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'The Great Inversion': Why one innovation theorist says technology is no longer adapting to us — we're adapting to it

Innovation theorist John Nosta, founder of NostaLab, warns that AI represents a shift he calls 'The Great Inversion,' where technology no longer adapts to humans but instead changes how people think, learn, and solve problems. Nosta says AI's cognitive impact differs from past physical innovations, echoing research from Oxford University Press and the Work AI Institute that generative AI can reduce depth of learning and create an illusion of expertise. He advocates using AI as a partner through 'iterative intelligence' rather than accepting answers without engagement.

read3 min views1 publishedJul 25, 2026
'The Great Inversion': Why one innovation theorist says technology is no longer adapting to us — we're adapting to it
Image: Businessinsider (auto-discovered)

Humans have long built technologies to change the world around them — faster cars, better tools, and more efficient machines.

AI may be among the first widely adopted technologies that not only shapes the world around us but also increasingly influences how we think, learn, and solve problems.

That's according to John Nosta, an innovation theorist and founder of the think tank NostaLab, who called the shift "The Great Inversion."

"Progress seems to be increasingly about making humans better for the technological world we've created," Nosta told Business Insider.

'The organism is the project' #

Historically, many innovations have helped people overcome physical constraints, he said. Humans invented the wheel to make it easier to move heavy loads, and the car dramatically expanded how far and fast people could travel, for example.

Nosta says that AI is different because its primary impact is often cognitive rather than physical. Instead of simply changing people's environment, he says, AI increasingly changes how they approach thinking, reasoning, and decision-making.

"We're now into the cognitive age, where what's changing is the nature of thought," he said. "The path from A to B is getting shorter and shorter, and we are deferring cognition to the machine."

His view echoes a growing body of research suggesting that AI can influence how people learn, remember information, and make decisions.

Researchers at Oxford University Press warned last year that generative AI can make students faster and more fluent while quietly reducing the depth of learning that comes from pausing, questioning, and working through problems independently.

Meanwhile, a report from the Work AI Institute found that AI often creates an illusion of expertise, making users feel more capable even as some underlying skills begin to erode.

For Nosta, AI is one example of a broader trend. He points to GLP-1 drugs such as Ozempic, which were originally developed to treat diabetes but are now widely used for weight loss and are being studied for their potential to reduce cravings for alcohol, nicotine, and compulsive behaviors. Rather than redesigning environments to better suit people, some new innovations modify human behavior to help people function within existing environments, he said. "The organism is the project."

That shift, he said, carries important implications for human cognition.

Using AI as a partner, not a replacement #

Still, Nosta doesn't believe AI is inherently harmful.

He distinguishes between what he calls "iterative intelligence," where people use AI to deepen their understanding through conversation, and "cognitive surrender," where they simply accept AI-generated answers without engaging in the thinking process.

Vivienne Ming, chief scientist at the Possibility Institute, raised a similar point to Business Insider in March, saying her research found most AI users rely on the technology to think less, while a minority use it to think better.

Instead, she said users should use it as a collaborator, exploring ideas, challenging assumptions, and pushing the problem forward, in what she described as "productive friction" — the process by which learning and skills form.

Nosta described a similar approach he called "iterative intelligence."

"The ability to engage with technology, with large language models, is an extraordinary opportunity for humanity to advance itself," he said.

But for that to happen, he said, people need to resist what he called the "myth" that AI's greatest value is speed and instead use it as a thinking partner, even if that means spending more time wrestling with ideas.

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