Twins Test FBI’s Biometrics How studying twins helps the Bureau evaluate and improve AI biometric systems A twin takes part in biometrics screening during the 2026 Twins Days Festival in Twinsburg, Ohio. Every August, thousands of siblings gather in Twinsburg, Ohio, for the annual Twins Days Festival. While the event is primarily a social celebration of multiples from around the world, it also serves as the setting for one of the FBI's most distinctive scientific research efforts. For more than 15 years, a partnership between the Bureau and West Virginia University (WVU) has utilized this gathering to evaluate and improve biometric technologies. Tucked away from the main festivities is an area known to regulars as "Research Row," where white tents stand alongside food trucks and souvenir stands. Here, researchers from a variety of industries invite festival-goers to step out of the summer heat and participate in various studies. The FBI and WVU are a staple there—hosting hundreds of individuals who volunteer to take part in a study designed to answer one of biometric science's most pressing questions: How do you accurately distinguish between two people who look almost exactly alike? The resulting dataset—one of the few of its kind in the world—helps researchers evaluate fingerprint, iris, and facial recognition technologies, improving their accuracy while deepening the understanding of their limitations. The ultimate biometric challenge “From a biometrics perspective, identical twins are the ultimate challenge because we are trying to uniquely identify one person from another,” said Ben Smith, a biometric program manager in the FBI’s Criminal Justice Information Services Division. “When it comes to facial recognition, the identical twins scenario is probably the most difficult challenge because they can look practically the same.” That difficulty is precisely what makes twins so valuable to science. Although identical twins often share remarkably
Aug 11, 2026 · via fbi.gov
Law review: You Think You’re Hot. You Probably Aren’t. License Plate Readers, Hot Lists, and the Fourth Amendment If you drove through Truckee sometime last month, your car was probably photographed by one of the Town’s Flock Safety automated license plate readers (ALPR). Odds are no one ever looked at the picture. Like a dating app, interest exists only if you meet someone else’s criteria. Here, that means your license plate appears on the hot list. If it doesn’t, no one looks at your photo twice. For once, that’s a compliment. That naturally raises three questions. What exactly is in the photograph? Is this legal? And perhaps most importantly: what on earth is a “hot list?” The cameras photograph cars, not people. They capture the rear of the vehicle, read the license plate, and note details such as the make, model, color, roof rack, and bumper stickers. They do not use facial recognition and cannot identify the driver. The system knows a surprising amount about your car and almost nothing about the person driving it. Every license plate is automatically compared against a “hot list” of vehicles associated with stolen cars and AMBER Alerts. If there is a match, an officer is notified and must visually confirm the vehicle before taking any action. If there is no match, no one looks at the image again, and it is automatically deleted after 30 days. According to the Truckee Police Department, auto thefts increased 300 percent in 2022. Truckee researched ALPR technology, secured grant funding, and launched a 17-camera pilot program in July 2023. Since then, the department credits the cameras with helping identify homicide suspects, missing persons, burglary suspects, and fraud offenders. One homicide suspect tried escaping through Tahoe Donner’s back roads but was quickly located after an ALPR alert. During
Aug 11, 2026 · via sierrasun.com
Immigration and Customs Enforcement (ICE) plans to pay LexisNexis millions more dollars for continued access to data it can feed into a Palantir platform, according to newly published procurement records. The data is to help, among other sections, ICE’s Enforcement and Removal Operations (ERO), the part of ICE focused on deportation. The documents provide some more insight into the sort of information ICE intends to use Palantir to process. In January, 404 Media revealed the existence of ELITE, a system Palantir made for ICE that helps the agency find which neighborhoods to target by bringing together data from private suppliers and government agencies. The news comes as ICE arrested more than 51,000 people in July, many of those at airports. The data is to support “all aspects of ICE screening and vetting, lead development, and criminal analysis activities,” one of the documents says. That also includes identifying what ICE perceives as fraud “before crime and fraud can materialize and detecting and reporting elements of crimes involving