Google has fired one of its top artificial intelligence researchers, Margaret Mitchell, escalating internal turmoil at the company following the departure of Timnit Gebru, another leading figure on Google's AI ethics team. Mitchell, who announced her firing on Twitter, did not immediately respond to requests for comment. In a statement to Reuters, Google said the firing followed a weeks-long investigation that found she moved electronic files outside the company. Google said Mitchell violated the company's code of conduct and security policies. Google's ethics in artificial intelligence research unit has been under scrutiny since December's dismissal of Gebru, a prominent Black researcher in Silicon Valley.

The US should not agree to ban the use or development of autonomous weapons powered by artificial intelligence (AI) software, a government-appointed panel has said in a draft report for Congress. The panel, led by former Google chief executive Eric Schmidt, on Tuesday concluded two days of public discussion about how the world's biggest military power should consider AI for national security and technological advancement. Its vice-chairman, Robert Work, a former deputy secretary of defense, said autonomous weapons are expected to make fewer mistakes than humans do in battle, leading to reduced casualties or skirmishes caused by target misidentification. "It is a moral imperative to at least pursue this hypothesis," he said. For about eight years, a coalition of non-governmental organisations has pushed for a treaty banning "killer robots", saying human control is necessary to judge attacks' proportionality and assign blame for war crimes.

Five years ago, the world of artificial intelligence--and the algorithms it runs on--looked very different. Asking your Google Home to play Adele's chart-topping single wasn't possible yet. IBM Watson was still widely considered a beacon for AI advancement, and DeepMind's AI victory over a human at Go was still fresh. Machine learning engineers were facing earlier versions of today's image classification and speech recognition challenges. And though most tech giants hadn't earmarked corporate funding for ethical AI, the conversation was becoming more mainstream as the impact of algorithms on human lives became clearer.