• The article warns that the phenomenon of “cognitive offloading” – outsourcing thinking to tools like AI – is becoming widespread and could erode core thinking capabilities.
  • When given a choice between thinking for themselves or using AI, humans often choose AI, even when they are fully capable of solving the problem themselves.
  • Research shows that people who rely heavily on offloading tools have lower scores on analytical thinking tests.
  • Researcher Sam Gilbert discovered “reminder bias”: humans use digital reminders even when their personal memory is sufficient.
  • The cause is metacognitive: humans underestimate their own abilities, leading to a habit of avoiding mental effort.
  • This habit tends to be persistent over time; capabilities that are not practiced early may not fully develop.
  • Nathaniel Barr pointed out a link between smartphone reliance and lower scores on the Cognitive Reflection Test.
  • AI reduces almost all “friction” in finding answers, causing the brain to increasingly choose shortcuts.
  • The argument that “there is no need to remember because it can be looked up” is countered: knowledge is the foundation of thinking, not just data that can be called upon.
  • True expertise requires information to be available in working memory, not just knowing where to find it.
  • Smart people face a paradox: they leverage AI best but also risk losing the training process that created that intelligence.
  • The output results may be the same, but the missed cognitive development only reveals itself when encountering problems AI cannot solve.

📌 The phenomenon of “cognitive offloading” – outsourcing thinking to tools like AI – is becoming widespread and could erode core thinking capabilities. When given a choice between thinking for themselves or using AI, humans often choose AI, even when they are fully capable of solving the problem themselves. The cause is metacognitive: humans underestimate their own abilities, leading to a habit of avoiding mental effort. Smart people face a paradox: they leverage AI best but also risk losing the training process that created that intelligence.

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