"Jeopardy!" host Ken Jennings tells Fox News Digital he wants to know a human is behind any creative projects, not AI. "I'm deeply skeptical of AI," Jennings told Fox News Digital at the TCM Classic Film Festival. "Obviously, these current iterations of LLMs [Large Language Models] would clean Watson's clock at'Jeopardy!' The technology has moved on. I've played with chatbots and'Jeopardy!' clues, and they're very hard to stump," he said.

"The only thing to be worried about is if you're making music to chase an algorithm," he told Fox News Digital. "If you're making music to trend on TikTok. And to do that, you have to really unlock the codes to that matrix. If that's your whole [hustle], then AI is going to do a better job than that." The Black Eyed Peas singer does think people not involved in the creative process in the music industry are the ones who should worry about AI taking away their jobs.

"Will AI take over jobs?" is a very controversial and interesting question that has been around for many years, and yet it will be questioned even more in the upcoming years, as artificial intelligence rapidly develops. Some people believe that AI will create more jobs than it destroys. They argue that as AI automates certain tasks, it will free up workers to do other, more creative or complex tasks. For instance, a bank teller whose job is automated by AI may be able to use their freed-up time to provide financial planning services to customers. Similarly, a manufacturing worker whose job is taken over by a robot may be able to move into maintenance or quality control. Others believe that AI will destroy more jobs than it creates.

There’s no doubt that digital technology has been highly disruptive. In industry after industry, from retail to media to travel and hospitality, nimble digital upstarts have set established industries on their head, completely changing the basis upon which firms compete. Many incumbents haven’t survived. Many others are greatly diminished. Still, in many ways, the digital revolution has been a huge disappointment. Besides the meager productivity gains, we’ve seen a ​​global rise in authoritarian populism, stagnant wages, reduced productivity growth and weaker competitive markets, not to mention an anxiety epidemic, increased obesity and, at least in the US, decreased life expectancy. We can—and must—do better. We can learn from the mistakes we made during the digital revolution and shift our mindset from disrupting markets to tackling grand challenges. This new era of innovation will give us the ability to shape the world around us like never before, at a molecular level and achieve incredible things. Yet we can’t just leave our destiny to the whims of market and technological forces. We must actually choose the outcomes we prefer and build strategies to achieve them. The possibilities that we will unlock from new computing architectures, synthetic biology, advanced materials science, artificial intelligence and other things will give us that power. What we do with it is up to us.

As AI improves and becomes more powerful, its impact on the world economy will become vastly more significant. It will affect virtually every aspect of the world economy -- from unemployment rates to economic growth, productivity, income inequality and more. Some argue that so far, AI has not had a large enough impact, but as its development accelerates, its effects will grow exponentially. Whether we like it or not, automation and job displacement are already here, slowly pushing the human workforce into different domains. Similar patterns can be found throughout history; new technology made certain products and jobs obsolete, and eventually humans were forced to switch to more innovative products and new jobs.

A lot of the conversation about the future of AI and automation focuses on the AGI endgame ("will humans still work when artificial general intelligence can do everything?"). But there are more interesting, tractable, and concrete questions to answer about the effects of "narrow," task-specific AI that looks more or less like what we have today. In the near future, we can expect more advanced robotics, autonomous cars, customer service chatbots, and other applications powered by such narrow AI to take over certain tasks from humans. Should we be optimistic about labor in the next 10-50 years, when parts of industries will be automated by narrow AI? What early signs of those trends should we be concerned about now?

No matter whether you have adopted machine learning technologies and in the grander picture, artificial intelligence, most engineers recognize that a change is coming. It would seem a natural fit to incorporate artificial intelligence into CAD, into our workflows, into our engineering. This not only facilitates our forward growth as engineers, but it gives us the ability to design with complexities never before possible. Remaining at the top of our engineering game is no easy task when the game is constantly innovating with new technologies. To remain relevant as engineers, we must understand – even predict – how machine learning and AI will change the game and adapt before we are left in the dust. AI is the next platform.

With the rise of self-driving technologies, there is great speculation as to how this new world of autonomous transportation will impact the economy and society. Critics claim that industries will suffer, millions of people will lose their jobs, and society will overall be worse off. Optimists predict that along with new technologies will come new industries and new jobs, and with the benefits of self-driving cars, there will be a ripple of benefits into other aspects of life. Before exploring these different possibilities of what the future may be, let's take a journey to the past. Here we find civilizations at war, and one of the earliest forms of transportation: the chariot.

While it's likely AI will create new jobs, its more immediate (and lasting) potential is in helping advance the science that underlies new industries. If you were a brilliant artificial intelligence (AI) expert just graduating from a doctoral program at a prestigious school, would you pursue that startup you've been thinking about, join a company that wants to build cutting-edge AI applications, or use your expertise to help scientists in other fields conduct basic research? Admittedly, this is a bit of a silly question. The opportunities presented by the first two options are outrageous, and growing more outrageous by the day. With more than 2,000 startups absorbing much of the top-tier AI talent -- estimated by some to be just 10,000 individuals worldwide -- the combination of great scarcity and even greater demand for talent is driving salaries through industry roofs.

UK Prime Minister Theresa May has announced plans to invest in a "whole new industry around AI in healthcare". Researchers at the University of Southern California have developed a new predictive model for heart disease, which makes use of a smartphone app. Machine-learning techniques are poised to hit the mainstream over the next few years. Machine learning has long been touted as the next big thing for healthcare. With countless startups investing in that promise, applications are emerging across everything from diagnostics to drug discovery.