The widespread adoption of Generative Artificial Intelligence (GenAI) technologies represents one of the most rapid processes of technological adaptation in human history. ChatGPT and similar models have accelerated writing, coding, and analytical processes to an unprecedented degree. However, recent research in the fields of neurobiology and cognitive psychology indicates that this convenience comes with a “hidden cost.” Experts are calling this phenomenon “cognitive debt.”
An experiment conducted by researchers at the Massachusetts Institute of Technology (MIT) aimed to study the impact of artificial intelligence on neuronal activity in the human brain. The study involved 54 students divided into three groups: the first group relied solely on their own knowledge, the second used search engines, and the third was assigned to write an essay with the assistance of ChatGPT. Throughout the process, the participants’ brainwaves were recorded using electroencephalography (EEG).
The results showed that the group using only their own mental faculties exhibited the highest levels of cognitive connectivity and neuronal activity. Conversely, brain activity in participants using artificial intelligence was significantly lower, indicating that the brain had entered an “autopilot” mode.
Most concerning was the second phase of the experiment: when roles were reversed, participants who had consistently relied on artificial intelligence faced serious difficulties in independent thinking and memory utilization. They were unable to reconstruct their texts, and their work lacked logical consistency.
The theory of “Cognitive Debt”
In the technology world, the concept of “technical debt” refers to the implied cost of future reworking caused by choosing an easy, limited solution now instead of using a better approach that would take longer. Researchers are now introducing the term “cognitive debt.” This state describes the atrophy of critical thinking, analysis, and information synthesis skills resulting from the offloading of human mental labor to external tools (artificial intelligence).
Scientists at Vrije Universiteit Amsterdam emphasize that students and professionals are placing excessive trust in the information provided by Large Language Models (LLMs). Because AI responses are delivered in an academic and authoritative tone, users are bypassing the verification process. This, in turn, can lead to the degradation of critical thinking.
Algorithmic bias and the illusion of objectivity
Natasha Govender-Ropert, Head of AI for Financial Crimes at Rabobank, raises another critical issue: bias. AI models are trained on billions of data points generated by humans throughout history. Consequently, this data is not free from existing societal stereotypes and subjective views.
If a user accepts the result provided by artificial intelligence as absolute truth, they inadvertently adopt outdated social norms and hidden biases. A lack of critical analysis can lead to poor decision-making and a chain reaction of errors.
Articles and studies suggest that the problem lies not in the technology itself, but in the methodology of its use. It is advisable to view artificial intelligence not as a substitute for human thought, but as an instrument that extends it.
According to scientific conclusions, the following principles must be observed to maintain intellectual capacity:
- Active Engagement: Any material generated by artificial intelligence must be deeply analyzed and refined by a human.
- Skeptical Approach: One must develop the skill to view every generated response as potentially erroneous and verify facts through primary sources.
- Cognitive Exercises: Performing a certain portion of complex mental tasks independently, without AI intervention, helps keep neuronal connections active.
The professionals who will achieve the highest efficiency in the future are not those who delegate all work to artificial intelligence, but those who skillfully utilize the technology while preserving their critical thinking abilities.
Gulnoza Mikhailovna
