A recent experiment provides evidence that relying on artificial intelligence to help study new material tends to reduce how much information students remember weeks later. The findings suggest that while these tools can speed up initial learning, they might actually weaken the deep mental processing required to store knowledge over the long term.

The study was published in the journal Social Sciences & Humanities Open. Generative artificial intelligence refers to computer programs capable of creating text, images, or other media in response to user prompts. These systems can answer complex questions, synthesize vast amounts of information, and write essays in seconds. Because of this convenience, millions of university students use these programs to assist with their coursework.

André Barcaui, a professor in the Business Management course at the Federal University of Rio de Janeiro, conducted the study to see how this technology affects memory. He wanted to test whether the ease of getting answers from a chatbot harms long-term learning.

When a student delegates mental tasks to an external tool, psychologists call it cognitive offloading. In the past, this meant using a calculator for math or a notebook to remember a grocery list. Generative AI platforms take this a step further by performing the actual thinking, analyzing, and problem-solving.

Barcaui grounded his research in the concept of desirable difficulties, a psychological principle that suggests that learning actually improves when a student faces a certain amount of productive struggle. Activities like actively trying to remember a fact or puzzling through a tough concept force the brain to build stronger memory pathways.

By providing immediate and polished answers, an automated chatbot might remove these necessary hurdles. Without that mental friction, students might experience weaker memory consolidation. Memory consolidation is the biological process where fragile new memories are stabilized and stored securely in the brain over time.

To investigate this dynamic, Barcaui recruited 120 undergraduate business administration students. The participants were randomly divided into two equal groups of 60. Both groups received the same assignment, which required them to research basic artificial intelligence concepts. Topics included ethics, societal impacts, and technical foundations.

The task required the students to spend up to two weeks researching their assigned topic and prepare a ten-minute presentation. The first group was instructed to use a specific AI chatbot, known as ChatGPT, as a study aid. They interacted freely with the program to explain concepts, generate examples, and structure their presentations.

After the initial research period, the participants delivered their presentations to small groups of their peers. The students then went about their normal academic lives for a month and a half. Forty-five days after the initial study phase, the researcher surprised the participants with a retention test. The students who used traditional study methods performed better. On average, the traditional learners answered 68.5 percent of the questions correctly. In contrast, the students who studied with the chatbot answered only 57.5 percent of the questions correctly.

The negative impact of the chatbot was most pronounced when students were learning highly technical topics. While the software also impaired memory for less technical topics, such as ethics and society, the gap between the two groups was not as wide. This pattern suggests that productive struggle is especially important when mastering complex or structurally difficult material.

Barcaui highlighted three main takeaways: “Productivity does not replace Competence: There is an abysmal difference between delivering a piece of work and understanding the process of its creation. The indiscriminate use of AI can create an ‘illusion of competence,’ where the individual obtains results without developing the synapses necessary to replicate that reasoning independently.”

“The Atrophy of the Critical ‘Muscle’: Just as the constant use of calculators reduced mental calculation skills, delegating writing and text interpretation to AI can atrophy the capacity for synthesis and critical thinking. Without the mental ‘friction’ of reading and writing, we lose the ability to articulate complex ideas and question information.” “AI as Co-pilot, not Autopilot: The main lesson is that AI should be used to expand human capabilities (increase reach), not to replace them (eliminate effort). Human value will increasingly shift from the ability to execute to the ability to ask the right questions and critically curate the generated data”.