Research suggests offloading mental work to AI is like debt: an immediate payoff with long-term consequences. But collaborating with the technology may boost our work without eroding skills.
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Thinking is hard. It’s no wonder we lean on technology to lighten the load. We use calculators instead of doing long division by hand, GPS or Google Maps for navigation, and search engines instead of countless trips to the library. Yet just a few decades ago, getting around meant unfolding paper maps, and looking up a word required leafing through a hefty dictionary. Cognitive offloading of mental tasks to tools makes us more efficient. What’s the harm?
Then along came ChatGPT, Claude, and Gemini. Unlike earlier digital tools, AI chatbots can tackle an astonishing range of tasks and are easy to use. At a prompt, AI generates essays, analyzes medical images, writes software, and floods our feeds with AI slop. It’s cognitive offloading to the max.
Now people are asking: Is AI dulling our minds?
Yes and no, according to a new paper written by an international team of psychologists. AI can accelerate learning by giving people immediate guidance and feedback. But take the tool away, and those who rely on it often perform worse than people who learned the material on their own. Similarly, using AI to summarize information, rather than researching and organizing it yourself, often leads to shallower understanding.
But it’s not all bad news. Core cognitive abilities—including attention, reasoning, and working memory—seem to be “stubbornly resistant” to manipulation, the team wrote.
As technology evolves, so does the way we gain knowledge and think for ourselves. AI may reshape not just what we learn, but how we learn to learn. And like any other tool, its impact comes down to how we use it. Completely relying on AI is likely detrimental. But as a collaborator that challenges ideas or fills knowledge gaps, it can boost performance even after the tool is taken away.
“There is clearly a risk that AI can make us ‘stupid’ by compromising our skills (and knowledge) if we completely offload them to AI,” wrote the team. “[But] AI may be less likely to diminish the foundational cognitive capacities that underpin our ability to be smart, rather than ‘stupid’, in the first place.”
The AI Crutch
It’s easy to rely on large language models (LLMs)—the algorithms behind chatbots—for help. Why read an assigned novel when AI can summarize it in seconds? Gmail has already drafted an email reply; all I need to do is click send. That pesky essay? A few prompts and voila, done.
It seems like an easy hack, but there’s a cost to handing over too much thinking.
Researchers have long studied the consequences of cognitive offloading, or using external tools to reduce mental effort. Writing down a shopping list and keeping appointments in a calendar free up working memory, the brain’s temporary mental workspace, and allow us to focus on more important tasks without having to remember every detail.
AI is different. Beyond memory, it can offload critical thinking itself.
An MIT preprint introduced the idea of “cognitive debt” to describe the tradeoff. Participants wrote essays either with ChatGPT, using only a search engine, or with just their brains. Researchers monitored their brain activity during the task. Those using AI showed the weakest brain connectivity, which suggests they were less engaged. They also struggled to remember their own writing and felt the completed essay didn’t reflect their own ideas. When asked to write again without AI, they produced weaker work according to human judges.
Like financial debt, cognitive debt offers an immediate payoff with long-term consequences. Outsourcing mental effort makes writing faster and easier, but it slashes opportunities to build knowledge, strengthen reasoning, and practice critical thinking.
“While LLMs offer immediate convenience, our findings highlight potential cognitive costs,” wrote the MIT team.
Other studies have found the same pattern. High school students learning a new mathematical concept solved practice questions better with AI help, but they struggled on a later test when left to think on their own. Using AI “impeded the students’ learning by preventing them from engaging in the practice needed to acquire the skill,” wrote the team.
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Habitual reliance on AI may even erode already-acquired expertise. In a large study of over 1,400 patients undergoing colonoscopy screening, doctors used an AI system to help detect abnormal growths. Three months later, when the AI was unavailable, their detection rate dropped from 28.4 to 22.4 percent.
“Continuous exposure to AI…[suggests] a negative effect on endoscopist behavior,” wrote the European team.
These effects extend beyond individual skills. AI can also influence how we build knowledge in the first place.
A recent study asked participants to learn about gardening by either Googling and synthesizing the knowledge themselves or by asking ChatGPT for a summary. They were then asked to give advice to someone else without technological help. Answers from those who relied on ChatGPT were rated as generic and less helpful, suggesting a shallower understanding of the topic.
