance

Sainsbury’s pilot sits within a broader shift where facial recognition is moving from niche deployments to visible use in everyday retail settings. Southern Co‑op has used Facewatch across dozens of branches since 2020, while independent convenience stores and some symbol groups have reported measurable reductions in repeat theft when using similar watchlist alerts. In one Morrisons Daily site, the store owner told trade press that incidents dropped by as much as ninety per cent after installation, though these results are self‑reported rather than independently audited.

Other Big Chains Are Already Testing the Waters

Other large grocers have been testing live facial recognition in recent months. For example, Asda ran a trial across five Greater Manchester stores, drawing thousands of complaints and sustained criticism from privacy groups, which shows how quickly public reaction can become a material factor in rollouts. Iceland has also been named by campaigners as exploring use, although details remain limited. These parallel efforts are relevant to Sainsbury’s because they indicate how public tolerance, operational benefits, and regulatory scrutiny interact in real retail environments.

Concerns About Accuracy and Misidentification

Concerns about accuracy and fairness remain central to the debate about the use of this kind of technology. For example, privacy group Big Brother Watch argues that commercial watchlists risk misidentifying innocent shoppers because entries are often created by retailers rather than police and can be shared between participating businesses. The group says this creates a risk of people being wrongly flagged and excluded. There have been reported misidentifications, including a case where a customer was barred after a Facewatch alert, which Facewatch later acknowledged was an error. These cases are shaping campaigners’ calls for stricter safeguards and clearer lines of accountability.

Legal Uncertainty Around Commercial Use

The policy landscape adds another layer. For example, the UK has no dedicated statute that comprehensively governs private sector facial recognition in public‑facing spaces, so retailers largely rely on data protection law, necessity and proportionality tests, and DPIAs to justify deployments. The ICO has previously investigated Facewatch and related deployments and, according to evidence submitted to Parliament, identified multiple areas where policies needed to better balance legitimate interests with people’s rights. This context frames what retailers must document and evidence when running pilots like Sainsbury’s.

How the Trial Is Being Measured

Operationally, Sainsbury’s says the Facewatch system is configured to alert staff only when a person on a pre‑defined watchlist is detected, focused on individuals linked to violence, aggression, or theft. Faces that do not match are deleted immediately, and signage at trial stores informs customers that facial recognition is in use. The supermarket has also stressed that the pilot is limited to locations with high levels of repeat offending, and that it is intended to support staff safety rather than to monitor ordinary shoppers.

Retail Crime Data Is Driving Urgency

Evaluation will centre on measurable changes in repeat theft and abuse, staff perceptions of safety, and any displacement effects, for example incidents shifting to nearby stores. The British Retail Consortium reports retail theft at crisis levels, with more than twenty million incidents in 2023 to 2024 and an estimated £2.2 billion lost to shoplifting, which explains why large chains are testing additional controls alongside guards, body‑worn cameras, and product protection. These sector‑wide figures provide the baseline against which any impact from facial recognition will be assessed.

Public Reaction Will Influence Industry Direction

It’s likely that public response will also form part of the assessment. Big Brother Watch has labelled the Sainsbury’s pilot “deeply disproportionate and chilling,” arguing that biometric scanning in supermarkets treats shoppers as suspects and risks normalising identity checks for everyday purchases. Trade unions have tended to frame the question through the lens of staff safety, calling for evidence‑led approaches that reduce violence and abuse at work. Therefore, how these competing views evolve during the pilot will influence whether other national chains follow Sainsbury’s lead.

Regulatory Input Could Shape What Comes Next

Also, any regulatory feedback could shape the design of future deployments. For example, if the ICO receives complaints during the trial, it may seek clarifications on data retention, watchlist criteria, redress routes for mistaken identity, and transparency notices. Previous facial recognition pilots in retail and other sectors have drawn attention to these governance questions, so documenting them clearly is likely to be as important as any headline reduction in theft.

What Does This Mean For Your Business?

The outcome of this trial will matter not only for Sainsbury’s but for any UK business operating in high-footfall environments where theft, abuse, or anti-social behaviour is on the rise. If facial recognition is shown to reduce repeat offending without undermining customer trust, other sectors may begin exploring similar systems, from retail and hospitality to logistics and healthcare. However, that will depend on clear governance, strong safeguards, and public confidence in how the technology is being used.

