Up to now, any robots brushing with the law were always running strictly according to their code. Fatal accidents and serious injuries usually only happened through human misadventure or improper use of safety systems and barriers. We’ve yet to truly test how our laws will cope with the arrival of more sophisticated automation technology — but that day isn’t very far away.

"Will these developments enable people to attain higher living standards, better working conditions, greater economic security, and improved health and longevity? The answers to these questions are not predetermined. They depend upon the institutions, investments, and policies that we deploy to harness the opportunities and confront the challenges posed by this new era," the report said. The warning signals keep flashing. In the past week alone, the Federal Reserve Bank of San Francisco, issued a report saying that automation has "contributed substantially" to reducing the portion of national income that goes to US workers over the past two decades, Bloomberg News reported. Technological efficiencies will result in an estimated 200,000 job cuts in the US banking industry in the next decade, according to a Wells Fargo & Co. report, Bloomberg also reported.

NEXT week, a meeting at UN headquarters in Geneva will discuss autonomous armed robots. Unlike existing military drones, which are controlled remotely, these new machines would identify and attack targets without human intervention. Groups including the Campaign to Stop Killer Robots hope the meeting will lead to an international ban. But while fiction is littered with cautionary tales of what happens when you put guns in the cold, metallic hands of a machine, the situation may not be as simple as "human good, robots bad". To understand why, we should look at what people are saying about the ethics of driverless cars, which advocates see as a way of reducing accidents.

On January 25, 1979, 25-year-old Robert Williams climbed into a storage rack to retrieve parts from a malfunctioning robot at Ford's Flat Rock plant in Michigan. The robot, not able to sense Williams' presence, swung round and struck him on the head, killing him instantly. The robot kept working for 30 minutes as Williams lay dead on the floor. His death, nearly forty years ago, makes Williams the first person to be killed as a result of actions by a robot. In August 1983, his family was awarded $10 million after a jury ruled against Unit Handling, the company that designed the one-ton machine.

New research from DeepMind, Alphabet Inc.'s London-based artificial intelligence unit could ultimately shed light on this fundamental question. They have been investigating the conditions in which reward-optimizing beings, whether human or robot, would chose to cooperate, rather than compete. The answer could have implications for how computer intelligence may eventually be deployed to manage complex systems such as an economy, city traffic flows, or environmental policy. Joel Leibo, the lead author of a paper DeepMind published online Thursday, said in an email that his team's research indicates that whether agents learn to cooperate or compete depends strongly on the environment in which they operate. While the research has no immediate real-world application, it would help DeepMind design artificial intelligence agents that can work together in environments with imperfect information.

Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs. But while AI and machine learning are very much related, they are not quite the same thing. Google's Digital Justice League: how its Jigsaw projects are hunting down online trolls AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.

Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs. But while AI and machine learning are very much related, they are not quite the same thing. AI'lawyer' correctly predicts outcomes of human rights trials AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.

Picture a self-driving car that sees a pedestrian in the road and has to swerve to avoid them. Now imagine there are cyclists on both sides of the car – and only the one on the right is wearing a helmet. Should the car veer right, to avoid killing the unprotected rider, even if that means punishing safer cycling? "At least since Socrates we've been worrying about moral philosophy and how to describe what's right and what's wrong," he says. "Now suddenly we've got to programme this into artificial systems and it's like, damn, we haven't got very far."

Fueling this intuition was not merely that Mika imitated life but that she claimed responsibility. If I have a right, then someone else has a responsibility to respect that right. I in turn have a responsibility to respect the rights of others. Responsibility in this sense is a very human notion. We wouldn't say of a driverless car that it possesses a responsibility to keep its passengers safe, only that it is designed to do so.