The legal profession is being challenged now as never before to embrace new technologies to transform the way they deliver legal services. And the impetus is coming from clients, particular general counsel of large multinationals, who in this new digital age are simply refusing to countenance paying for 30 associates to do a job they now know full well an intelligent piece of software can do in their place. Gone are the days of junior litigators barricading themselves in a war room for days, sifting through boxes and boxes of evidence; or trainee conveyancers sweating 100s of hours reviewing a 300-page lease. Today, clients expect this work to be despatched in hours or minutes with the aid of artificial intelligence tools, leaving the humans to focus on the real value-adds: deciding on litigation strategy and tactics; or handling a sensitive lease negotiation. Law firms are now required to become adept in separating out the different strands of the service they provide to clients and working out which bits are still best delivered by (wo)man and which by machine.

Robert Jones was driving home through the pretty town of Todmorden, in West Yorkshire, when he noticed the fuel light flashing on the dashboard of his car. He had just a few miles to find a petrol station, which was cutting things rather fine, but thankfully his GPS seemed to have found a short cut – sending him on a narrow winding path up the side of the valley. Robert followed the machine's instructions, but as he drove, the road got steeper and narrower. After a couple of miles, it turned into a dirt track, but Robert wasn't fazed. After all, he thought, he had "no reason not to trust the satnav".

A few years ago I had written an article about how technology is literally obliterating jobs and how to skill yourself up for this new economy. In this article I want to provide you with a renewed peek into what I believe is the road to success, should you want to be part of the artificial intelligence economy - which some are equating to the revolution nearly 120 years ago with electricity. But first, let's take a look at what digital disruption or the increased pervasiveness of new technology is doing to the job market. Last year, AP (Associated Press) ran a 3-part big story on "Technology and permanent job destruction," very real and a very chilling narrative of what is happening in the job market right now. We have never witnessed at jobless economic recovery ever!

Today's artificial intelligence systems, including the artificial neural networks broadly inspired by the neurons and connections of the nervous system, perform wonderfully at tasks with known constraints. They also tend to require a lot of computational power and vast quantities of training data. That all serves to make them great at playing chess or Go, at detecting if there's a car in an image, at differentiating between depictions of cats and dogs. "But they are rather pathetic at composing music or writing short stories," said Konrad Kording, a computational neuroscientist at the University of Pennsylvania. "They have great trouble reasoning meaningfully in the world." To overcome those limitations, some research groups are turning back to the brain for fresh ideas.

China will be the world's dominant player in artificial intelligence by 2030. A State Council document, issued in July last year, resolved to position China as the world's pre-eminent practitioner of artificial intelligence (AI) in both research and application within the next 12 years. Governments across the world are rushing to support innovation in AI, but none has published as coherent a plan as China and – more importantly – has the ability to get things done: the Chinese government can implement policy in ways that are impossible in western democracies. Intent, however, is one thing: to paraphrase the boxer Mike Tyson, everyone has a plan until they get punched in the mouth. The Chinese not only have a strategy, they have a track record of delivering on large-scale, ambitious projects.

Last month, a team of self-taught AI gamers lost spectacularly against human professionals in a highly-anticipated galactic melee. Taking place as part of the International Dota 2 Championships in Vancouver, Canada, the game showed that in broader strategic thinking and collaboration, humans still remain on top. The AI was a series of algorithms developed by the Elon Musk-backed non-profit OpenAI. Collectively dubbed the OpenAI Five, the algorithms use reinforcement learning to teach themselves how to play the game--and collaborate with each other--from scratch. Unlike chess or Go, the fast-paced multi-player Dota 2 video game is considered much harder for computers.

The consulting specialists and innovation drivers CAMELOT Management Consultants today announced the start of the "Global Community for Artificial Intelligence in Supply Chain Management". With immediate effect, CAMELOT is offering supply chain management and AI masterminds from research and practice an open platform for the targeted transfer of knowledge. The initiative gives companies the opportunity to collaborate in implementing the first flagship projects using artificial intelligence in supply chain management (SCM). Members of the community will benefit from the latest innovations and research outcomes, motivational speeches, use cases and how-to guides for artificial intelligence in supply chain management. The focus here is on AI applications in logistics.

Artificial intelligence can significantly improve the diagnosis of lung disease, suggests a new study. Artificial intelligence (AI) can improve the diagnosis of lung disease by helping doctors interpret respiratory symptoms more accurately, according to new research. An AI computer algorithm using high quality data proved more consistent and accurate in interpreting respiratory test results and suggesting diagnoses than lung specialists, revealed recent research presented at the European Respiratory Society International Congress in Paris, France. "Pulmonary function tests provide an extensive series of numerical outputs and their patterns can be hard for the human eye to perceive and recognise; however, it is easy for computers to manage large quantities of data like these and so we thought AI could be useful for pulmonologists," said Dr Marko Topalovic, a postdoctoral researcher at the Laboratory for Respiratory Diseases, Catholic University of Leuven, Belgium. The study included 120 pulmonologists from 16 hospitals and researchers used historical data from 1,430 patients from 33 Belgian hospitals.

Medical imaging creates tremendous amounts of data: many emergency room radiologists must examine as many as 200 cases each day, and some medical studies contain up to 3,000 images. Each patient's image collection can contain 250GB of data, ultimately creating collections across organizations that are petabytes in size. Within IBM Research, we see potential in applying AI to help radiologists sift through this information, including imaging analysis from breast, liver, and lung exams. IBM researchers are applying deep learning to discover ways to overcome some of the technical challenges that AI can face when analyzing X-rays and other medical images. Their latest findings will be presented at the 21st International Conference on Medical Image Computing & Computer Assisted Intervention in Granada, Spain, from September 16 to 20.

These are perhaps the most powerful and important four words a woman can hear after a breast-screening visit. X-ray based mammography is an effective screening tool for detecting cancer, but what many women may not know is that breast screening programs produce a high level of false positive results, particularly after multiple years of screening. In other words, women are informed they may have cancer when in fact they don't. This is particularly true in the U.S., where each study is generally read by a single, expert radiologist. In Europe, two independent radiologists read each study.