For technology providers, the stakes are also high. For example, Facewatch’s credibility as a supplier of compliant, proportionate, and accurate surveillance tools may hinge on how this pilot is received by regulators and rights groups. If the ICO intervenes or public backlash intensifies, it could limit how far these systems can expand. Businesses adopting facial recognition will need to be ready to justify every aspect of its deployment, from necessity and proportionality to data handling and redress.

For consumers and communities, the case raises fresh questions about what kind of monitoring is acceptable in everyday spaces, and where the boundaries lie between legitimate protection and excessive surveillance. The lack of specific legislation leaves a vacuum where privacy, ethics, and commercial interest are all pulling in different directions. Without clear national rules, it may fall to individual retailers, campaigners, and regulators to shape how far this goes.

As the pilot continues, attention will turn to how Sainsbury’s measures success and handles concerns. Whether this becomes a new layer of shopfloor security or a short-lived experiment will depend on what the results show, how they are interpreted, and whether wider industry and political appetite supports rolling it out further.

Tech Insight : UK Police Expand Usage of Facial Recognition Vans

Posted on by Paul Stradling

The UK Government has announced the deployment of 10 new Live Facial Recognition (LFR) vans across seven police forces in England, saying the move will help officers track down suspects wanted for some of the most serious crimes.

What?

On 13 August, the Home Office confirmed that vans equipped with live facial recognition cameras will be shared between Greater Manchester, West Yorkshire, Bedfordshire, Surrey and Sussex (jointly), and Thames Valley and Hampshire (jointly). The rollout is part of the government’s wider “Plan for Change” in policing, which also includes neighbourhood policing guarantees and the recruitment of 13,000 more officers by 2029.

The new vans are expected to be deployed in the coming weeks. They will be coordinated nationally by the National Police Chiefs’ Council and South Wales Police, which has already led the way in using the technology. The government says each vehicle will be staffed with trained officers who verify every potential match generated by the software.

How Does the Technology Work?

Live facial recognition compares the faces of people passing by with those held on a police “watchlist”. These watchlists are drawn up for each deployment and include individuals wanted for offences such as sexual assault, violent crime, murder, and breaches of bail or court conditions.

The technology measures facial features such as the distance between a person’s eyes or the shape of the jawline, creating a digital signature that can then be matched against the watchlist. If a possible match is made, an officer on site reviews the image before deciding whether to stop the individual.

Why Is the Government Expanding It Now?

Home Secretary Yvette Cooper said the expansion reflects both the need to modernise policing and the results already seen in London and South Wales. “Facial recognition will be used in a targeted way to identify sex offenders or people wanted for the most serious crimes who the police have not been able to find,” she explained, adding that the rollout will be backed by a new legal framework and public consultation on safeguards.

Only Intelligence-Led Use

It’s worth noting here that the government says that officers will only use the technology in intelligence-led deployments, and that strict guidance from the College of Policing and the Surveillance Camera Code of Practice will apply. It insists the aim is not mass surveillance but a proportionate use of new tools to protect the public.

What Have Previous Trials Achieved?

The Metropolitan Police and South Wales Police have been the two leading forces trialling LFR technology. According to the Met, 580 arrests were made in London over a 12-month period up to mid-2025, covering offences including rape, domestic abuse, robbery, and knife crime. Among those detained were 52 registered sex offenders who had breached their conditions.

South Wales Police has emphasised its record, reporting no false alerts since August 2019. Chief Superintendent Tim Morgan has argued the technology has been deployed ethically and lawfully, saying it has “never resulted in a wrongful arrest” in the force’s area. It has been used at large public gatherings such as football matches and concerts, where suspects for serious offences have been identified and detained.

However, these claims have not gone unchallenged. For example, earlier deployments in South Wales were the subject of a legal challenge brought by a Cardiff resident (Ed Bridges), who argued the technology was used unlawfully to scan him in public without consent. Although the Court of Appeal ruled in 2020 that South Wales Police’s use of LFR was unlawful on three grounds, including a lack of proper safeguards against arbitrary use, the force was later cleared to continue under revised guidance.