the exploitation or attempts to exploit the immigration and customs laws of the United States.” ICE anticipates paying LexisNexis $6.7 million, according to the records. LexisNexis has long provided data to ICE across multiple administrations. In this new procurement record, ICE is looking to continue access to “to LexID and Accurint Virtual Crime Center,” according to a listing posted along with the document. LexID and Accurint are LexisNexis tools that take a wealth of data — “over 82 billion public and proprietary records from more than 10,000 sources” according to the company’s website — and link them together to help law enforcement locate people. The document suggests ICE wants to pair these capabilities and data with Palantir systems, too. One part reads, “The government's requirement is that the database must be able to application
Aug 11, 2026 · via 404media.co
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Aug 11, 2026 · via facebook.com
Mayflower has become the second Central Arkansas city in the last week to ditch its Flock Safety license plate readers. Interim Police Chief Brittany Byrd announced Monday that after “evaluating the capabilities” of the cameras, Mayflower will discontinue their use and will “rescind their deployment within the city immediately.” The move comes three days after the city of Cabot announced its decision to stop using Flock cameras pending a “comprehensive review.” Last month, the police chief in Pea Ridge announced his city would no longer use the devices. In her announcement, Byrd acknowledged Flock cameras have aided in the investigation of criminal cases across the country, including in Mayflower. But despite the benefits, she wrote, “we believe them to be intrusive in nature.” “The Mayflower Police Department will not participate in tactics which compromise or infringe upon the liberties entitled to law-abiding citizens,” Byrd wrote. Flock license plate reader cameras take pictures of passing cars and log their license plate numbers, comparing the captured information against so-called hot lists assembled by the law enforcement agencies that operate them. Flock Safety, the company that manufactures the devices, states on its website that the cameras don’t use facial recognition software but boast the ability to search captured images based on a description of a vehicle — such as its color, make and model, or unique features such as bumper stickers — if a plate number isn’t known. Many cities in Arkansas use the cameras, including Little Rock, North Little Rock, Conway, Hot Springs, Benton, Bryant, Jacksonville and Sherwood. Nationally, more than 5,000 law enforcement agencies have bought Flock’s license plate readers, the company’s website states. Byrd said Mayflower signed a multi-year agreement with Flock Safety in 2023 that runs through 2027. “Police Department personnel have been communicating with representatives from Flock Safety
Aug 10, 2026 · via arkansasonline.com
Two bars in San Francisco's Castro District are pausing the use of facial recognition technology to verify identities following community backlash.
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Aug 10, 2026 · via ktvu.com
Windows 11 is pulling picture passwords and pushing people to PINs, passwords, and biometrics Microsoft is phasing out picture passwords in favour of more secure methods. Windows 11 will soon lose a way to log in to a PC. A recent update removes the option to set up a new picture password. If you already have a picture password on your PC, you can continue to use it, but the feature is being phased out. Microsoft is on a mission to push the world beyond passwords. The tech giant generally recommends a PIN, facial recognition, or a fingerprint to log in to Windows 11. Passkeys are often the top recommendation for authentication, though you cannot log in to a Windows 11 PC with a passkey. But back in the days of Windows 8, Microsoft introduced the option to unlock your PC using a picture. That feature, which has remained available across Windows 10 and Windows 11, allows you to unlock your PC with a series of touches or gestures, like tapping the eyes of a smiley face then swiping across the face's mouth. You could use a combination of three types of gestures as part of a picture password: circles, straight lines, or taps. Picture passwords were a fun way to show off the touch-centric nature of Windows 8, but they aren't as secure as a passkey or even a strong password. Since people often pick gestures or taps around key objects, hackers can sometimes guess the gestures needed to unlock a PC. People can look at the smudges on your screen to guess where you touch frequently. A research paper from 2013 that was flagged by Neowin highlights the risks of picture passwords. If you have a picture password set up now and want to continue to use it,
Aug 10, 2026 · via windowscentral.com
