Elon Musk, recently busying himself with calling people "pedo" on Twitter and potentially violating US securities law with what was perhaps just a joke about weed – both perfectly normal activities – is now involved in a move to terrify us all. The non-profit he backs, OpenAI, has developed an AI system so good it had me quaking in my trainers when it was fed an article of mine and wrote an extension of it that was a perfect act of journalistic ventriloquism. As my colleague Alex Hern wrote yesterday: "The system [GPT2] is pushing the boundaries of what was thought possible, both in terms of the quality of the output, and the wide variety of potential uses." GPT2 is so efficient that the full research is not being released publicly yet because of the risk of misuse. And that's the thing – this AI has the potential to absolutely devastate.

William Fry's focus on AI in the workplace discovers the potential for artificial intelligence to help solve some of Ireland's current employment law issues. Artificial intelligence or AI is defined by the Oxford English Dictionary as "the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perceptions, speech recognition, decision-making, and translation between languages". The term is defined in popular culture, and in the eyes of employees the world over as an ever-approaching threat. The World Economic Forum has discussed AI as a major element of the fourth industrial revolution (4IR) and something that will rapidly change our world and workplaces. Regardless of the definition, AI is coming into our workplaces and coming quickly.

Of primary importance in formulating a response to the increasing prevalence and power of artificial intelligence (AI) applications in society are questions of ontology. Questions such as: What "are" these systems? How are they to be regarded? How does an algorithm come to be regarded as an agent? We discuss three factors which hinder discussion and obscure attempts to form a clear ontology of AI: (1) the various and evolving definitions of AI, (2) the tendency for pre-existing technologies to be assimilated and regarded as "normal," and (3) the tendency of human beings to anthropomorphize. This list is not intended as exhaustive, nor is it seen to preclude entirely a clear ontology, however, these challenges are a necessary set of topics for consideration. Each of these factors is seen to present a 'moving target' for discussion, which poses a challenge for both technical specialists and non-practitioners of AI systems development (e.g., philosophers and theologians) to speak meaningfully given that the corpus of AI structures and capabilities evolves at a rapid pace. Finally, we present avenues for moving forward, including opportunities for collaborative synthesis for scholars in philosophy and science.

My ten year old daughter recently told me that she does not expect to get a driver's license. Upon asking her why, she explained that when she is old enough to drive, she expects all cars to be self-driving. She further elaborated that she should need to be even more vigilant in a self-driving car, because, in her words – "I always know what I am thinking, but who knows what those cars are thinking!" As AI and ML permeate more businesses and become part of daily life, natural human fears are being expressed in various ways, from individual to corporate concerns to government regulations. News stories appear daily, detailing AI mistakes that led to corporate losses or embarrassment [2,3,4,7].

This blog post discusses how the General Data Protection Regulation (GDPR), if properly enforced, can support organisations deploying artificial intelligence (AI) with the appropriate governance. As digital ethics and privacy become increasingly intertwined, it is crucial to ensure we set clear guidelines about what businesses can and cannot do with people's data. Technology is changing our day to day lives and we should embrace this development. When it comes to AI, the issue is not innovation, or the pace of technological improvement. The real problem is its governance, the ethics underpinning it, the boundaries we give it and, within that, the roles for defining the solution to these problems.

It's not quite the question one expected during the Q&A session at the end of the 2019 BCS Turing Talk on Artificial Intelligence. The event was held earlier this week at the swanky IET building in London's Savoy Place and the audience comprised academics, developers and tech professionals. You'd think such an interjection was akin to someone grabbing the microphone in the main auditorium during a cryptocurrency conference and blurting "So… there aren't any actual coins?" Surely this was a cue for the auditorium to resound with an unpleasant cacophony of forehead-slapping and eye-rolling. And let me tell you, the ugly wet sound of hundreds of people rolling their eyes at the same time is the stuff of Japanese body horror nightmares.

"We are not talking about Terminator. We're talking about much simpler technologies, which are at best a few years away, and in fact, many of which you can see under development today in every theater of the war." He spoke February 14th as part of discussion called Killer Robots: Technological, Legal and Ethical Challenges at a meeting of the American Association for the Advancement of Science. "And so these are systems that are using sensors and software processing on their own to determine what constitutes a target and then applying lethal force to that, without supervision or meaningful human control." Another speaker, Peter Asaro, co-founder of the International Committee for Robot Arms Control, has participated in U.N. talks on autonomous weapons.

If you shop at Westfield, you've probably been scanned and recorded by dozens of hidden cameras built into the centres' digital advertising billboards. The semi-camouflaged cameras can determine not only your age and gender but your mood, cueing up tailored advertisements within seconds, thanks to facial detection technology. Westfield's Smartscreen network was developed by the French software firm Quividi back in 2015. Their discreet cameras capture blurry images of shoppers and apply statistical analysis to identify audience demographics. And once the billboards have your attention they hit record, sharing your reaction with advertisers.

Every once in a while, I'll open something up that hasn't seen the light of day for a while. It always yields discoveries, forgotten memories and much more. Sometimes I'll open something up because it needs to be cleaned or fixed, as was the case recently with my father's 1955 Seeberg jukebox, long sitting idle in the basement. As with anything that is aging and has moving parts, it needed some care, my father long having left this life and his jukebox behind. A rare quiet hour with a piece of your childhood can reveal much.

The future of AI encompasses many risks and challenges. The public perception of the future of AI can be a challenge as many fear artificial intelligence might take away their job, which may be true as AI is a tool people can use to operate business more efficiently. Other risks to the future of AI include data privacy concerns, government laws and regulations, and company stakeholders not understand the technology.