The Metropolitan Police has also faced criticism after individuals (including Londoner Shaun Thompson) were wrongly flagged by cameras during live deployments. Civil liberties groups say such errors highlight the risks of false positives, even if no wrongful arrests ultimately followed.

Examples of use include London deployments in violent crime hotspots and at high-profile events such as a Beyoncé concert, where police used the technology to search for individuals suspected of terrorism or child abuse offences. While supporters say these trials show the technology’s potential to locate dangerous offenders in crowded settings, opponents argue the risks to privacy and the possibility of misidentification remain significant.

The Case for Benefits

Proponents argue that live facial recognition allows officers to locate suspects more quickly than traditional policing methods. For example, Lindsey Chiswick, the National Police Chiefs’ Council lead for facial recognition, said the new vans provide “an excellent opportunity for policing”, with every deployment being “targeted, intelligence-led, within a set geographical location and for a defined period of time”.

The Tony Blair Institute for Global Change has also supported its use, describing it as “a no-brainer” for catching violent offenders in crowded public places. They argue that those not on a watchlist will have their faces pixelated, with no data retained.

For police forces, the vans are expected to essentially act as a force multiplier, freeing up resources and providing a visible deterrent at a time when officers are under pressure to deal with rising violent crime and anti-social behaviour.

Criticism and Concerns

Civil liberties groups remain strongly opposed to the use of this technology. For example, Big Brother Watch described the rollout as “a significant expansion of the surveillance state” and has lodged a legal challenge against the Metropolitan Police’s use of the technology. Interim director Rebecca Vincent argued that police were treating the lack of a specific legal framework as “carte blanche” to expand the practice without democratic scrutiny.

Also, Baroness Chakrabarti, former director of Liberty, called the technology “incredibly intrusive” and warned that it posed risks to privacy, freedom of assembly, and the possibility of false matches. She welcomed the consultation but criticised the absence of legislation to date, saying the technology had so far been deployed “completely outside the law”.

Amnesty International UK has also criticised the move, describing LFR as “dangerous and discriminatory”. The group warns that even if algorithms are shown to be unbiased in laboratory tests, real-world deployments risk disproportionately targeting minority communities.

The Information Commissioner’s Office (ICO), which regulates data protection, emphasised that facial recognition “does not operate in a legal vacuum” and must always be lawful, fair, and proportionate. The ICO is due to publish its findings on the use of the technology by South Wales and Gwent Police.

What Does Independent Testing Show?

To address bias concerns, the government commissioned the National Physical Laboratory to test the algorithms being used in the vans. The laboratory reported that at the settings used by police, the system was accurate and showed no bias by age, gender, or ethnicity.

Even so, critics argue that independent testing cannot address all the risks. The possibility of false positives, mission creep into less serious crimes, or erosion of trust in policing remain live debates.

Implications for Communities and Businesses

For the public, the presence of LFR vans is likely to be visible in town centres and at large public events. The Home Office has said that signage will make it clear when the technology is being used, and that data will only be retained for the period of the deployment.

Businesses in affected areas may see benefits if the vans deter shoplifting, robbery, or violent crime in retail and nightlife districts. However, there are concerns about potential impacts on footfall if people feel uncomfortable being scanned while shopping or socialising.

Neighbourhood organisations such as Neighbourhood Watch have broadly welcomed the balance between more officers and targeted technology. Chief Executive John Hayward-Cripps said the combination of “responsive policing that prioritises local relationships” with modern tools could help rebuild public trust.

For police officers themselves, the vans offer a new way to match intelligence with on-the-ground enforcement, but they also come with added responsibilities for transparency, proportionality, and accuracy.

What Does This Mean For Your Business?

The government’s decision to expand live facial recognition vans puts advanced surveillance tools directly into mainstream policing, but it also raises difficult questions about oversight. For police forces, the benefits are obvious, i.e., the vans make it easier to identify wanted suspects in crowded areas and allow officers to focus on other frontline duties. The record of arrests in London and South Wales shows the technology can be effective against serious offenders, yet the court rulings and cases of mistaken identification show why critics say it cannot be deployed without stronger safeguards.

For the public, the experience is likely to be mixed. For example, some will welcome the reassurance of extra tools against violent crime, while others will be uneasy at the idea of their faces being scanned in public. Public trust will hinge on whether officers use the vans in line with clear rules and whether those rules are seen to be independently enforced. Businesses in city centres may gain if the technology reduces theft, disorder and violence near shops and venues, although any perception of over-policing could also deter customers.

