Law Enforcement & Public Safety

SingularityNET Integrates Aigents Social Intelligence Services, Creating Significant First-Mover…


What is intelligence? Is it only a property of self-aware beings? Is it built-in or has it evolved through interactions with the surrounding environment? Maybe it's the type of intelligence described by Stanislav Lem in Solaris. Or maybe it's a social phenomena of emerging cooperative behavioral pat...

Chinese police use face recognition glasses to catch criminals

New Scientist

For the past two months, cyborg police officers have screened travellers passing through Zhengzhou railway station in China. The officers, wearing smart glasses with built-in face recognition, have caught seven fugitives and 26 fake ID holders already. According to local media, some of the fugitives were wanted for alleged involvement in human trafficking cases. Zhang Xin, at LLVision, the firm that developed the GLXSS Pro smart glasses, says the glasses are very light so the police officers can wear them all day. Feedback so far been positive, she says. …

Robots could become "Klashnikovs" of future after entering black market: Tech thinktank


Robots equipped with artificial intelligence technologies could become the "Kalashnikovs" of the future after entering the black market, a report by the technology think tank ThinkTech has suggested, state-run Anadolu Agency reported on Feb. 13. ThinkTech is an offshoot of Defense Technologies …

Isis videos targeted by artificial intelligence that can detect propaganda before it's uploaded

The Independent

Artificial intelligence technology that can detect Isis videos and prevent them from being uploaded is being released to stop the spread of the "poisonous" material. Developers funded by the Home Office are sharing their software for free with any website or app in the world in the hope it will mak...

Machine Learning And Business Problem-Solving


For our lab, we began digging into the application of machine learning beginning in 2014, exploring its application in everything from supply chain optimization to factory automation and retail, including predicting terrorist attacks. Where we can apply knowledge for a given domain and weave it into...

Chinese Police Now Use Facial Recognition Glasses to Fight Crime


Facial recognition technology will change the world. Still emerging into the mainstream, facial recognition technology has the potential to reshape that way you interact with the fringes of both the digital and real world. For the uninitiated, facial recognition is a biometric technology that scans people's face, photographs and recognizes them as an individual. Impressively, the technology can identify facial features like the space between the eyes, the depth of the eyes sockets, the width of the nose, cheekbones and the jawline. This technology has been recently entered the mainstream with Apple's iPhone X facial recognition feature, but the appeal of facial recognition goes beyond just consumer goods, and will eventually be an integral part of security. Recently, Chinese police officers have been spotted wearing surveillance sunglasses equipped with facial recognition software. In Zhengzhou, China Police offers have implemented crime-fighting technology that can be found in some of your favorite sci-fi movies. Police officers in the region are now wearing glasses that allow them to identify individuals in the crowd using facial recognition technology Though they were reported to have been launched last year, it looks like they have been officially implemented. Over the years has China has lead the world in surveillance technology, implementing artificial intelligence into their surveillance programs. The software technology created by LLVision aims to create another level of security and improve police work. The glasses have already proven its merit helping police officers sport seven people wanted for major crimes and even identified 25 people using someone else's identity. The facial recognition technology glasses help solves the issue with lag time between spotting someone who may be a criminal and calling the authorities before the person of interest disappears: an issue with a lot of traditional surveillance setups. Each pair of glasses is connected to a small, easily accessible handheld device that uses facial recognition software to compare what a police officer sees and compares that information with a pre-loaded dated base in lighting fast speeds of one-tenth of a second. As stated by LLVision Chief Executive Wu Fei "By making wearable glasses, with AI [artificial intelligence] on the front end, you get instant and accurate feedback.You can decide right away what the next interaction is going to be." Though people are excited about the potential security applications, many people have obvious concerns with the technology. Some believe technology will cause officers to lend themselves to racial profiling and even more broadly citizen privacy issues. What do you think of the facial recognition technology?

Racial Bias in Facial Recognition Software - Algorithmia Blog


We've all heard about racial bias in artificial intelligence via the media, whether it's found in recidivism software or object detection that mislabels African American people as Gorillas. Due to the increase in the media attention, people have grown more aware that implicit bias occurring in peopl...

No Quick Fix in Solving UK Crime Even Artificial Intelligence Would Struggle


Basic human error or a lack of understanding of how disclosure works will always remain potential stumbling blocks even if AI was made available to help alleviate the increased volume of data now being gathered to ensure a successful prosecution. A senior UK police chief revealed in a speech in Lon...

Super-charge your fraud detection techniques


Some of the most onerous risks are difficult to detect with isolated transaction monitoring systems. One system might flag a transaction, but without a complete view of an entity's relationships, the investigator could deem it innocuous. Imagine the power of having a holistic view of connections among accounts and transactions, across channels and products, spanning a network of potentially related customers. By connecting the dots, you could find hidden risks that are spread across multiple systems, fall below rule thresholds, or are only revealed in broader context. One of the most common pitfalls is relying too heavily (or even exclusively) on a single technique or model type for detecting fraud. As fraudsters get more sophisticated, it takes a combination of approaches to spot their handiwork. For example, network analysis finds patterns among linked entities – great for insurance claims fraud and anti-money laundering – but it doesn't detect all varieties of fraud and doesn't lend itself to real-time detection. A hybrid approach blends multiple analytic techniques from different disciplines (along with business rules) to provide a far more powerful and accurate fraud detection system. Unlike rules, which are easy for fraudsters to test and circumvent, machine learning adapts to changing behaviors in a population through automated model building. With every iteration, the algorithms get smarter and more accurate. With machine learning, you can encode large numbers of conditions, variables and events into models and detect things that rules and human analysts would miss. Ensembles of different machine learning models and techniques have proven to be extraordinarily accurate.