Artificial intelligence is not as advanced as you may think. Sure, it's technologically advanced, but it lacks a general understanding of what's socially acceptable to say, the real world and the way humans interact. In the last couple of months, Microsoft has had a couple of failed attempts with artificial intelligence. The first involved an image recognition app called Fetch!, which looks at photos of dogs to identify its breed. People, of course, started to use the app to determine what breed of dog people resemble.

The following is an edited, updated version of an article originally written for IEEE Spectrum. I'm 62, with all that entails. I still play a mean game of hockey, but entropy looms ever larger. So part of me wants very much to believe that we are rapidly approaching "The Singularity." Like heaven, the Singularity comes in many versions, but most involve bionic brain boosting.

New lip-reading technology developed at the University of East Anglia could help in solving crimes and provide communication assistance for people with hearing and speech impairments. The visual speech recognition technology, created by Helen L. Bear, PhD, and Prof Richard Harvey of UEA's School of Computing Sciences, can be applied "any place where the audio isn't good enough to determine what people are saying," Bear said. Those include criminal investigations, entertainment, and especially where are there are high levels of noise, such as in cars or aircraft cockpits, she said. Bear said unique problems with determining speech arise when sound isn't available -- such as on video footage -- or if the audio is inadequate and there aren't clues to give the context of a conversation. The sounds '/p/,' '/b/,' and '/m/' all look similar on the lips, but now the machine lip-reading classification technology can differentiate between the sounds for a more accurate translation.

Computing models based on the human brain have immense geopolitical possibilities. Enter your email address below to receive this article directly to your inbox. We will never sell or share your information. Your email address is stored on an encrypted and secure server. Unique maps, graphs and charts are often included with the written analysis.

In many ways, our current inability to replicate our own brains is not a particularly large concern. For driverless cars, for example, the aim is to create a system that combines pure logical processes with ethical judgements and a protective mentality. Google's self-driving car project proved this in February, when one of its vehicles was responsible for causing a low-speed crash. The error was a typically human one -- assuming that a bus would slow and let it pull out past some sand bags -- and Google's response is to teach the system through deep learning processes that certain vehicles will be less likely to slow down for it.

We know by (9 years of) experience that, the most important thing to do before releasing a chatbot is to plan a strategy to make sure you communicate the content domain properly, so that you can set the expectations right. Since perception is everything, nothing else matters. Remember the success of the YO! app?

Sometimes, the field of artificial intelligence looks pretty ridiculous, like when Microsoft's teen chatbot was tricked by online trolls to say racist and sexist things. Consider how it's affecting our working world. Jen-Hsun Huang, the CEO of computer graphics hardware company Nvidia, can see this clearly. For a long time, gamers have loved Nvidia for the company's graphics processors (GPUs) that have the ability to gorgeously render insanely violent games. Here's the twist: Nvidia's GPUs also happen to be excellent for deep learning, an AI technique that allows algorithms to recognize patterns and become more adept at finding them over time.

Long before we kneel to our robot overlords, AI tools will help schedule meetings and perform research for busy business professionals. Sustaining a positive work-life balance has become increasingly more challenging in today's technology-driven business environment. Automation technology thrives in environments traditionally considered laborious and time consuming – time better spent on tasks that make money, instead of wasting it. Time spent manually entering tasks, calendar items, and typing up emails on smartphones, in particular for those of you, like myself, blessed with sausage fingers, quickly became more hassle than it was worth. This process became especially irritating for business pros that are constantly on the move and rely, almost exclusively, on the features and functionality of their smart devices.

Humans are nothing if not contrary. Technology destroying jobs is something most Americans accept will happen within their lifetimes, according to a new study by the Pew Research Center, just not to their own jobs -- which most believe won't change significantly in the next 50 years. Polling just over 2,000 Americans in June and July last summer to ask about their perception of the risk of jobs being automated, the researchers found a majority (65 per cent) of Americans believe that robots and/or software will "definitely" or "probably" be capable of doing much of the work that humans do now within 50 years' time. But when the robots and the algorithms move a little closer to home – and the question becomes specifically about the future security of their own jobs -- respondents' views are very different, with an even larger majority (80 per cent) convinced their own jobs and professions will remain largely unchanged and will exist in their current form 50 years from now. More than a third (36 per cent) of respondents expressed definitive confidence that their current job or occupation will "definitely" exist in its current form five decades from now vs just six per cent saying their current role will "definitely not" exist.

The Science and Technology Committee is undertaking an inquiry into robotics and artificial intelligence. Robotics and Autonomous Systems (RAS) is one of the'Eight Great Technologies' identified by the UK Government in 2012. A national strategy for RAS innovation from a'RAS Special Interest Group' was published by Innovate UK in 2014. The Government responded to that strategy in March 2015 (PDF 405 KB) and agreed to establish a RAS Leadership Council to oversee its execution. The Special Interest Group also published The UK Landscape for Robotics and Autonomous Systems in 2015.