The government’s consultation on new legislation is, therefore, critical. Campaigners argue that police have been using LFR outside a proper legal framework for years, while ministers insist deployments will stay targeted and proportionate. The outcome will decide whether this expansion strengthens policing while protecting rights, or whether it fuels a deeper public backlash that undermines confidence across communities, businesses and other stakeholders.

Tech News : Croydon First Place To Get Permanent Facial Recognition Cameras

Posted on by Paul Stradling

It’s been reported that Croydon is set to become the first place in the UK (and possibly the democratic world) to host permanent live facial recognition (LFR) cameras on its streets.

Two Fixed Units This Summer

The Metropolitan Police has confirmed the installation of two fixed units in the town centre this summer, the first fixed deployment of the technology in the UK.

What Is Live Facial Recognition and How Does It Work?

Live facial recognition (LFR) technology uses cameras to scan the faces of people passing through a defined area in real time. The images are instantly compared against a police watchlist, which may include suspects, wanted criminals, vulnerable individuals, and even victims of crime.

If a match is found, an alert is sent to nearby officers who are on standby and ready to make an arrest. If there is no match or the alert turns out to be a false positive, the captured image is deleted.

The Met insists the system is accurate, quoting a false match rate of less than one percent during its mobile van trials across London. However, as this tech becomes fixed and potentially more widespread, questions are being raised about its reliability, legality, and ethical implications.

Why Croydon, and Why Now?

Croydon has long struggled with violent crime. For example, the borough recorded more than 10,000 violent offences in a single year, making it one of London’s most crime-plagued areas. High-profile tragedies like the fatal stabbing of schoolgirl Elianne Andam outside the Whitgift Centre last year have amplified public concern.

It seems that this may well be the reason why the Met has chosen Croydon as the launch site for permanent LFR deployment. It’s been reported that the fixed cameras will be installed on North End and London Road (both busy pedestrianised streets) and mounted on lampposts and buildings. Crucially, the Met says the cameras will only be switched on when officers are present and ready to respond.

According to Superintendent Mitch Carr, the move will make LFR a “business as usual” policing tool, rather than relying on the availability of roving LFR vans. “It will give us much more flexibility around the days and times we can run the operations,” he told community leaders earlier this month.

What Are the Claimed Benefits?

The Met claims that the technology is already proving its worth. For example, last year, mobile facial recognition units reportedly led to over 500 arrests across London, including the identification of suspects wanted for stalking, domestic abuse and rape. In Croydon alone, about 200 arrests were linked to LFR use, including at least two alleged rapists.

Supporters argue that fixed cameras will enhance public safety and act as a powerful deterrent to criminals. Croydon South MP Chris Philp, who also serves as the Conservative Shadow Home Secretary, called the move a “logical next step”. In a recent interview with The Times he was quoted as saying: “Those few people opposing this technology need to explain why they don’t want wanted criminals to be arrested.” It’s been reported that for some residents, the technology is a welcome intervention.

But What Are the Critics Saying?

Despite the police’s reassurances, the move has ignited fierce opposition from privacy campaigners and civil liberties groups.

Big Brother Watch, a leading advocacy group, is particularly scathing. Its interim director, Rebecca Vincent, called the Croydon deployment “an alarming expansion of the surveillance state” and part of a “steady slide into a dystopian nightmare”.

She added: “It also underscores the urgent need for legislative safeguards on LFR, which to date has not been addressed in any parliamentary legislation.”

One of the key criticisms is the absence of clear regulation. There is no UK law specifically governing the use of LFR technology, meaning that police forces are left to write their own policies on how it should be used.

Big Brother Watch also points to real-world examples of things going wrong, i.e. cases of mistaken identity by the camera systems. For example, one such case involved Shaun Thompson, an anti-knife crime campaigner who was wrongly identified as a suspect at London Bridge station. He was detained for nearly 30 minutes despite presenting multiple forms of ID proving he was not the wanted individual.

Madeleine Stone, Senior Advocacy Officer at the group, said: “Everyone gets something wrong sometimes, but what happens when the algorithm gets it wrong? Who is responsible then?”

