Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable Selects Look Up Say More Safety Net Versus Creator Playbook In My Bag Trending Now Back to School Good Connection: Uplifting stories for a digital age Switch Off All Series Gallup surveyed people in 37 countries about their relationship with AI. Chance Townsend is the General Assignments Editor at Mashable, covering tech, video games, dating apps, digital culture, and whatever else comes his way. He has a Master's in Journalism from the University of North Texas and is a proud orange cat father. His writing has also appeared in PC Mag and . People around the world are largely optimistic about artificial intelligence, according to a new Gallup poll.

There is a whole lot of talk nowadays about power, who has it, who wants it, who should have it. What you do not hear a lot about is what exactly power is and where it really comes from. We believe that everybody in a free and capitalistic democracy should have it -- and we believe that one of the surest sources of it is knowledge. Those who possess crucial information and the knowhow to put that information to use effectively will be heads and shoulders above those who do not -- and not because they are better or more deserving but simply because they have that knowledge. The fact is that knowledge is and always has been the ultimate equalizer or advantage if you had it and others did not, and the ultimate granter of access to all that you could be. It's why monks slaved by candlelight to find and preserve the words of wisdom from the Greek and Roman empires almost lost forever during the Dark Ages by rewriting every word by hand. It's why the invention of the printing press, radio and TV and, ultimately, the internet on which you are reading this article changed the world. Conversely, it's the reason why for centuries those who wanted to keep people down and out of power have tried to keep knowledge out of the hands of those they wanted to oppress. In the United States, for instance, during the era of slavery, slave codes actually made it illegal to teach slaves to read or write. And in current day Afghanistan, women are not even allowed to go to school.

Companies plan to spend big money on AI -- as much as $77.6 billion by the year 2022 according to some estimates, with a compound annual growth rate (CAGR) of a whopping 37.3%. That spending is an investment that can be expected to pay rich dividends in the future. AI is a competitive advantage and leaders would be wise to ensure their companies are AI-ready. But how will the rapid rise of AI change what's expected of leaders -- today and in the future? According to It's the Manager, of all the traits of successful leadership Gallup has studied, most can be "distilled down to two elements" -- bringing multiple teams together and great decision-making.

Artificial intelligence (AI), robots, automation, deep-learning machines -- these and similar technologies already have replaced human workers across a number of industries, including retail, financial, manufacturing, transportation, and construction. Not surprisingly, this has prompted concerns about machines taking jobs from people as enterprises seek to increase operational efficiency, lower costs, and reduce their dependence on humans, unreliable and unpredictable as we are. And we haven't even started talking about disengaged! The truth is that most enterprise employees are just punching a clock, literally or metaphorically. "The majority of employees (51%) are not engaged and haven't been for quite some time," Gallup concludes. "These employees are indifferent and neither like nor dislike their job.

The fast-moving field of artificial intelligence development is a lucrative one -- a head-spinning one -- an oft-surprising and exciting one. But peer past the frenzy of media headlines announcing the latest discoveries and newest breakthroughs and it's sad but true, the world of science, including technology, is a field dominated by godless leftists, too. Look at this headline, from a New Yorker piece in September of 2015: "All Scientists Should be Militant Atheists." That was by cosmologist Lawrence Krauss, who also served as the director of the Origins Project at Arizona State University, an endeavor aimed at exploring the universe, humanity and technology. Krauss saw his career suffer a bit of a hit in 2018, on the heels of accusations by women of sexual harassment -- accusations which he has strenuously denied, by the way.

AI is a problem for jobs, say the majority of Americans, but it's someone else's problem. Nearly three-quarters (73 percent) of US adults believe artificial intelligence will "eliminate more jobs than it creates," according to a Gallup survey. But, the same survey found that less than a quarter (23 percent) of people were "worried" or "very worried" automation would affect them personally. Notably, these figures vary depending on education. For respondents with only a four-year college degree or less, 28 percent were worried about AI taking their job; for people with at least a bachelor degree, that figure was 15 percent.

Listen to much of the well-peddled advice in the enterprise tech world today, and you'd have to be excused for coming away with the belief that "big data" holds all the answers your company is looking for. Too bad it often can't live up to that promise -- at least, not in its traditional form. Turns out, what's commonly referred to as big data -- all those vast "lakes" of numerical measures captured by the enterprise resource planning (ERP), consumer relationship management (CRM) and other business systems so enthusiastically mined by today's analytics tools -- actually amounts to only 10 percent of the data an average company has at its fingertips, according to IDC. The rest is "unstructured" or "qualitative" data, and it can be messy. Included in this type is information from customer surveys, response forms, online forums, social media, documents, videos, news reports, phone calls to call centers and anecdotal evidence gathered by the sales team, to name just a few examples.

Five years ago, a team of researchers from Google announced a remarkable achievement in one of the world's top scientific journals, Nature. Without needing the results of a single medical check-up, they were nevertheless able to track the spread of influenza across the US. What's more, they could do it more quickly than the Centers for Disease Control and Prevention (CDC). Google's tracking had only a day's delay, compared with the week or more it took for the CDC to assemble a picture based on reports from doctors' surgeries. Google was faster because it was tracking the outbreak by finding a correlation between what people searched for online and whether they had flu symptoms. Not only was "Google Flu Trends" quick, accurate and cheap, it was theory-free. Google's engineers didn't bother to develop a hypothesis about what search terms – "flu symptoms" or "pharmacies near me" – might be correlated with the spread of the disease itself.

Wisconsin Gov. Scott Walker may be surging as an early favorite for the Republican presidential nomination -- but the numbers show the person leading among potential Iowa caucus-goers often doesn't win. In the Democratic field, Hillary Clinton is the most dominant position ever for a non-incumbent, with odds of clinching the nomination as high as 91 percent. Over at the 538 site launched by statistician Nate Silver, the race is already on to handicap the 2016 presidential contest, a reminder that the season of campaigning, polls, predictions and surveys is descending upon us. Which makes it a perfect time to think about statistics. Even this soon in the game, we'll start to see polling from all sides of the political spectrum, making us ponder which results are valid and which might be biased.

We connect measures of public opinion measured from polls with sentiment measured from text. We analyze several surveys on consumer confidence and political opinion over the 2008 to 2009 period, and find they correlate to sentiment word frequencies in contempora- neous Twitter messages. While our results vary across datasets, in several cases the correlations are as high as 80%, and capture important large-scale trends. The re- sults highlight the potential of text streams as a substi- tute and supplement for traditional polling. consumer confidence and political opinion, and can also pre- dict future movements in the polls. We find that temporal smoothing is a critically important issue to support a suc- cessful model.