'The U.S. Department of Defense will for the first time be using large-scale artificial intelligence systems that could automate mundane tasks and augment the work of military members as a result of an $885 million five-year contract, said Josh Sullivan, senior vice president at government consulting firm Booz Allen Hamilton. The technology will allow the Defense Department to better compete with nations including China and Russia, said Mr. Sullivan, who leads the analytics business for Booz Allen. "Part of this is (about) making sure our government has the access to the best technology and using it responsibly in service of our citizens and warfighters," he said. The use of AI systems such as neural networks that mimic the human brain could help the Defense Department sift through the "overwhelming" amount of data related to such areas as national security and health care. In turn, soldiers and military members can be freed up to identify threats on the battlefield sooner, spend more time with military patients and work on problems that require higher-level contextual reasoning, Mr. Sullivan said.

Norm Judah is chief technology officer, Microsoft Services. Artificial Intelligence (AI) is already having a transformative impact across every industry. From helping employees at transportation companies predict arrival times or issues that may arise, to predicting toxins in grains of food. It's helping scientists learn how to treat cancer more effectively and farmers are figuring out how to grow more food using fewer natural resources. A 2017 study by PWC calculated global GDP will be 14 percent higher by 2030 as a result of AI adoption, contributing an additional $15.7 trillion to the global economy.

Toymaker The Crafty Robot has launched a crowdfunding campaign for its latest design -- a DIY robot that can follow you around the house and bring you drinks. Smartibot is an educational, build-it-yourself toy for adults and children who want to become more familiar with robotics. The Crafty Robot describes the toy as the world's first artificial intelligence (AI) enabled cardboard robot. The AI it contains is a real-time object-detection system, which means that the small, smiling robot can be taught to recognise people, pets or vehicles and automatically follow them. Alternatively, the kit comes with two variant models of Smartibot that operate via remote control rather than automated AI: a teabot with cupholders to deliver drinks, and a unicorn with a little cardboard horn.

A poll of British consumers conducted by software firm OpenText found that one in four Brits think robots would do a better job than humans as politicians. Years ago, The Muppet Show ran a segment mocking politicians for their stereotypical robotic behaviour. Last April a robot was nominated to run to be Tokyo's mayor, promising fair and balanced representation. In a world where reality is sometimes more bizarre than an episode of Black Mirror, what if we replaced our current politicians with algorithms? In a period where trust in politicians is low and government efficiency is questionable, might we be better off? Upgrade your inbox and get our Daily Dispatch and Editor's Picks.

Artificial intelligence (AI) has been changing our lives for decades, but today its presence is bigger than ever before. Sometimes, we don't even realize it when a new AI-powered system, tool, or product appears and outperforms us, humans. The benefits of AI and automation for HR and the workforce don't come instantly, however. It's a journey and one can see the short-term benefits of this journey in automation, the medium-term benefits in augmentation and finally the long-term benefits in the amplification of human activities or tasks. Let's take a look at the various effects of AI and automation on HR and the workforce in more detail.

As artificial intelligence is entering all spheres of our lives, a lot of concern is arising about the possible white bias and patriarchy of the impending AI world. Research shows women are much more skeptical of and averse to innovation in comparison to men who embrace and triumph it. This fear of technological innovation has to do with the fact that society often views the role of women as replaceable by AI, which is visible in the abundance of women robots and female personal assistants, such as Alexa and Cortana. If we're coming to the point when most jobs are automated and robots become everyday reality in our lives, we'd better make sure those algorithms are beneficial for most people, be it an Afro-American woman or a Chinese man. As of today, 85% of the machine learning workforce is male.

In 2013, an algorithm determined Eric Loomis' six-year prison sentence in Wisconsin for attempting to flee a traffic officer and operating a motor vehicle without the owner's consent. No one knew how the software, Correctional Offender Management Profiling for Alternative Sanctions, or COMPAS, worked--not even the judge who delivered the sentence. Analyses conducted by ProPublica later found the predictive artificial intelligence used in this case, which attempts to gauge the likelihood of an offender committing another crime, to be racially biased: A two-year study involving 10,000 defendants found that the A.I. routinely overestimated the likelihood of recidivism among black defendants and underestimated it among whites. The U.S. Supreme Court declined to review Eric Loomis' case, so the sentence stands. Increasingly, A.I. has the power to alter the course of people's lives.

Though nearly a third of American adults still report experiencing fear of flying, the majority of us implicitly trust that airlines will get us from point A to point B and back again in one piece. Indeed, few factors are as crucial in the transportation industry as trust. If we didn't believe in the safety of a train, plane or automobile, no one would ever travel that way. Planes, however, still have pilots, and trains usually have conductors, and most likely will for the near future. Interestingly, the introduction of autopilot in commercial aviation – effectively rendering pilot control for large parts of the flight unnecessary – did not seem to bother most passengers, (similar to modern conductor-less locomotive systems).

With increasing institutional use of Al and machine learning methods, more and more industry regulators are making use of such software to provide financial stability through services and systemic risk surveillance. Central to the UK Financial Conduct Authority's (FCA) agenda is their intent to develop "both their technology side – cloud analytics – as well as building out our human side – our data science capability" to allow an "osmotic" expansion across the wider organisation, "effectively enabling us to leverage machine learning," says head of regtech and advanced analytics at FCA, Nick Cook. Investigations of suspicious transactions are highly time-consuming, and often, due to overly-defensive mechanisms, fall victim of unsuccessful outcomes. Through the identification of intricate patterns, machine learning would flag up serious, rather than harmless transactions, and, consequently require the attention of supervisors. For instance, with the aid of Al and machine learning, the Monetary Authority of Singapore (MAS) examines suspicious transactions that require further analysis and attention, which, in turn, enables supervisors to spend their time and resources on higher risk transactions.

If you manage operations or IT in manufacturing, transportation, energy, mining, or other industrial sectors, you've undoubtedly heard a lot about AI, how quickly the technology is evolving, and how it's going to transform how business gets done. Indeed, with the exponential growth of data generated by IoT sensors and applications, there are unprecedented opportunities for AI to leverage this data to generate critical insights, drive automation, and increase efficiency. PricewaterhouseCoopers predicts AI will boost global GDP by 14 percent by 2030, with increased labor productivity accounting for more than half of these gains. But what does AI really mean for leaders, managers, and engineers out in the field? Have you started to implement AI projects, or is AI on your company's roadmap?