Even more concerning, critics say, is the makeup of the ‘police watchlists’. These reportedly include not only suspects but also victims and vulnerable individuals, thereby blurring the line between surveillance and profiling.

Legality and Oversight Still in Question

The introduction of permanent facial recognition cameras comes at a time when the legal framework around the technology remains unclear. For example, a House of Lords committee recently expressed “deep concern” over its unregulated use and campaigners have called for Parliament to intervene.

In contrast, the government seems to be doubling down. The current Labour administration recently launched a £20 million fund to expand LFR use across UK police forces.

Despite this political momentum, critics remain unconvinced. Big Brother Watch recently filed legal action in response to what it calls an “unprecedented expansion” of facial recognition surveillance in both public and private sectors.

The group has warned that the Cardiff trial during the Six Nations tournament, where over 160,000 people were scanned and no arrests made, shows that mass surveillance doesn’t always yield results. In that instance, temporary LFR cameras were deployed throughout the city centre, but the operation failed to identify any wanted suspects.

Is the Technology Effective or Just Theatrical?

The core question for many people remains whether permanent facial recognition cameras will genuinely help tackle crime or whether the move is more about public reassurance and political point-scoring, i.e. more of a theatrical gesture than a real, practical solution.

Press reports about the subject (e.g. in the Metro) highlight how some Croydon residents clearly welcome the technology, particularly after years of rising violent crime and high-profile incidents in the town centre. With concerns about gang activity, knife crime and anti-social behaviour dominating local conversation, it’s no surprise that many see any effort to increase safety as a step in the right direction.

However, doubts persist. In a borough where offenders often wear masks, balaclavas or hoodies to obscure their identities, it’s unclear how effective facial recognition will actually be in real-world conditions. Some commentators have also noted how the fixed locations of the new cameras may also work against them once people know where the cameras are, avoiding them could be as simple as taking a different route.

What This Could Mean For Your Business?

The decision to install permanent facial recognition cameras in Croydon isn’t just a local policing initiative – it’s the first real test of whether this kind of surveillance can be embedded into everyday British life. With no specific laws governing its use, and police forces writing their own rules, the move exposes a major gap in oversight that lawmakers have so far failed to address.

If the technology proves effective, it could pave the way for wider adoption in other towns and cities, which would bring facial recognition into regular public and commercial spaces. For UK businesses, particularly those in high-footfall retail or transport hubs, that might mean closer partnerships with police or even the rollout of their own systems. However, this could raise fresh challenges around data protection, customer consent, and reputational risk, especially as public awareness of privacy rights continues to grow.

For residents and civil liberties groups, the concern is not just how the technology works, but also how it’s controlled, and who gets to decide where the limits lie. As Croydon essentially becomes the UK’s surveillance testbed, its experience will likely shape future policy, public trust, and the broader role of biometric surveillance in Britain’s urban life. Whether it’s a breakthrough or a step too far, the rest of the country is now watching closely.

Tech News : Meta Hunting Celeb-Scams

Posted on by Paul Stradling

Meta, the parent company of Facebook and Instagram, has revealed a new plan to combat the growing number of fake investment scheme celebrity scam ads by using facial recognition technology to weed them out.

What’s the Problem? 

Fake ads featuring celebrities, known as “celeb-bait” scams by Meta, have become a plague on social media platforms in recent years, particularly ads promoting fraudulent investments, cryptocurrency schemes, or fake product endorsements. These scams use unauthorised images and fabricated comments from popular figures like Elon Musk, financial expert Martin Lewis, and Australian billionaire Gina Rinehart to lure users into clicking through to fraudulent websites, where they are often asked to share personal information or make payments under false pretences.

Also, deepfakes have been created using artificial intelligence to superimpose celebrities’ faces onto endorsement videos, producing highly realistic content that even seasoned internet users may find convincing. For example, Martin Lewis, founder of MoneySavingExpert and a frequent victim of such scams, recently told BBC Radio 4’s Today programme that he receives “countless” notifications about fake ads using his image, sharing that he feels “sick” over how they deceive unsuspecting audiences.

How Big Is the Problem? 

