In an interview with Bloomberg News published Wednesday (Aug. 19), Li stressed that the U.S. needs to serve as a role model and demonstrate what she described as AI’s “incredible economic value.”
“If we are not showing a positive attitude and positive path toward AI, everybody loses,” said Li, the co-founder and CEO of World Labs.
The Bloomberg report noted that her warning comes amid increasing skepticism about AI in the U.S. Data from the Pew Research Center shows that half of Americans feel more worried than excited about AI’s integration into daily life.
The report also pointed out that many American communities have targeted the data centers powering the industry, citing concerns about high water and energy consumption.
By contrast, Pew found many nations in Asia have a more positive outlook on the technology, which Li said is due to those countries making AI a focus of early education.
Li, who has been dubbed the “Godmother of AI” for her foundational work on ImageNet, acknowledged that the scientific and educational communities may have failed to communicate AI’s benefits effectively.
“I take it sometimes upon myself thinking that we’ve done a bad job communicating with the public,” she said.
The Bloomberg report added that World Labs raised $1 billion in February to develop “world models” designed to help AI navigate and make decisions within three-dimensional environments. Li believes this technology will eventually revolutionize fields such as robotics, healthcare and education.
In other AI news, recent PYMNTS Intelligence research shows that stronger results and time savings are causing people to use the technology more often, while growing user skills are turning occasional AI experiments into routine habits.
“From First Prompt to Daily Habit: The Data Behind Rising Gen AI Reliance,” the July edition of the Consumer AI Benchmark Report, found between 58% and 69% of consumers already using AI use it more often now than when they first started, depending on the task.
“The pattern suggested a reinforcing cycle,” PYMNYS wrote Wednesday. “Better tools produce better results, users learn how to give those tools better instructions, and the combination makes AI useful for a wider range of activities.”
