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Large Language ModelsAI Safety & Alignmentr/artificialPublished: Aug 20, 2026, 01:03 JST2 min read

LLM users report weaker reasoning; two studies back the concern

LLM users report weaker reasoning; two studies back the concern

Key takeaway

  • Two recent academic studies found that regular use of large language models correlates with weaker reasoning and critical thinking.

  • MIT Media Lab research detected reduced brain connectivity and lower sense of ownership in LLM-assisted writing, while a separate study found frequent AI use linked to lower critical thinking scores, mediated by cognitive offloading.

  • Although neither study proves permanent damage, users report that offloading effortful tasks like problem-breaking and argument-building to LLMs makes independent reasoning harder afterward.

3 Key Points

  1. What happened

    Two recent studies found cognitive effects tied to regular LLM use. MIT Media Lab research (Kosmyna et al. 2025) detected reduced EEG connectivity, worse recall of one's own text, and lower sense of ownership when writing essays with LLM assistance. A separate 2025 study in *Societies* (Gerlich) found a negative correlation between frequent AI use and critical thinking scores, with cognitive offloading as the mediating factor.

  2. Why it matters

    Users report offloading effortful cognitive tasks—breaking down problems, building arguments, phrasing—the moment an LLM is available, making unaided reasoning feel harder afterward. Neither study proves permanent damage, but the pattern suggests regular LLM reliance may atrophy reasoning skills in the specific tasks delegated to the model, raising questions about long-term effects on professional and intellectual work.

  3. What to watch

    The Reddit discussion frames the core tension: which tasks are worth keeping off-LLM to preserve cognitive strength, and what concrete routines or rules might protect reasoning ability while still using AI assistance.

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Context & Analysis

The concern articulated in the Reddit post—that offloading reasoning tasks to LLMs makes unaided thinking harder—now has preliminary research backing. MIT Media Lab's focus on EEG connectivity and sense of ownership during writing suggests the cognitive cost goes beyond task performance; it may touch how deeply the writer engages with their own thought process. The Gerlich study's finding of a mediation effect through cognitive offloading points to a mechanism: the more frequently users delegate thinking, the more their critical thinking capacity atrophies, at least measurably. Yet causality remains open. The studies document correlation and plausible pathways, not proof that LLM use *permanently* weakens reasoning. The distinction matters: a temporary dip in unaided performance after heavy LLM use is different from irreversible cognitive decline. The Reddit framing—asking which tasks users deliberately *don't* offload and what routines protect thinking—suggests a pragmatic next step: identifying which cognitive habits and task boundaries preserve reasoning strength alongside AI assistance.

FAQ

Which studies found this effect?
MIT Media Lab (Kosmyna et al. 2025) found reduced EEG connectivity, worse recall of one's own text, and lower sense of ownership under LLM-assisted essay writing. A 2025 study by Gerlich in *Societies* found a negative correlation between frequent AI use and critical thinking scores, mediated by cognitive offloading.
Do these studies prove long-term damage?
No. The body explicitly states that neither study proves long-term causal damage, only that the correlation and mechanism exist.

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