The prevalence of scams featuring celebrity endorsements has skyrocketed, reflecting a global trend in online fraud. In the UK alone, the Financial Conduct Authority (FCA) reported that celebrity-related scams have doubled since 2021, with these frauds costing British consumers more than £100 million annually. According to a recent study by the Fraud Advisory Panel, financial scams leveraging celebrity endorsements rose by 30 per cent in 2022 alone, a trend fuelled by increasingly sophisticated deepfake technology that makes these scams more believable than ever.

Not Just the UK 

The impact of celeb-bait scams is even more significant worldwide. In Australia, for instance, the Australian Competition and Consumer Commission (ACCC) reported that online scams, many featuring unauthorised celebrity endorsements, cost consumers an estimated AUD 2 billion in 2023. Social media platforms, particularly Facebook and Instagram, are frequent targets for these fraudulent ads, as scammers exploit their large audiences to reach thousands of potential victims within minutes.

The US has also seen similar issues, with the Federal Trade Commission (FTC) noting that more than $1 billion was lost to social media fraud in 2022 alone, a figure that has increased fivefold since 2019. Fake celebrity endorsements accounted for a large proportion of these losses, with reports indicating that over 40 per cent of people who experienced fraud in the past year encountered it on a social media platform.

Identify and Block Using Facial Recognition 

In a Meta blog post about how the tech giant is testing new ways to combat scams on its platforms (Facebook and Instagram), and especially celeb-bait scams, Meta stated: “We’re testing the use of facial recognition technology.” 

According to Meta, this new approach will identify and block such ads before they reach users, offering a stronger line of defence in the ongoing battle against online scammers. The approach represents one of Meta’s most proactive attempts yet to address a persistent problem that has impacted both high-profile public figures and unsuspecting social media users alike.

How Will Meta’s Facial Recognition Work? 

Meta’s facial recognition ad-blocking approach will build on its existing AI ad review systems, which scan for potentially fraudulent or policy-violating ads, but will introduce an additional layer of facial recognition that will work to verify the identities of celebrities in the ads. If an ad appears suspicious and contains the image of a public figure, Meta’s system will compare the individual’s face in the ad to their official Facebook or Instagram profile pictures. When a match is confirmed, and the ad is verified as a scam, Meta’s technology will delete the ad in real-time.

David Agranovich, Meta’s Director of Global Threat Disruption, emphasised the importance of this shift in a recent press briefing, saying: “This process is done in real-time and is faster and much more accurate than manual human reviews, so it allows us to apply our enforcement policies more quickly and protect people on our apps from scams and celebrities.” Agranovich noted that the system has yielded “promising results” in early tests with a select group of 50,000 celebrities and public figures, who will be able to opt out of this enrolment at any time.

According to Agranovich, the swift, automated nature of the system is critical to staying ahead of scammers, who often adapt their techniques as detection methods improve. The facial recognition system is not only intended to remove existing scam ads but to prevent them from spreading before they can reach a wide audience. Agranovich has highlighted how a rapid response of this kind is essential in a digital landscape where even a brief exposure to these ads can lead to significant financial losses for unsuspecting victims.

When? 

This new measure is set to begin its rollout in December 2024.

Meta’s Track Record and Renewed Focus on Privacy 

It’s worth noting, however, that Meta’s deployment of facial recognition technology marks a return to a tool it abandoned in 2021 amid concerns over privacy, accuracy, and potential biases in AI systems. Previously, Facebook used facial recognition for suggested photo tags, a feature that drew criticism and prompted the company to step back from the technology. This time, Meta says it has implemented additional safeguards to address such concerns, including the immediate deletion of facial data generated through the scam ad detection process.

Privacy 

Privacy remains a contentious issue with facial recognition technology. Addressing privacy concerns over its new approach, Meta has stated that the data generated in making the comparison will be stored securely and encrypted, never becoming visible to other users or even to the account owner themselves. As Meta’s Agranovich says, “Any facial data generated from these ads is deleted immediately after the match test, regardless of the result.” Meta is keen to highlight how it intends to use the facial recognition technology purely for combating celeb-bait scams and aiding account recovery. In cases of account recovery, users will be asked to submit a video selfie, which Meta’s system will then compare to the profile image associated with the account. This verification method is expected to be faster and more secure than traditional identity confirmation methods, such as uploading an official ID document.

