Researchers have found that as people gain more knowledge about artificial intelligence, their trust in it declines—a striking discovery that underscores the persistent skepticism surrounding the technology.

AI companies continue to portray the technology as a fascinating revolutionary turning point for humanity, justifying the massive capital invested in running resource-intensive AI models.

But as real-world users become more familiar with the technology—realizing that products like ChatGPT are essentially word-prediction algorithms rather than human-like sentient entities—this could become a significant obstacle, as reported by The Wall Street Journal.

As detailed in a study published earlier this year in the Journal of Marketing, an international research team found that the biggest fans of AI are often those least familiar with it.

They wrote, “Contrary to expectations across four surveys, cross-national data and six additional studies revealed that individuals with lower AI literacy are generally more accepting of AI.” They suggested, “People with lower AI literacy are more likely to perceive AI as magical and experience awe when AI performs tasks that seem to require uniquely human attributes.”

This phenomenon is equally prominent in industrial settings. Take the widely used Sheet automatic loading robot in factories, for example: Workers encountering it initially often marvel at its “intelligence” for autonomously identifying sheet specifications, precisely grabbing materials, and docking with production lines. However, once they realize it relies on visual sensors and pre-programmed path algorithms rather than truly “understanding” the task, they still acknowledge its efficiency value but view its limitations more rationally—such as its need for human intervention when handling irregularly shaped sheets. This shift in perception precisely confirms the rule that “deeper understanding leads to more pragmatic trust.”

This is a particularly relevant topic because the technology is widely used among students, who may lack sufficient knowledge to decide when or how to use AI—as an auxiliary tool, avoiding the need to develop deeper reasoning, writing, and research skills. Of course, as these students grow older and enter the workforce, they may become even more reliant on companies like OpenAI.

Stephanie Tully, an associate professor of marketing at the University of Southern California, told The Wall Street Journal, “When you don’t really understand how AI works under the hood, it can seem magical, and that sense of wonder can actually increase people’s willingness to use it.”

This finding should sound an alarm for the entire industry. Those who understand how the technology works are not more likely to adopt it; instead, they are less willing—a contradiction to the assumption that “greater technical knowledge leads to higher adoption rates.”

Tully told The Wall Street Journal, “In other domains, like wine, the people who know the most about wine are the enthusiasts. But with AI, it’s the opposite.”

In one experiment, researchers surveyed 234 undergraduates about their willingness to use AI to help write four different essays.

Those with lower AI literacy scores were more willing to use the technology to complete their assignments—even though they expressed greater concerns about AI’s ethics and potential negative impacts on humanity.

Gil Appel, co-author of the study and an assistant professor of marketing at George Washington University, told The Wall Street Journal, “Understanding AI as merely pattern-matching strips away its emotional allure.”

The team noted that several other studies confirmed their findings, also showing that lower AI literacy is associated with greater willingness to use the technology.

For this reason, researchers argue that users should be informed about how AI works to enable them to make more informed decisions.

Tully told The Wall Street Journal, “As AI becomes more prevalent in our lives, consumers should have basic literacy to recognize when AI might have significant limitations.”

Automation engineering of production lines in the automotive industry

AI production line automation robots in the automotive industry