With Great Power
We’re only beginning to understand how AI reshapes the mind. And it’s not all doom and gloom. The crux is how we use it.
In the MIT essay-writing study, for example, people who initially wrote on their own but later gained access to ChatGPT produced work with higher creativity and stronger arguments, while retaining their original perspectives and voice. Likewise, high school students who used AI as a tutor—asking for hints rather than answers—performed well even after the chatbot was taken away.
Used thoughtfully, AI may also enhance collaborative learning and brainstorming or serve as a writing coach, helping people work less and learn more.
Far less is known about if, and how, AI impacts fundamental cognitive capabilities. Attention, reasoning, and working memory have proven remarkably resilient over decades of cognitive research. Becoming better at a task usually reflects learning to use these mental resources more efficiently, not expanding the brain's processing power. While AI may erode a specific skill, it could spare this core cognitive architecture, wrote the authors.
Whether that remains true over decades of AI use or during early childhood—when the brain is rapidly developing—is an open question.
Plenty other unknowns remain. Will we eventually adapt to AI, just as we’ve embraced calculators, search engines, and smartphones? Can refresher training ward off skill decay, or will some tasks simply become obsolete? How can we encourage people to strategically offload and benefit from AI use? And perhaps more philosophically: As we increasingly share our thinking with machines, will our definition of thinking evolve?
Dr. Shelly Xuelai Fan is a neuroscientist-turned-science-writer. She's fascinated with research about the brain, AI, longevity, biotech, and especially their intersection. As a digital nomad, she enjoys exploring new cultures, local foods, and the great outdoors.
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What we’re reading
Facts Only
* AI can accelerate learning by providing immediate guidance and feedback.
* Reliance on AI may lead to poorer performance when the tool is removed, compared to self-learned material.
* Using AI to summarize information, instead of personal research and organization, often results in shallower understanding.
* Core cognitive abilities such as attention, reasoning, and working memory appear resistant to manipulation.
* Participants using AI for essay writing produced weaker work when asked to write again without the AI.
* Students who used AI for practice questions struggled on subsequent tests when left to think independently.
* Doctors using an AI system for colonoscopy screening showed a drop in detection rates when the system was unavailable.
* Participants learning about gardening via ChatGPT produced answers rated as generic and less helpful.
* When participants initially wrote essays themselves but later gained access to ChatGPT, they produced work with higher creativity and stronger arguments.
* Users of AI for tutoring, who asked for hints instead of answers, performed well after the chatbot was removed.
Executive Summary
Full Take
The narrative surrounding AI and cognition centers on a trade-off between immediate convenience and long-term intellectual scaffolding. The concept of cognitive debt illustrates that outsourcing mental effort yields short-term efficiency but incurs costs related to knowledge building and skill strengthening. The pattern observed is that the mechanism of interaction dictates the outcome: when AI functions as an external memory aid or shortcut, it compromises practice and internalization necessary for true skill acquisition. This suggests that the risk is not necessarily making individuals "stupid," but eroding the pathways through which complex reasoning is practiced and stored.
The implication for human agency lies in the necessity of developing metacognitive strategies to manage this technological shift. The contrast between using AI as a passive synthesizer versus an active collaborator—seeking hints or challenging outputs—demonstrates that the technology functions less as a pure knowledge source and more as an amplifier of existing cognitive styles. The erosion observed in professional skills, such as endoscopist detection rates, further suggests that the impact extends beyond individual learning to systemic performance when reliance on external tools is introduced.
The fundamental question shifts from whether AI dulls intelligence to how we structure our relationship with information processing. If the focus remains on leveraging AI for scaffolding—as a writing coach or brainstorming partner—while consciously retaining responsibility for foundational reasoning, an adaptive framework can emerge. The critical unknown remains whether this capacity for strategic offloading will become a new baseline, or if it signals a fundamental shift in what we define as thinking itself. What are the alternative architectures of knowledge creation that exist outside the current human-AI interaction paradigm?
Sentinel — Human
The text is a synthesized analysis of cognitive offloading research, presenting opposing views supported by specific examples, characteristic of high-quality journalistic or long-form essay writing.