Hong Kong has already installed almost 4,000 CCTV cameras under a police crime-fighting program. That number will increase to a total of 60,000 by 2028, according to documents submitted to the legislature. Hong Kong - Hong Kong plans to install tens of thousands of surveillance cameras that will make use of AI-powered facial recognition, the city's security chief said on Friday, bringing it closer to China where authorities often monitor public spaces with cutting-edge technology. The Chinese finance hub has already installed almost 4,000 closed-circuit television (CCTV) cameras under a police crime-fighting program. That number will increase to a total of 60,000 by 2028, according to documents submitted to the legislature.

The UK government's proposed AI-powered crime prediction tool, designed to flag individuals deemed "high risk" for future violence based on personal data like mental health history and addiction, marks a provocative new frontier. Elsewhere, Argentina's new Artifical Intelligence Unit for Security intends to use machine learning for crime prediction and real-time surveillance. And in some US cities, AI facial recognition is paired with street surveillance to track suspects. The promise of anticipating violence Minority Report-style is compelling.

South Wales Police has been criticised over its live facial recognition use at events including Harry Styles and Beyoncé concerts in Cardiff. The Metropolitan Police has used it several times this year, including at the King's Coronation in May.

South Wales Police has been criticised over its live facial recognition use at events including Harry Styles and Beyoncé concerts in Cardiff. The Metropolitan Police has used it several times this year, including at the King's Coronation in May.

Fox News correspondent Gillian Turner has the latest on the president's focus amid calls for an impeachment inquiry on "Special Report." Six police officers swarmed Porcha Woodruff's Detroit home before 8 a.m. one morning in February while she was getting her 12- and 6-year-old kids ready for school, the federal lawsuit says. "I have a warrant for your arrest, step outside," one of the officers told Woodruff, who initially thought it was a joke, according to the lawsuit. Officers told her she was being arrested for robbery and carjacking. Do you see that I am eight months pregnant?"

Moves to ban live "Big Brother" facial recognition technology from being deployed across the streets of the EU will be tested in a key vote at the European parliament on Thursday. The amendment is part of a package of proposals for the world's first artificial intelligence laws, which could see firms fined up to €10m (£8.7m) or removed from trading within the EU for breaches of the rules. But the ban is expected to be challenged by a group of centre-right MEPs on the grounds that biometric scanning should be deployed to combat serious crime such as terrorism. An amendment to Article 5 of the proposed Artificial Intelligence Act prohibiting the use of cameras to follow people around shops, streets, parks or any other public places will go before the committee on Thursday. It will also ban companies from using AI to identify individuals by match scans on CCTV with images posted by users on Instagram, Facebook or other social media platforms.

The Ukraine defense ministry announced that it is now using facial recognition technology from an American startup to combat misinformation, identify the dead, and expose Russian assailants. The technology, which is like a search engine for faces that aggregates data from millions of social media users across the open web, had previously stirred controversy due to privacy complaints. After the war broke out, the American-based artificial intelligence company Clearview reached out to Ukraine's government, offering its services free of charge. This week, the collaboration became official and Clearview's facial recognition tech is now claimed to be used for security purposes, such as vetting people of interest at checkpoints. Clearview claims that it has amassed a database of over 10 billion photos posted publically on the internet from sites like Facebook, Instagram, Flickr, and Getty Images.

Nowadays, face recognition systems have become an integral part of our lives. Research shows that a face plays a significant role while interacting with people, as it elucidates people's identity, making facial recognition systems a crucial aspect of security solutions in many organizations. As of today, many corporate and government firms are rapidly adopting the face recognition technology across the world due to its invulnerability to threats, reliability, and identifying criminals. Moreover, the face recognition systems provide vast benefits as compared to other biometric security solutions i.e palm print and fingerprint. To have a deep knowledge of how facial recognition systems work is vitally important in order to explore the technical, social, and cultural implications of these systems. Let's exemplify a bit how a facial recognition system works!

Facial Recognition technology detects faces in the camera's field of view and matches them against faces previously stored in a database. Anti-spoofing is provided through liveness testing without the need for a stereo or a 3D camera. Face Recognition technology is now taking a further step as it is being combined with IP surveillance. Gemalto, a part of the Thales Group and a company that focuses on Digital Identification and Data Protection in order to counter the two root causes of cyberattacks, identity theft, and unencrypted data, defines Facial Recognition as the process of identifying or verifying the identity of a person using their face. It is a technology that captures, analyzes, and compares patterns based on the person's facial details. The face detection process is a basic and essential step allowing the systems to detect and locate human faces in a set of images and videos.

Recent studies demonstrate that machine learning algorithms can discriminate based on classes like race and gender. In this work, we present an approach to evaluate bias present in automated facial analysis algorithms and datasets with respect to phenotypic subgroups. Using the dermatologist approved Fitzpatrick Skin Type classification system, we characterize the gender and skin type distribution of two facial analysis benchmarks, IJB-A and Adience. We find that these datasets are overwhelmingly composed of lighter-skinned subjects (79.6% for IJB-A and 86.2% for Adience) and introduce a new facial analysis dataset which is balanced by gender and skin type. We evaluate 3 commercial gender classification systems using our dataset and show that darker-skinned females are the most misclassified group (with error rates of up to 34.7%).