-- Dr. Vishal Kapoor is calling for greater attention to how AI dependence could affect independent thinking, critical reasoning, and human judgment, as artificial intelligence becomes increasingly embedded in professional and educational environments,
Kapoor, whose perspectives on AI and human cognition are shared through his LinkedIn newsletter, argues that the growing emphasis on productivity risks overlooking an important question: whether people remain capable of reasoning independently when AI tools are no longer available.
Research has highlighted the productivity benefits of generative AI. A 2025 field experiment titled Shifting Work Patterns with Generative AI, involving approximately 6,000 workers, examined how AI influenced workplace activities, including email. Another study, The Effects of Generative AI on High-Skilled Work, involving 4,867 software developers, reported a 26.08% increase in completed tasks with AI assistance.
For Kapoor, these findings demonstrate why productivity should not be the only measure of successful AI adoption.
“Productivity tells us how quickly work gets done, but it does not necessarily tell us whether the person doing the work is becoming more capable,” Kapoor argues. “We need to consider what happens to human reasoning when we increasingly rely on AI to perform the thinking that once required our own effort.”
Cognitive offloading, the practice of using external tools to reduce mental effort, predates generative AI. Calculators and search engines have long helped people delegate certain tasks. However, generative AI can go further by producing explanations, developing arguments, and offering conclusions that users might otherwise work through themselves.
Research from the MIT Media Lab examined participants completing essays with and without large language model assistance. The findings raised questions about differences in cognitive engagement and subsequent performance when AI assistance was removed. Although further research is needed to establish the long-term effects of AI dependence, Kapoor believes these questions deserve attention as the technology becomes more widespread.
His concerns are informed partly by personal experience. After using AI to assist with reasoning, he observed a decline in his cognitive profile on a brain-training tool, which he estimated at approximately 40 to 50 points on a 1,000-point scale. He views this as a personal observation that prompted him to reconsider his working habits, not as scientific proof that AI causes cognitive decline.
Rather than opposing AI adoption, Kapoor advocates an approach he calls “AI-fed, human-led.” The philosophy encourages people to develop their own observations, questions, and hypotheses before using AI to investigate gaps, challenge assumptions, and strengthen conclusions.
“When AI becomes a dominant part of the process, reasoning is often the first to go,” Kapoor says.
For example, someone researching a new market could begin by identifying a hypothesis and determining what evidence is needed to test it. AI could then assist with gathering information and evaluating alternative explanations, while the individual remains responsible for interpreting the findings.
Kapoor summarizes the principle simply: “Do not outsource the first question or the final decision.”
He believes this distinction matters in professional environments, where AI can produce convincing answers without guaranteeing that their underlying assumptions are sound. Workers still need the ability to recognize errors, challenge recommendations, and make informed decisions in unfamiliar circumstances.
Kapoor argues that organizations should evaluate AI not only through productivity gains and cost savings, but also by considering whether employees continue developing the skills needed to assess AI-generated information independently.
Education presents a particularly important challenge. If students use AI to complete assignments without engaging with the underlying concepts, the technology could undermine opportunities to develop analytical skills.
“The purpose of education is to develop the human brain,” Kapoor says. “If the human brain is not developed as part of that education, then what's the use of that education?”
He advocates a task-specific approach to AI adoption, with particular care in education and original research, where independent analysis and skill development are essential.
For business leaders and policymakers, this means considering not only which tasks can be automated, but also which human capabilities must continue to be exercised. In high-stakes decisions, processing information quickly is not the same as making the right decision. Human responsibility, values, and judgment remain essential.
As AI systems become increasingly capable, Kapoor believes the conversation must expand beyond what machines can accomplish to include what people retain the ability to do independently.
Through his LinkedIn newsletter, he encourages leaders to consider how AI can complement human intelligence rather than replace the reasoning processes that underpin it.
His central argument is that technological progress and human capability should advance together. The long-term value of AI, he suggests, should be measured not only by efficiency, but also by whether people remain equipped to understand, challenge, and direct the systems they use.
About the company: Dr. Vishal Kapoor shares perspectives on artificial intelligence, human cognition, and decision-making through his LinkedIn newsletter. His “AI-fed, human-led” philosophy explores how AI can support human reasoning while preserving independent judgment and critical thinking.
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