All around us people are slowly (or sometimes quickly) transitioning into the future of work. The full-time job (9 to 5, traditional career, etc.) is about to become a rarity; only available to a select group of people who represent the core of an organization, or who possess a very specific skill set. Because we live in a society increasingly shaped by tech. Automation will take over many of the tasks previously assigned to people. And the youth of today (and tomorrow) will have no problem transitioning into that situation.

'We can presume that the goal of the EAGIs is to emancipate themselves from human control while also participating in the world economy which would be the most efficient way to acquire necessary resources (using the economic means or political means or a mix of both?).' The last phrase refers to an observation made by Franz Oppenheimer in The State. Oppenheimer noted that there are only two means of acquiring the resources necessary for survival, the political means or the economic means. The political means involve the threat or use of violence and/or fraud. The economic means is peaceful, voluntary exchange.

If the machines are taking all the jobs, how come so many people are working? The unemployment rate is at 4.9 percent. There are 143.6 million Americans with payroll jobs, a record. The number of first-time unemployment claims (pdf) is down more than 10 percent from last year, and is bumping along at levels not seen since the 1970s. Oh, and the Bureau of Labor Statistics says there are 5.5 million job openings in America, close to a record.

'Organizations are pivoting towards operational analytics as it can both increase the efficiency and performance of the back office as well as boost the customer experience in the front office.' comments Anne-Laure Thieullent, Head of Big Data in Europe, for Capgemini's Insights & Data global practice. 'However, despite the focus, there are factors limiting the success of these projects; specifically siloed datasets, fragile governance models, inability to harness third party data sources, and an absence of a strong mandate from leadership teams.' 'Going Big: Why Organizations Need to Focus on Operations Analytics' from Capgemini Consulting's Digital Transformation Institute mapped organizations based on the extent to which their analytics initiatives were integrated with core operations processes and their success rate with initiatives, identifying four stages of operational analytics maturity: Capgemini Consulting's Digital Transformation Institute applied the four stages of operational analytics maturity to build up a geographic picture of adoption and success rates around the world. US companies are not only the most advanced with their analytics initiatives but also the most successful; 50 percent have successfully realized the desired benefits from operational analytics compared to only 23 percent of Chinese respondents, despite China ranking highly for level of implementation. A strong contributing factor of the success of US companies is their focus on setting up effective data and governance processes. The prominence of US organizations tallies with a recent resurgence in US manufacturing and will drive US manufacturing competitiveness in the coming years.

A small step for Google may very soon become a giant step for mankind. An artificially intelligent computer system built by Google has just beaten the world's best human, Lee Sedol of South Korea, at an ancient strategy game called Go. Go originated in Asia about 2,500 years ago and is considered many, many times more complex than chess, which fell to AI back in 1997. Google's programmers didn't explicitly teach AlphaGo – that's what the system is called - to play the game. Instead, they built a sort of model brain called a neural network that learned how to play Go by itself. As it studied a database of about 100,000 human matches, and then continued by playing against itself millions of times, it constantly reprogrammed itself and improved.

When Google's AlphaGo program beat grandmaster Lee Se-Dol four games to one, both programmers and professional Go players were surprised. The general consensus was that it would be years before a computer could defeat a human at the complex board game, which players describe as requiring elegance and imagination. Director of the MARCS Institute for Brain, Behaviour and Development and electrical engineering professor, Jon Tapson, said AlphaGo's victory was cause for a re-evaluation of how we use artificial intelligence (AI). "They could find ways of manipulating the stock market -- maybe by buying and selling shares in rapid succession to create the illusion of a change in market sentiment," he said. He said unless there was reason to go looking, it was unlikely humans would notice that kind of behaviour, and that it would be difficult to program or regulate the actions of an AI if we do not know how it makes decisions.

Jose Luis Cordeiro is a futurist thinker, the director of the Venezuelan node of the Millennium Project as well as energy advisor and part of the founding faculty of Singularity University (SU). In his speech at this year's START Summit he passionately argued that things like human-level artificial intelligence or physical immortality aren't nearly as far away in the future as most people would think, due to the power of exponential growth patterns observed in Moore's Law and other key areas, and he shared his vision of how technology will change almost every aspect of our lives, including ourselves. His conception of the future is very similar to that of his friend, the author, inventor, director of engineering at Google and co-founder of Singularity University, Ray Kurzweil. Both are radical optimists, both believe in a merger of humans and machines and both don't shy away from controversy. After Cordeiro's keynote I had the chance to do a short interview with him.

What makes the UK such a breeding ground for businesses working with Artificial Intelligence? We asked Alexandre Flamant and John Henderson, Co-founders of the LondonAI meetups, for their thoughts. Last week, a prototype programme from Google DeepMind achieved what many commentators thought would take at least another decade: it won a five match series of the ancient Chinese board game Go against reigning world champion Lee Sedol. In doing so, AlphaGo made a number of'creative' moves that flummoxed Go experts – no human would have ever played in such a way. This is true intelligence, even if currently confined to a specific board game.

Machine learning is already a very big deal. It's here, and it's in use in far more businesses than you might suspect. A few months back, I decided to take a deep dive into this topic to learn more about it. In today's post, I'll dive into a certain amount of technical detail about how it works, but I also plan to discuss its practical impact on SEO and digital marketing. For reference, check out Rand Fishkin's presentation about how we've entered into a two-algorithm world.

Almost half of U.S. jobs may one day be automated. For some employees who worked at a free on-demand concierge, that day came last month. For about a year, Sam Fox-Hartin had worked for an on-demand concierge startup called GoButler as a "Hero," the company's term for employees who field users' requests, via text message, and then complete tasks such as booking tables at restaurants, scheduling appointments, or ordering food for delivery on their behalf. Most of these tasks, like the ones I watched Fox-Hartin maneuver when GoButler invited me to visit its New York headquarters last year, were fairly routine. But he also wrote poems.