Most major railway stations in India will use facial recognition to fight crime by the end of 2020, a senior official said, in a move that digital rights campaigners on Tuesday warned could breach people's privacy in the absence of stringent laws. The system is being trialled in the tech hub of Bengaluru where about half a million faces are scanned every day and - using artificial intelligence (AI) - matched against faces stored in a police database of criminals. "The railways will become like a virtual fortress," a senior railways official told the Thomson Reuters Foundation. "Without a physical, brick and mortar boundary wall, we will be able to make the whole system more secure," said the official who declined to be named as he was not authorised to speak to the media. Stretching from the foothills of the Himalayas to sandy southern beaches, India's railway network is one of the biggest in the world, carrying about 23 million people - or the population of Taiwan - every day.

A former employee of Google has warned of the web giant's'disturbing' plans for a search engine in China which could help Beijing monitor its citizens online. Jack Poulson wrote in a letter to the US Senate's commerce committee that the proposed Dragonfly website was'tailored to the censorship and surveillance demands of the Chinese government'. In his letter he also claimed that discussion of the plans among Google employees had been'increasingly stifled'. Mr Poulson was a senior research scientist at Google until he resigned last month in protest at the Dragonfly proposals. A former employee of Google has warned of the web giant's'disturbing' plans for a search engine in China which could help Beijing monitor its citizens online While China is home to the world's largest number of internet users, a 2015 report by US think tank Freedom House found that the country had the most restrictive online use policies of 65 nations it studied, ranking below Iran and Syria.

"Existing patterns of structural discrimination may be reproduced and aggravated in situations that are particular to these technologies – for example, machine learning system goals that create self-fulfilling markers of success and reinforce patterns of inequality, or issues arising from using non-representative or "biased" datasets.

The two Islamic State jihadis scrambled up to the roof of the building, breaking cover for a moment before quickly hiding from sight. But it was too late. They had been spotted by the camera drone hovering above Mosul's Old City, their images beamed to black-clad special forces operatives huddled around a tablet roughly 300 yards away. Lt. Col. Muhannad Tamimi, a battalion commander, turned to his walkie-talkie. "Staff Col. Arkan," he said.