British Transport Police (BTP) will begin using live facial recognition technology at Transport for London (TfL) Underground stations as part of an ongoing trial. The first deployment will take place at Victoria Underground station on Tuesda (August 11) as part of an extended pilot now running until November. It will then rotate between deployments at Underground and Network Rail stations. Chief Superintendent Chris Casey, BTP's senior officer responsible for the project, said: "This marks an important new stage in our trial of Live Facial Recognition technology. "Expanding deployments into London Underground stations will help us assess the technology in a different transport environment while continuing to refine how it is used across the railway network. "Our deployments are intelligence-led and focused on identifying people wanted by the police or courts, including those suspected of serious offences and those who may be breaching bail conditions or court orders. "Our focus remains on protecting the public, preventing crime and bringing offenders to justice, while ensuring the technology is used lawfully, proportionately and transparently." The cameras work by scanning faces and comparing them to a watchlist of people who are wanted by the police or courts, or who are subject to conditions designed to protect the public. Read more - 1,500 London bus drivers to strike - more than 40 routes affected - London's cleanest and dirtiest boroughs for food hygiene have been revealed - This student is giving away free coffee on the London Underground If a match is found, an alert will be triggered and reviewed by an officer before any action is taken. Siwan Hayward, Director of Security, Policing and Enforcement at TfL, said: "Live facial recognition has the potential to be a powerful additional tool in helping police quickly identify those wanted for high-harm offences, including sexual offences, and
Aug 10, 2026 · via yourlocalguardian.co.uk
Privacy concerns raised over Australian-first live AI police face scanning trial An Australian-first trial of live AI facial recognition technology by a police force has been criticised by privacy experts and legal advocates. The mass AI surveillance pilot has been rolled out in Western Australia and is being closely watched by law enforcement agencies across the country. Since the trial began in June, cameras linked to facial recognition software have scanned more than 130,000 people in Perth and Fremantle, comparing their faces against a police watchlist in real time. Western Australian police say the results are promising but questions have been raised about an opaque watchlist and trial site locations that some say may target First Nations people. In June, the Western Australian Police announced it would be the first police force to use live facial recognition technology on the public. Facial recognition technology has become increasingly commonplace. It includes simpler one-to-one systems that check whether a single face matches a particular identity, like those used to unlock a mobile phone. It also includes the more complex one-to-many systems like those used in Bunnings to compare faces of customers against a database of people suspected of activity including theft or abuse of staff. Since June, WA Police have been trialling that more complex type of system. Using tech company NEC's Neoface m40 product, a pilot program scanned more than 130,000 faces around Perth and Fremantle in the first week of the trial. It compared their faces against a watchlist of about 4,000 people, including people accused of serious offences, people who are missing, and people who may pose a risk to themselves or others, police said. WA Police celebrated the early results from the trial, which resulted in 33 alerts and 18 arrests. Of the faces scanned in the first
Aug 10, 2026 · via abc.net.au
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Aug 10, 2026 · via iopscience.iop.org
Restaurant operators rarely have two days that look alike. New challenges emerge constantly, and keeping up means making dozens of decisions with limited time and incomplete information: Why did food costs spike at one location? Which limited-time offer actually drove profits? Why is one store consistently outperforming another? Finding those answers often means digging through multiple reports, exporting spreadsheets and piecing together data from different systems, a process that takes time and distracts restaurant operators from their key hospitality role. Surfacing data and pattern recognition are where AI excels. However, when restaurants use a generic AI model, it can’t dive into what your restaurant needs to know about its own operation, explains Matt Sundberg, SVP, Product at Craftable. That’s the impetus behind “Crafti,” the AI model from Craftable, a software platform that replaces disconnected spreadsheets and manual processes with automated, real-time