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NewsMaterial3 min readDisconfirmAI Editorial

US Survey: About One-Third of Executives Trust AI More Than Their Own Judgment; MIT Experiment Shows Decline in Fact-Checking Ability After One Month of Reliance

A survey conducted in August by the US research organization Charter among over 5,000 American AI users found that approximately one-third of executives trust AI more than their own judgment, a proportion twice that of ordinary employees. Meanwhile, an experiment by the MIT Media Lab showed that subjects who relied on AI to verify facts for a month experienced a decline in their ability to detect misinformation after the tool was removed. German tech media t3n.de links these findings under the mechanism of 'Cognitive Offloading': when executives hired to provide judgment delegate it to systems that only make statistical predictions, risk increases.

2026-10-22 19:00 GMT+8

The August survey by the Charter research organization covered over 5,000 US respondents who reported using AI at work. Results show that approximately one-third of executives trust AI's judgment more than their own, while this proportion is only about half as high among ordinary employees. On the question of 'who truly benefits from AI,' 55% of executives stated that AI improved both their work and personal lives, whereas only about half of the employees gave the same response.

The article by t3n.de points out a structural contradiction: companies hire executives for their experience and knowledge, not to hand over decisions to AI. When those most responsible for providing judgment begin to offload it, the issue is no longer just personal preference but the erosion of organizational capability.

The article introduces a specific term to describe this phenomenon: 'Cognitive Offloading,' which refers to the behavior of transferring cognitive work to AI systems to reduce one's own cognitive load. Having AI summarize a long article rather than reading it oneself, or having AI analyze resumes or financial data rather than reviewing them personally—these practices indeed save time and mental energy. However, the cost of saving cognitive load may be the cognitive capacity itself.

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An experiment by the MIT Media Lab also showed that subjects who delegated fact-checking tasks to AI systems for a month had reduced ability to detect misinformation when the AI tool was no longer available. Anku Rani, a doctoral student and one of the study's lead authors, warned in an MIT publication that users often forget that AI models make statistical predictions, not true judgments.

The Center for Universal Education, part of the Brookings Institution, observed a similar pattern among adolescents: when students hand over their thinking processes to AI, the educational process may be undermined. 65% of surveyed students expressed concern about the long-term decline of their cognitive abilities. One student's quote was: 'Simply put, you don't need to use your brain.'

These pieces of evidence collectively point to a 'Deskilling' mechanism, analogous to how calculators weakened mental arithmetic skills in historical precedents. The difference is that calculators handle deterministic calculations, while AI handles judgmental tasks—the latter being precisely the reason executives are hired. When statistical predictions are used as judgment, hallucinations, misleading inferences, and biases enter the decision chain, affecting scope from individual executives to the entire organization.

It must be clarified that the MIT experiment measured a specific ability—fact-checking—rather than general management judgment. The survey data reflects self-reported trust levels, not direct measurements of decision quality. There is an extrapolation between 'decline in discrimination ability after relying on AI for fact-checking for one month' and 'degeneration of judgment after executives delegate data analysis to AI,' involving differences in task complexity and time span. However, consistent directional evidence is sufficient to indicate that cognitive offloading is not a zero-cost efficiency tool; it may be eroding core capabilities in ways least noticeable to the user.

Sources

  • t3n.de↗
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