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AI adoption calls for balanced thinking

AI adoption calls for balanced thinking - ai adoption
AI adoption calls for balanced thinking

Howard Gardner, the psychologist known for his theory of multiple intelligences, now says artificial intelligence will soon make many cognitive skills unnecessary for humans. In a recent discussion, he explained that AI could perform tasks like disciplined reasoning, synthesis, and creativity so well that people may no longer need to develop those abilities unless they want to.

From multiple intelligences to artificial ones

Gardner introduced his theory in 1983, broadening the idea of intelligence beyond a single IQ score. At the time, he didn’t consider how machines might compare to human thinking. By 2024, he and his colleagues released an essay titled “Who Owns Intelligence?”, exploring the connections between human, animal, plant, and artificial intelligence.

His interest in AI started unexpectedly through work with Anthea Roberts, a visiting professor at Harvard Law School. Roberts showed Gardner how AI could quickly synthesize large amounts of information. His research group then used AI to analyze lengthy interviews with college students and alumni—a process that once required hours but now took minutes.

Gardner reflected on how seeing AI complete in moments what takes humans hours made him think about its impact on education.

What becomes optional—and what doesn’t

In his 2007 book Five Minds for the Future, Gardner outlined five key cognitive abilities: the disciplined mind, the synthesizing mind, the creative mind, the respectful mind, and the ethical mind. Now, he believes AI will soon handle the first three so effectively that developing them may no longer be essential for most people.

In Five Minds for the Future, he called for cultivating those three forms of cognition but now believes AI will handle them so well that pursuing them will become optional for humans. Of course, anyone who wants to master a discipline, or to synthesize or create, has his complete respect and admiration. The last two abilities—respect and ethics—remain uniquely human, he noted. Even where AI excels, people might still engage in cognitive work for enjoyment, personal growth, or to produce something machines can’t. “Perhaps poetry or stories no AI could write,” he added. “But that will only happen if people are motivated to push their own limits.”

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A Harvard publication quoted Gardner as saying that by 2050, due to advances in AI, students won’t need more than a few years of schooling in “reading, ’riting, ’rithmetic, and a little bit of coding.”

Some educators oppose the idea that AI could replace human teaching. Gardner, however, believes well-designed AI will eventually surpass even the best teachers in certain areas. “Education should continue,” he said, “but not by keeping young people in classrooms for years to study the same topics in the same way.”

A future of choice, not necessity

Gardner’s vision isn’t about removing human effort but making it voluntary. If AI can handle cognitive work more efficiently, people might spend less time on tasks they dislike and more on activities they enjoy—whether cooking, studying history, or inventing something new.

“Speed and efficiency won’t matter,” he said. “We’ll use our minds because it brings us joy and benefits others.”

He recognizes this future depends on personal motivation. Without it, people might default to passive consumption rather than active creation. The challenge, then, extends beyond technology—it’s cultural. Once students master basics around age 10, Gardner envisions a system where they explore their interests with AI as a tool. “They should be free to pursue their own interests with the help of AI, peers, and appropriate coaches,” he said. The aim isn’t to abandon education but to make it more adaptable and driven by curiosity rather than obligation.

The timeline for this shift remains unclear. Gardner’s argument raises a key point: if machines can do the work, what will people choose to do instead?

education higher education innovation learning technology technology
Rosalyn Merrifield

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