National Crime Records Bureau (NCRB) under the Government of India has released a tender asking for bidders to help create Automated Facial Recognition System (AFRS). The objective is to leverage the power of facial recognition technology to make the security forces more efficient. The technology system which has been proposed will make an extensive database of photos belonging to Indian citizens using which machine learning models will be trained. The criminals will be identified using CCTV footage from the database, verified, and information will be distributed to all law enforcement agencies in real-time across the country. Experts have touted that using facial recognition technology to identify and solve crime may be one of the best applications of the technology.
American law enforcement agencies have created a massive facial recognition database. If you're an adult in the US, you might already be in it. According to a comprehensive report by the Center for Privacy & Technology at Georgetown Law, the law enforcement's database has 117 million American adults on file. The report says authorities used driver's license IDs from 26 states to build the database, which includes people who've never committed any kind of crime before. That's already a problem in and of itself, but it's compounded by the lack of oversight on how it's used.
The FBI maintains a huge database of more than 411m photos culled from sources including driver's licenses, passport applications and visa applications, which it cross-references with photos of criminal suspects using largely untested and questionably accurate facial recognition software. A study from the Government Accountability Office (GAO) released on Wednesday for the first time revealed the extent of the program, which had been queried several years before through a Freedom of Information Act request from the Electronic Frontier Foundation (EFF). The GAO, a watchdog office internal to the US federal government, found that the FBI did not appropriately disclose the database's impact on public privacy until it audited the bureau in May. The office recommended that the attorney general determine why the FBI did not obey the disclosure requirements, and that it conduct accuracy tests to determine whether the software is correctly cross-referencing driver's licenses and passport photos with images of criminal suspects. The Department of Justice "disagreed" with three of the GAO's six recommendations, according to the office, which affirmed their validity.
A company that operates facial recognition systems in China has exposed the personal information of 2.5 million people after leaving a database unprotected. Facial recognition system showing a blue interface with a human head and biometrics data, with a grid of relevant points connected to facial features: used for survellaince, privacy control and identity tracking (Big Brother).Getty A company that operates facial recognition systems in China has exposed the personal information of 2.5 million people after leaving a database unprotected, it has emerged. It was discovered by Dutch cybersecurity researcher Victor Gevers, who works for the GDI Foundation, a non-profit dedicated to reporting security issues. He tweeted: "There is this company in China named SenseNets. They make artificial intelligence-based security software systems for face recognition, crowd analysis, and personal verification. And their business IP and millions of records of people tracking data is fully accessible to anyone."
India has just 144 police officers for every 100,000 citizens, compared to 318 per 100,000 citizens in the European Union. In recent years, authorities have turned to facial recognition technology to make up for the shortfall. New Delhi's law enforcement agencies adopted the technology in 2018, and it's also being used to police large events and fight crime in a handful of other states, including Andhra Pradesh and Punjab. But India's government now has a much more ambitious plan. It wants to construct one of the world's largest facial recognition systems.