visibility into food costs, vendor spend and operational margins. “Crafti’s conversational layer allows general managers to ask anything and receive a grounded answer, along with the path forward, without having to wait on a colleague or a support ticket,” Sundberg says. From Reports to Conversations Through conversational AI, GMs can interact with operational data naturally, uncovering insights that help them make better decisions across every aspect of the business. “Restaurant operators are surprised to find that Crafti doesn’t just give an answer, but actually drafts solutions,” Sundberg says. For example, if a GM asks it to describe next week’s order, Crafti will draft a purchase order against the actual vendor catalog, pricing and pack sizes. Or, after providing a cocktail name, photo or PDF, it will draft a costed recipe matched to actual inventory. Wondering how Crafti can level up your own operations? Here are some examples of actual questions operators have asked to spark ideas about how it
Aug 10, 2026 · via restaurantdive.com
Facial recognition technology leads to 11 arrests at Manchester's Caribbean Carnival Tens of thousands attended the two-day event Last updated 14 hours ago Manchester's Caribbean Carnival has passed without any significant problems, according to Greater Manchester Police. Tens of thousands of people attended the two-day event, taking in Saturday's parade, live performances and other activities over the weekend. Officers used Live Facial Recognition, known as LFR, as part of their policing at this year's carnival. The technology scans faces and alerts officers when someone is wanted or subject to a court order, with all images deleted within 24 hours, according to Greater Manchester Police. LFR has previously been deployed at the Brit Awards, the MOBO Awards, football matches, the Manchester Marathon and in town centres. Eleven arrests over the weekend There were 34 alerts from the technology over the two days. Eleven of these led to arrests, for offences including breach of a sexual harm prevention order, fraud, failing to appear at court, and theft. The remaining 23 alerts included eleven registered sex offenders, whose conditions were checked by officers, and five people known to regularly carry knives. A missing child was also identified with the help of the technology, police said. Greater Manchester Police said no one was misidentified during any of the scans carried out over the weekend. More than one million scans since launch LFR has been used more than one million times since it was introduced in October last year, according to the force. In that time, only one person has been mistakenly identified, a white female at the Manchester Marathon, police said. Officers were on hand throughout the carnival to explain how the technology works and to answer questions from the public, Greater Manchester Police said. Assistant Chief Constable Rick Jackson, who was Gold Commander
Aug 10, 2026 · via planetradio.co.uk
Abstract Surface defect segmentation (SDS) is challenging in automated inspections due to the high variability of defects amid complex metallic textures. The defects show significant variations in size, shape, contrast, and spatial distribution. Existing segmentation methods struggle to jointly model fine boundary cues, omni-directional long-range dependencies, and multi-scale context in a single framework. To address these issues, we propose Edge-Guided Omni-Directional Attention Network (EGONet), a novel hierarchical architecture for metallic SDS. EGONet offers rich, multi-level intermediate features that capture both fine-grained details and broader semantic information. It also enhances multi-scale contextual understanding by integrating a Dense Atrous Spatial Pyramid Pooling (DASPP) module with four parallel dilated-convolution branches and a learnable residual blend for maintaining spatial resolution. A Sobel-guided Edge Attention Module (EAM) highlights high-frequency boundary cues at the shallowest feature level via auxiliary edge supervision. The proposed Omni-Directional Attention (ODA) decomposes spatial attention into four axes to model long-range dependencies across all orientations via a two-stage refinement. A Quad-Statistical Spatial Attention Module (SAM) leverages quadruple pooling to deliver finer spatial sensitivity than traditional dual-pooling methods. Moreover, the Efficient Channel Attention (ECA) module recalibrates channel responses to suppress background interference. Lastly, a Bilateral Feature Integration Block (BFIB) combines the dual attention pathways via complementary asymmetric gating and residual stabilization. Extensive ablation studies validate each component’s contribution toward improving overall detection performance. Experiments on two benchmark datasets demonstrate that EGONet achieves competitive performance against state-of-the-art methods, with leading results across multiple defect categories on MT-Defect and strong generalization on SD900. Subjects Introduction Surface defect detection (SDD) is critical for maintaining product quality and operational efficiency in modern manufacturing. Conventional inspection methods suffer from fundamental limitations in precision and adaptability to complex patterns. Human-based inspection is inherently slow and prone to inconsistent judgments1. Ultrasonic methods are constrained by material acoustic properties and require
