The future workforce will be made up of both humans and intelligent things. We'll need to understand and leverage the strengths and weaknesses of human cognition and machine intelligence to command and control this new organizational form. Alexander Kott, David S. Alberts, "How Do You Command an Army of Intelligent Things?", Computer, vol.

Moore's law drove an information revolution that changed the world. But computers will need more than raw performance in the future. Because computers now act as agents for humans, new issues arise that can only be addressed if engineers coordinate with lawyers and businesspeople.

Just last month on June 22 and 23, the United Nations Public Service Forum 2017 took place in The Hague to celebrate public service delivery and to discuss how innovation is shaping the government of the future as well as how to accelerate such innovation. With the ever-increasing amount of data collected through a wide variety of sources and sensors, the potential for computers to learn from this data and take over certain tasks is increasing. Although the potential of technological innovations is often overrated in the short term, it seems that AI is treated as the "shiny new typewriter" of which we should be wary. AI is perceived to have the potential to accomplish much of the valuable work currently done by humans, specifically routine work where humans make an assessment within one second. One should avoid giving the computer too much autonomy in case it runs loose and acts outside the interest of the humans it serves, or creates its own bias in the form of discrimination.

The stunning capabilities of artificial intelligence (AI) may obscure the reality that we are only at the beginning of its evolution. It is bound to grow to be something that makes today's capabilities look quaint. The Economist makes clear that the excitement no doubt will continue to build, painting the picture of an industry segment on the rise. Big name companies, including Alphabet, Apple, Facebook, IBM and Microsoft, are deeply in the game. China is pushing hard on AI as well.

The U.S. military has unveiled plans to use artificial intelligence (A.I.) on the battlefield; however, the military admits that they are struggling to keep up with commercial A.I. firms. The great challenge for A.I. researchers in 2016 will be to figure out how to enable machines to think for themselves; to make them autonomous. With this technology, the military hopes A.I. can control everything, from cyber soldiers to the targeting systems of the F-35.(1) According to Deputy Defense secretary Robert Work, "The Department of Defense is a follower. The commercial world has already made this leap. We have to catch up with them quickly."(1)

Global competition to be the country with the most sophisticated AI will be the cause of the next world war, Musk predicts. His comment was responding to a story about Russian president Vladimir Putin predicting the country winning in artificial intelligence "will be the ruler of the world." Musk posted the warning with a photo of a poster that read "in the end, the machines will win." "I have exposure to the most cutting edge AI, and I think people should be really concerned by it," Musk said at the National Governors Association. "AI is a fundamental risk to the existence of human civilization in a way that car accidents, airplane crashes, faulty drugs or bad food were not -- they were harmful to a set of individuals within society, of course, but they were not harmful to society as a whole." According to Musk, an essential part of the solution is proactive and immediate regulatory oversight.

A proactive and dynamic response to digital identity security is now critical. Latest figures from fraud prevention organisation Cifas show there has been a sharp rise in identity fraudsters applying for loans, online retail, telecoms and insurance products. Simon Dukes, chief executive of Cifas, says: "We have seen identity fraud attempts increase year-on-year, now reaching epidemic levels, with identities being stolen at a rate of almost 500 a day." Proving your identity has always been essential, but none more so than across the digital landscape. It's not surprising that artificial intelligence (AI) and machine-learning are being rapidly developed as an aid to identity authentication.

If you've been putting off your flu shot until the season really gets going, wait no longer. Influenza viruses quietly circulate year-round in the US, but every winter they go big, triggering a seasonal epidemic of sniffles, sweats, and sore throats. And this year it's come earlier than usual, just in time for a potential peak over the holidays. Normally, infections start to increase around the beginning of January, peak in February, and then come down by the end of March. But according to data released by the Centers for Disease Control and Prevention on Friday, the flu is already widespread in 12 states, including California and New York.

Much of the software now revolutionizing the financial services industry depends on algorithms that apply artificial intelligence (AI)--and increasingly, machine learning--to automate everything from simple, rote tasks to activities requiring sophisticated judgment. These algorithms and the analyses that undergird them have become progressively more sophisticated as the pool of potentially meaningful variables within the Big Data universe continues to proliferate. When properly implemented, algorithmic and AI systems increase processing speed, reduce mistakes due to human error and minimize labor costs, all while improving customer satisfaction rates. Creditscoring algorithms, for example, not only help financial institutions optimize default and prepayment rates, but also streamline the application process, allowing for leaner staffing and an enhanced customer experience. When effective, these algorithms enable lenders to tweak approval criteria quickly and continually, responding in real time to both market conditions and customer needs. Both lenders and borrowers stand to benefit. For decades, financial services companies have used different types of algorithms to trade securities, predict financial markets, identify prospective employees and assess potential customers.

America's military budget, at $615 billion, dwarfs those of its closest competitors, China ($211 billion) and Russia ($69 billion). Even with that advantage, a new report finds that the U.S. is at risk of falling behind in the race to find and create AI for military applications. In 2014, U.S. Secretary of Defense Chuck Hagel announced that his department intended to lead the coming AI revolution with what he called the "Third Offset Strategy." For the uninitiated, the Second Offset Strategy was in response to the buildup of conventional forces along the Central European front by the Soviet Union and its satellite states ... which itself was a response to the First Offset Strategy that had the U.S. putting its own forces in the field. America didn't want to match the Soviets soldier for soldier, so new technology like long-range sensors and a new generation of guided munitions and submunitions was developed to give the U.S. an edge.