Scaling the Solution and Potential Regulatory Hurdles 

Meta’s new system is set to be tested widely among a larger group of public figures in the coming months. Celebrities enrolled in the programme will receive in-app notifications and, if desired, can opt out at any time using the Accounts Centre. This large-scale trial comes as Meta faces increasing pressure from regulators, particularly in countries like Australia and the UK, where public outcry against celeb-bait scams has surged. The Australian Competition and Consumer Commission (ACCC) is currently engaged in a legal dispute with Meta over its perceived failure to stop scam ads, while mining magnate Andrew Forrest has also filed a lawsuit against the company for allegedly enabling fraudsters to misuse his image.

Martin Lewis Sued Facebook 

In the UK, personal finance guru Martin Lewis previously sued Facebook for allowing fake ads featuring his image, ultimately reaching a settlement in which Meta agreed to fund a £3 million scam prevention initiative through Citizens Advice. Nevertheless, Lewis continues to push for stronger regulations, recently urging the UK government to empower Ofcom with additional regulatory authority to combat scam ads. “These scams are not only deceptive but damaging to the reputations of the individuals featured in them,” Lewis stated, highlighting the broader impact that celeb-bait scams have beyond financial loss.

Despite the New Tech, It’s Still ‘A Numbers Game’ 

Despite Meta’s new approach, the company still faces a huge challenge. For example, Agranovich has admitted that, despite robust safeguards, some scams will still evade detection, saying, “It’s a numbers game,” and that, “While we have automated detection systems that run against ad creative that’s being created, scam networks are highly motivated to keep throwing things at the wall in hopes that something gets through.” As scam networks find new ways to bypass detection, Meta acknowledges that the technology will require continuous adaptation and improvement to keep up.

What About Concerns Over AI and Bias? 

In deploying facial recognition technology, Meta has also faced scrutiny over potential biases in AI and facial recognition systems, which have been shown to have variable accuracy across different demographics. The company claims that extensive testing and review have been undertaken to minimise such biases. Also, Meta has said it will not roll out the technology in regions where it lacks regulatory approval, such as in the UK and EU, indicating a cautious approach towards compliance and accountability.

Meta says it has “vetted these measures through our robust privacy and risk review process” and is committed to “sharing our approach to inform the industry’s defences against online scammers.” The company has also pledged to engage with regulators, policymakers, and industry experts to address ongoing challenges and align on best practices for facial recognition technology’s ethical use.

What Does This Mean for Your Business? 

Meta’s latest move to integrate facial recognition technology into its anti-scam measures signals a significant shift toward tackling the complex world of celeb-bait scams. However, as Meta ventures back into using facial recognition, it’s clear the company must balance robust security with privacy, a concern that continues to shadow the rollout. While the technology holds promise, particularly in increasing detection speed and reducing the frequency of celebrity scams, it will undoubtedly be scrutinised by both users and regulators who have long questioned the use of facial recognition on such a broad scale.

For everyday Facebook and Instagram users, Meta’s new facial recognition feature could mean greater security and fewer encounters with fake ads that exploit public figures for fraudulent schemes. If successful, the initiative could lessen the risk of users falling victim to scams that impersonate well-known personalities to promote fake investments or products. The added layer of facial recognition should serve as a safeguard, reducing the frequency of these fake ads in users’ feeds and building a safer browsing experience across Meta’s platforms.

For celebrities and public figures, this development is a significant step towards reclaiming control over their public images, which are often misused without permission. The new system will help protect their reputations, preventing unauthorised use of their likenesses in fraudulent ads. Figures like Martin Lewis, who has been vocal about the damage these scams cause, could benefit as Meta finally implements more targeted measures to shield them from unauthorised endorsements.

The impact of this initiative may extend to legitimate advertisers as well. Meta’s crackdown on celeb-bait scams will likely improve ad integrity on its platforms, helping businesses that rely on Facebook and Instagram to reach audiences without the risk of association with deceptive content. A cleaner, more trustworthy advertising environment could enhance user trust and, in turn, benefit brands that promote genuine products and services. As Meta focuses on strengthening its ad review systems, legitimate advertisers may find their content reaching more engaged, security-conscious users who are less wary of the ads they encounter online. In this way, Meta’s facial recognition technology could not only shield users and celebrities from scams but also foster a more secure, credible marketplace for businesses across its platforms.