Aug 10, 2026 · via nature.com
Gay bars in San Francisco have discontinued the use of artificial intelligence-assisted face scanning technology after the community raised privacy concerns. Both Badlands and Toad Hall announced on Saturday they would stop using Patronscan technology, according to the San Francisco Chronicle. “Effective immediately, we are pausing the use of Patronscan while we review our ID verification and security practices,” Brian Aranda, director of operations at both bars, told the newspaper in a statement. “Our security teams will continue to thoroughly check IDs manually during this time. We appreciate everyone who has shared their concerns and remain committed to providing a safe and welcoming environment for all.” Related: Why are San Francisco gay bars scanning patrons’ faces? The Castro District bars sparked anger and scrutiny when the security measures were first deployed earlier this year, especially among LGBTQ+ patrons of establishments often seen as havens for those not publicly out. Controversy intensified after reporting by the San Francisco Gazetteer. The publication also reported on the use of AI-assisted recognition software at The Mix, where managers have defended the screening technology with local press. "It keeps my customers safe. We've had no bar fights, vandalism and theft is down," a general manager told a Bay Area NBC affiliate in June. The Mix has not made any announcements about the use of the technology since concerns were first raised. The technology is intended to flag fake IDs and identify individuals with a history of causing violence at the clubs. Signage has told patrons before they enter that the technology will be used, though many visitors told the Gazetteer they were unaware images of them would be taken and stored until they were in front of a camera themselves. Among privacy advocates, the use of Patronscan’s technology has raised concerns for years. The OneZero
Aug 10, 2026 · via advocate.com
Law enforcement agencies and governments have long used biometric modalities for accurate identification, enabling law enforcement activities and immigration and border controls. Our data can be collected and lawfully used through facial, iris or fingerprint recognition tools and, now, a new biometric modality has emerged in tattoo recognition technology, which can verify who someone is by the permanent visible marking on their body. It may not be part of an individual’s DNA or genetic makeup, however a tattoo modifies the body and can contribute to identifying unique features about someone to help authorities in investigations. We have introduced a panel at Identity Week America on NIST’s world-class evaluation of tattoo recognition, titled “Tatt-E: Benchmarking the state of the art in tattoo recognition”. Find the session on our agenda. Historically, authorities have searched tattoo image databases using text descriptions of tattoos to assist in their investigations. However, the effectiveness of this method has been limited by the subjectivity of text-based descriptions. Recent advances in technology have enabled developers to leverage artificial intelligence (AI) to create automated, image-based tattoo search capabilities. Compared to traditional approaches that rely on subjective text descriptions, image-based searching provides a more objective means of retrieval. To determine whether these systems are fit for purpose, decision-makers will need to know their capabilities and limitations. NIST is running an evaluation program to assess the accuracy of tattoo recognition algorithms. This evaluation will measure the capability of these algorithms to detect tattoos in an image and to perform automated matching of different images of the same tattoo from the same subject over time. This talk, presented by Mei Ngan, a scientist at NIST, will present the state-of-the-art accuracy in image-based tattoo recognition and discuss current capabilities and limitations of the technology. NIST evaluates tattoo recognition technology as a secondary biometric
Aug 10, 2026 · via identityweek.net
