College students Tabatha Fajardo, Jay Ram and Kyra Varnavas give their take on the development of AI in the classroom on'The Story.' Artificial intelligence experts have advised consumers to use caution and trust their instincts when encountering "hallucinations" from artificial intelligence chatbots. "The number-one piece is common sense," Kayle Gishen, chief technology officer of Florida-based tech company NeonFlux, told Fox News Digital. People should verify what they see, read or find on platforms such as ChatGPT through "established sources of information," he said. AI is prone to making mistakes -- "hallucinations" in tech terminology -- just like human sources. The word "hallucinations" refers to AI outputs "that are coherent but factually incorrect or nonsensical," said Alexander Hollingsworth of Oyova, an app developer and marketing agency in Florida.

Editor's note: This is part of a KSL.com series looking at the rise of artificial intelligence technology tools such as ChatGPT, the opportunities and risks they pose and what impacts they could have on various aspects of our daily lives. In the 1992 movie "Wayne's World," the character Garth is working on a robotic arm when Benjamin comes to ask him about making a change to his show. "We fear change," Garth says. He then looks down at the mechanical hand and begins to repeatedly smash it with a hammer. Many Americans have a similar reaction to change and technology, especially when it comes to using artificial intelligence in health care.

Many scientists and researchers still rely on Excel spreadsheets and lab notebooks to manage data from their experiments. That can work for single experiments, but companies tend to make decisions based on data from multiple experiments, some of which may take place at different labs, with slightly different parameters, and even in different countries. The situation often requires scientists to leave the lab bench to spend time gathering and merging data from various experiments. Teams of scientists may also struggle to know what the others have tried and which avenues of research still hold promise. Now the startup Uncountable has developed a digital workbook to help scientists get more from experimental data.

The odds are high, according to recent economic analyses. Indeed, fully 47 percent of all U.S. jobs will be automated "in a decade or two," as the tech-employment scholars Carl Frey and Michael Osborne have predicted. That's because artificial intelligence and robotics are becoming so good that nearly any routine task could soon be automated. Robots and AI are already whisking products around Amazon's huge shipping centers, diagnosing lung cancer more accurately than humans and writing sports stories for newspapers. Last year in Pittsburgh, Uber put its first-ever self-driving cars into its fleet: Order an Uber and the one that rolls up might have no human hands on the wheel at all. Meanwhile, Uber's "Otto" program is installing AI in 16-wheeler trucks--a trend that could eventually replace most or all 1.7 million drivers, an enormous employment category.

Long before the public learned that the Large Hadron Collider had unearthed the Higgs boson, physicists like Matt Hollingsworth knew it was coming. They had seen hints in the data: First, a small, statistically dubious bump where the subatomic particle--the one that explains why everything in the universe has mass--should be. Then, the bump began to grow. Every day, some employees would religiously check an internal website that charted the growth of the signal, the probability that it was real. Before breaking out the champagne, they needed to reach three-sigma--or 99.7 percent certainty.