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Until appropriate safeguards are in place, we need a moratorium on biometric technology that identifies individuals, says Kate Crawford. Until appropriate safeguards are in place, we need a moratorium on biometric technology that identifies individuals, says Kate Crawford. “These tools are harmful when they fail and dangerous when they work.”

From Quito to Nairobi, Moscow to Detroit, hundreds of municipalities have installed cameras equipped with FRT, sometimes promising to feed data to central command centres as part of 'safe city' or 'smart city' solutions to crime. [...]Lee Tien, a senior staff attorney at the Electronic Frontier Foundation in San Francisco, California, says that one of the main reasons large technology firms - whether in China or elsewhere - get involved in supplying AI surveillance technology to governments is that they expect to collect a mass of data that could improve their algorithms. The Russian capital rolled out a city-wide video surveillance system in January, using software supplied by Moscow-based technology firm NtechLab. In May, the chief executive of London's Heathrow airport said it would trial thermal scanners with facial-recognition cameras to identify potential virus carriers.

•A simple approach to use the hand vein pattern as a tool for identification is introduced.•A standardised grid system consisting of six lines and four sectors is applied on the dorsum of the hands.•This approach can be a simple and non-costly tool for the analysis of hand vein patterns. In a case of child pornography, only the dorsum of the offender's hand was clearly visible. After identification of a suspect, the question arose of whether and how it is possible to identify or exclude the suspect as perpetrator according to the morphology of the hand vein pattern. A simple approach to use the hand vein pattern in crime suspects as a tool for identification was tested. In this study, the hand vein patterns of 30 study participants were analysed from conventional frames on videography. A standardised grid system consisting of six lines and four sectors was applied on the dorsum of the hands. Vein branchings within the sectors and line crossings of the veins were counted, leading to a total of 11 variables for each hand. A positive identification of each of the 30 test participants was possible for each hand when taking only the first five variables into account. A random overlapping prediction was obtained by statistically simulating hand vein patterns of different numbers of persons using this sample. Considering the hand vein frequencies in this sample, the results indicate that the chance for two persons having the same pattern is smaller than 1:1000. It can be concluded that the introduced grid system approach can be an appropriate simple and non-costly tool for the analysis of the pattern of hand veins for identification purposes.

Collusion-resistant fingerprinting paradigm seems to be a practical solution to the piracy problem as it allows media owners to detect any unauthorized copy and trace it back to the dishonest users. Despite the billionaire losses in the music industry, most of the collusion-resistant fingerprinting systems are devoted to digital images and very few to audio signals. In this paper, state-of-the-art collusion-resistant fingerprinting ideas are extended to audio signals and the corresponding parameters and operation conditions are proposed. Moreover, in order to carry out fingerprint detection using just a fraction of the pirate audio clip, block-based embedding and its corresponding detector is proposed. Extensive simulations show the robustness of the proposed system against average collusion attack. Moreover, by using an efficient Fast Fourier Transform core and standard computer machines it is shown that the proposed system is suitable for real-world scenarios.