"We Envision Growth Strategies Most Suited to Your Business" Revolution of AI integration in ultrasound imaging dates back to the late 1970s, when researchers at different institutions experimented with primary pattern recognition. This marked ultrasound's transition from interpretation to systematic analysis. Currently, edge AI helps in processing images on portable units for instant feedback in emergency settings. Moreover, handheld scanners currently incorporate beamforming chips matching cart-based systems. Organizations also collaborate with clinicians to validate the use of these solutions across diverse regions. AI in ultrasound imaging has grown from a primary development to a crucial diagnostic component, empowering healthcare providers globally. Firms are also adopting ethical standards, ensuring reasonable access and precision diagnostics, elevating patient outcomes. Fortune Business Insights reported that the industry for AI in ultrasound imaging is noticing a substantial growth with a CAGR of 26.61% and is expected to reach a revenue share of USD 3.43 billion in 2026 to USD 22.62 billion by 2034. GE HealthCare Technologies Inc. is a well-known brand providing AI in ultrasound imaging systems that improve scan guidance, workflow productivity, and clinical decision support. Headquartered in the U.S., its Voluson Expert Series and LOGIQ platforms use automation tools to speed assessments and strengthen image consistency. In January 2025, the company received FDA clearance for updated Voluson Expert systems, adding AI features for women’s health imaging. GE HealthCare continues to widen intelligent ultrasound tools for obstetrics, general imaging, and point-of-care use across demanding clinical settings. In February 2026, the company expanded its BARDA collaboration with around USD 35.0 million to improve AI powered ultrasound. Koninklijke Philips N.V., headquartered in the Netherlands, advances in AI in ultrasound imaging through platforms that automate measurements, support cardiac assessment, and extend access to clinical care. Its Lumify handheld ultrasound and EPIQ CVx systems incorporate AI features from
Aug 10, 2026 · via fortunebusinessinsights.com
Abstract The tomato plant is considered one of the most important crops in the world, yet it is vulnerable to various diseases that affect crop quality and agricultural productivity. These challenges have driven the need for an efficient and intelligent plant disease detection system. With the development of computer vision and artificial intelligence, this proposed methodology based on deep learning for tomato leaf diseases has been presented. Two public datasets: Taiwan DS with nine classes and Tomato Leaf Diseases Detection Computer Vision Dataset (TLDDCV DS) with seven classes have been used to test this system. This system begins with plant image processing, which includes gamma correction and bilateral filtering, to enhance image quality and clarity while preserving key disease features. Then, a genetic metaheuristic algorithm was used to automatically select the most significant hyperparameters, further optimizing both processing time and accuracy. After that, the tomato leaf disease detection applies the You Only Look Once version 11 Nano (YOLOv11n) model. The YOLOv11n backbone is edited through a Data-efficient Image Transformer (DeiT) to improve the system’s capacity for learning global contextual information and long-range dependencies. Experimental results demonstrate that the proposed system outperforms existing methods. It achieved an average mAP@50 of 97.8%, mAP@50-95 of 93.4%, precision of 97.3%, recall of 93.8%, and F1-score of 95.5% on the Taiwan dataset. Additionally, it achieved an average mAP@50 of 87%, mAP@50-95 of 48%, precision of 83.9%, recall of 70.3%, and F1-score of 76.4% on the TLDDCV dataset. These results demonstrate the generalizability and effectiveness of the proposed system in real-world agricultural situations. Similar content being viewed by others Subjects Introduction Tomato is the most widely consumed and economically significant vegetable crop worldwide, second only to potato in global importance1,2. It is used as both a common dietary staple and a fruit-like ingredient, making it highly
Aug 10, 2026 · via nature.com
Challenging GPUs, bypassing HBM, digging deep into Cerebras behind the largest chip in history Ten years ago, this was a company that no one had high hopes for. From the very first day of its establishment, it only wanted to build a type of chip that had never been made before. It tried to challenge Nvidia's dominant position, but repeatedly hit a wall in the early days of its founding and was on the verge of bankruptcy many times. Ten years to sharpen a sword. In May this year, Cerebras finally went public, with its market value once approaching 100 billion US dollars. CEO Andrew Feldman said: We are willing to cooperate with every hyperscaler to improve AI inference speed, except for Nvidia. We had the honor to interview Cerebras' early investors, the researchers who first proved that Cerebras' products could be deployed, and discussed with senior executives in charge of products inside Cerebras about the company's transformation in the past two years and its moves after IPO. After piecing together these clues, we were surprised to find that to understand the glory of Cerebras' listing, we need to go back 10 years. Go back to a whiteboard, a startup that was about to go bankrupt, a physics gamble that almost no one believed in, and an AI lab that owned the world's largest language model at that time, and how it became the most critical page in this story at an impossible point in time. The following is the story of Cerebras. 