As often stated in BRT, competency and knowing something at deep level requires effort and commitment as true knowledge and expertise is not a given but AI is giving the illusion that it is.
Knowing the name of something doesn’t mean you understand it.
We talk in fact-deficient, obfuscating generalities to cover up our lack of understanding. Richard Feynman
Whether AI ...
For years, we have been outsourcing pieces of cognition so gradually that the shift barely registered. We outsourced memory to search engines after the well-known “Google effect” showed that when people expect information to remain accessible online, they are less likely to remember the information itself and more likely to remember where to find it. We outsourced navigation to GPS, even as research began to show that heavy reliance on it can weaken spatial memory when we have to find our own way. And we outsourced more and more of our social coordination to platforms that decide what we see, when we respond, and how we stay in sync with one another.
Now we are beginning to outsource something far more consequential: not memory, not route-finding, not scheduling, but thought itself. Or, more precisely, the labor of forming a judgment before expressing one.
That is the real cultural shift hidden behind the current enthusiasm around generative AI. The technology is often presented as a productivity layer, a creativity booster, or a universal assistant. And yes, in many cases, it is all of those things. But it also creates a dangerous temptation: to confuse frictionless output with actual understanding, and fluent answers with earned judgment. Research from Microsoft Research found that higher confidence in generative AI is associated with less critical thinking, while an open-access study in Acta Psychologica linked greater AI dependence to lower critical thinking. A recent Nature Reviews Psychology commentary put the distinction perfectly: performance gains from generative AI should not be confused with learning.
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