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The Center for Evidence-Based Management (CEBMa) is a non-profit member organization dedicated to promoting evidence-based practice in the field of management. We provide support and resources to managers, consultants, organizations, teachers, academics and others interested in learning more about evidence-based management.

Microsoft Professional Program in AI, the latest learning track open to the public. The program provides job-ready skills and real-world experience to engineers and others who are looking to improve their skills in AI and data science through a series of online courses that feature hands-on labs and expert instructors.

"Augmented reality might not be able to cure cancer (yet), but when combined with a machine learning algorithm, it can help doctors diagnose the disease."

"To help space travelers recover from the kinds of mishaps that can occur in the reaches of deep space-mishaps that can end missions and potentially end lives-Lockheed Martin is combining machine learning and artificial intelligence with augmented and virtual reality interfaces to provide a bit more self-reliance to manned space exploration missions at distances at which it could take more than 40 minutes to get a reply from mission control."

"A primer to blockchain and distributed ledger technologies. Learn how to start building blockchain applications with Hyperledger frameworks."

AI is (currently) very good at specialist/single tasks that require brute force computational effort or training algorithms, but we are a long way from developing generalised AI, that requires some form of unsupervised deep learning. There are many things that humans understand but are well beyond the reach of AI, and this will remain the case for many years to come - if it ever happens.

"The ability for machines to see, understand and interact with the world is growing at a tremendous rate and is only increasing with the volume of data that helps them learn and understand even faster. Big data is the fuel that powers AI."

"Morgan Stanley is about to augment its 16,000 financial advisers with machine-learning algorithms that suggest trades, take over routine tasks and send reminders when your birthday is near."

Hidden biases may be written inadvertently into the algorithms used to decide who gets a job interview or who qualifies for a loan or for parole. If a data set considers the word "programmer" closer to the word "man" than "woman," or if you build a system that learns from Wikipedia, where only 17 per cent of profiles of notable people are women, these biases will be perpetuated in the machine.

"It is somewhat safe to predict that AI will continue to be at the top of the hype cycle in 2018. But the following 51 predictions also envision it becoming more practical and useful, automating some jobs and augmenting many others, combining machine learning and big data for fresh insights, with chatbots proliferating in the enterprise."

Free online courses

Stop swearing at Siri. Quit cursing Cortana. As digital devices grow smarter, being beastly toward bots could cost you your job.

The government needs to get the ethical framework and regulation of artificial intelligence right and invest in skills training if it wants to make the most of the technology, the Government Office for Science has said.

Google answers these questions with the help from deep neural networks, a form of artificial intelligence rapidly remaking not just Google's search engine but the entire company and, well, the other giants of the internet, from Facebook to Microsoft.

We can stay in command of AI for as long as we control resources and value exchange in the future. However there is probably some minor chance that a self-improving AI will figure out how to wrest that control from us ... at some time in the future.

Today we face an entirely new environment for innovation and getting things done. The days of the lone genius quietly toiling away in pursuit of that 'Eureka' moment to revolutionise an industry are all but over. We are now in the days of asking and listening to our customers and working with them in our innovation cycles. Innovation demands collaboration. So does production. In the past we could focus on a single task in an assembly-line fashion, handing our completed activity to the next person who would in turn do the same, until the job was finished. Now the jobs change fast, requiring learning new skills rather than merely repeating the old. We have to seek out people who have other pieces of the puzzle and work with them to tackle increasingly complex issues at a much faster pace.

Cisco is high-tech company, yet uses really simple techniques to prototype end-user experiences. By simple, they mean string, Blu-tac, pins etc. The example of drawing out what the 'new-hire' experince should be like is very revealing innovative (see 9mins 47secs to 11:00mins)