I have been studying the whole range of issues/opportunities in the commercial roll out of robotics for many years now, and I've spoken at a number of conferences about the best way for us to look at regulating robotics. In the process I've found that my guidelines most closely match the EPSRC Principles of Robotics, although I provide additional focus on potential solutions. And I'm calling it the 5 Laws of Robotics because it's so hard to avoid Asimov's Laws of Robotics in the public perception of what needs to be done. The first most obvious point about these "5 Laws of Robotics" should be that I'm not suggesting actual laws, and neither actually was Asimov with his famous 3 Laws (technically 4 of them). Asimov proposed something that was hardwired or hardcoded into the existence of robots, and of course that didn't work perfectly, which gave him the material for his books.

Artificial Intelligence (AI) and robots often seem like fun science fiction, but in fact already affect our daily lives. For example, services like Google and Amazon help us find what we want by using AI. Every aspect of how Facebook works is based on AI and Machine Learning (ML). The reason your phone is so useful is it is full of AI -- sensing, acting, and learning about you. All these tools not only make us smarter, their intelligence is based partly on what they learn both from us and about us when we use them.

RICHARD DAWKINS: When we come to artificial intelligence and the possibility of their becoming conscious, we reach a profound philosophical difficulty. I am a philosophical naturalist; I'm committed to the view that there is nothing in our brains that violates the laws of physics, there's nothing that could not, in principle, be reproduced in technology. It hasn't been done yet; we're probably quite a long way away from it, but I see no reason why in the future we shouldn't reach the point where a human-made robot is capable of consciousness and of feeling pain. JOANNA BRYSON: So, one of the things that we did last year, which was pretty cool, the headlines, because we were replicating some psychology stuff about implicit bias--actually, the best one is something like'Scientists show that AI is sexist and racist and it's our fault,' which, that's pretty accurate because it really is about picking things up from our society. Anyway, the point was, so here is an AI system that is so humanlike that it's picked up our prejudices and whatever and it's just vectors.

Exceptional times require exceptional solutions. Due to the current lockdown, the IEAI has decided to hold its May Speaker Series with Prof. Dr. Joanna Bryson virtually via Zoom. With its Speaker Series, the TUM Institute for Ethics in Artificial Intelligence is inviting experts from all over the world to talk about ethics and governance of AI. These events serve as an important platform for sharing new research and exchanging knowledge. The May session of the TUM IEAI Speaker Series will take place on 14 May 2020, 10am (CEST), virtually via Zoom.

Just a week after it was announced, Google's new AI ethics board is already in trouble. The board, founded to guide "responsible development of AI" at Google, would have had eight members and met four times over the course of 2019 to consider concerns about Google's AI program. Those concerns include how AI can enable authoritarian states, how AI algorithms produce disparate outcomes, whether to work on military applications of AI, and more. Of the eight people listed in Google's initial announcement, one (privacy researcher Alessandro Acquisti) has announced on Twitter that he won't serve, and two others are the subject of petitions calling for their removal -- Kay Coles James, president of the conservative Heritage Foundation think tank, and Dyan Gibbens, CEO of drone company Trumbull Unmanned. Thousands of Google employees have signed onto the petition calling for James's removal.

Make sure you're following these industry leaders on Twitter. The world of AI and robotics is evolving all the time, with job opportunities and new products springing up constantly. It's never been a better time for someone interested in building a career in AI. While the jobs, companies and skills may vary, the wider industry trends are always worth keeping an eye on if you're serious about an AI career. One of the best ways to keep yourself immersed in the AI world is by following the leaders, experts and influencers in the field.

Future AI may be super powerful but, as Dr. Joanna Bryson of the University of Bath relates, that still won't make it a person. The desire to bestow human life on inanimate material has been a component of our collective imagination since at least the days of Ovid. In his work Metamorphoses he relates the tale of Pygmalion, who sculpted Galatea out of ivory and besought her animation at the hands of Aphrodite. Two thousand years later, we still see that narrative trope playing itself out in stories such as Alex Garland's Oscar-winning film Ex Machina, where an AI developer creates an autonomous female android named Ava as the key component of a Turing Test. From marriage to murder, the finales of these and other similar stories range from wish fulfillment to cautionary tale, but the psychological underpinnings remain the same: the aspiration to take something intrinsically non-human (such as ivory or silicon) and humanize it.

Joanna Bryson (@j2bryson) is an Associate Professor in the Department of Computing at the University of Bath. She works on Artificial Intelligence, ethics, and collaborative cognition. In 2010 Bryson published her most controversial work, "Robots Should Be Slaves" and has helped the EPSRC to define the Principles of Robotics in 2010. She has also consulted The Red Cross on autonomous weapons and is a member of an All Party Parliamentary Group on Artificial Intelligence. Joanna is focused on "Standardizing Ethical Design for Artificial Intelligence and Autonomous Systems".

PONG is a gloriously simple video game: you control one paddle, aiming to bounce the ball past your opponent's paddle. Artificial intelligence has learned to play it so well that it can easily beat human players. But try to get the same AI to play Breakout, a very similar paddle-based game, and it is utterly stumped. It can't reuse what it has learned about paddles and balls from Pong, and has to learn to play from scratch. Computers can learn without our guidance, but the knowledge they acquire is meaningless beyond the problem they are set.