01 Baidu AI Lab Discovering the Scaling Law In 2014, Andrew Ng left the Stanford AI Lab and joined Baidu. Inspired by Google Brain, Baidu invested 300 million US dollars to establish an AI lab located in Silicon Valley. Their main goal was to make deep learning
Aug 10, 2026 · via eu.36kr.com
Women and children could be disproportionately impacted by the use of such technology Attorney-general Michelle Rowland has penned a letter to privacy commissioner Carly Kind regarding possible privacy concerns flagged by the community over the use of smart glasses, which are embedded with cameras that can take photos and videos. Rowland requested that the Office of the Australian Information Commissioner (OAIC) prioritise looking into the privacy implications of such gadgets, noting their rising accessibility in the country. She indicated that women and children in particular could be disproportionately impacted by the use of the technology for harmful conduct like inappropriate recording, harassment and surveillance. “Unlike other forms of technology, smart glasses may be used more discreetly, making it harder to know when you are being recorded”, Rowland said in a statement. In 2024, the International Bar Association raised concerns regarding Meta and Ray-Ban's AI-powered smart glasses, which came out in late 2023. The body highlighted issues with data security. “How do you provide for the rights of the data subject? If you film someone without authorisation to what extent is that legal?” asked Larissa Galimberti, then-chair of the IBA’s cybersecurity subcommittee. Callum Sinclair, who leads the technology and commercial firm at Scotland firm Burness Paull, noted that smart glasses wearers could record people and obtain personal data without consent. Rowland said the government considered the OAIC’s expertise and oversight to be key to tracking developments in this field. “The OAIC regularly monitors the effects of new technologies on privacy – and the government has every faith that they will identify any new privacy risks and mitigation measures”, the attorney-general said. “The government is continuing to work on the next phase of privacy reforms to ensure our privacy laws are fit for purpose in the digital age”. The OAIC recently updated
Aug 10, 2026 · via thelawyermag.com
09 Aug FLOCK EXPERT WITNESS AND TESTIMONY CONSULTANT: PRIVACY, SECURITY, IDENTITY, ETC. A Flock Safety expert witness and testimony consultant is a person with knowledge relevant to the company’s technology, automated license plate recognition (ALPR/LPR), vehicle-location data, digital evidence, law-enforcement use of license-plate-reader systems, privacy and surveillance technology, or another issue involving related matters or evidence. Like you’d hear from top Flock Safety expert witness testifying consulting pros, the firm is a public-safety technology company whose products include license plate reader cameras and other technologies. Its LPR system is designed to capture images and data relating to vehicles and license plates and make that information searchable for authorized users. The way Flock Safety expert witnesses tell it, the firm describes its LPR technology as providing vehicle information, including license plate information and vehicle characteristics, along with dates, times, and camera locations. In a legal proceeding, the technology itself may become important evidence. For example, a case might involve a question about: - Whether a particular vehicle was captured by a Flock camera - What the image actually shows - Whether a license plate was correctly read - How the system identified vehicle characteristics - When an image was captured - Where a camera was located - How the evidence was stored - Who accessed the information - Whether data was shared - How long the information was retained - Whether the system was operating properly - How reliable a particular identification is - How an investigator interpreted Flock results A Flock Safety expert witness can help explain technical subjects that ordinary judges, jurors, attorneys, or other decision-makers may not be expected to understand without specialized knowledge. What Is Flock Safety? Flock Safety describes itself as a public-safety technology company whose products include LPR cameras, video cameras, gunshot-detection sensors, real-time crime-center
Aug 9, 2026 · via futuristsspeakers.com