MIT Makes Shocking Find How ChatGPT Affects Users

A recent study by the Media Lab at Massachusetts Institute of Technology (MIT) has made an interesting discovery, How ChatGPT Affects Users.

With the title: Your Brain on ChatGPT, It is indeed a discovery that may shock ChatGPT burgeoning users globally, centering on the long-term educational implications of LLM reliance, while also underscoring the need for deeper inquiry into AI’s role in learning

Prolonged use of ChatGPT, a large language model (LLM) chatbot, the institution found, can have a harmful impact on the cognitive abilities of its users.

It said, over four months, LLM users consistently underperformed at neural, linguistic, and behavioral levels.

These results raise concerns about the long-term educational implications of LLM reliance and underscore the need for deeper inquiry into AI’s role in learning, the report which main author is research scientist Nataliya Kos’myna, noted.

Providing a background to his reason for undertaking the study, How ChatGPT Affects Users, the researcher said:

“What really motivated me to put it out now before waiting for a full peer review is that I am afraid in six to eight months, there will be some policymaker who decides, ‘let’s do GPT kindergarten,’” Kos’myna told Time magazine. “I think that would be absolutely bad and detrimental. Developing brains are at the highest risk.”

ChatGPT Affects Users are affected in ways that many may not have taken due cognisance of, a new study says

With today’s wide adoption of LLM products like ChatGPT from OpenAI, humans and businesses engage and use LLMs on a daily basis, the researchers say, adding:

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Like any other tool, it carries its own set of advantages and limitations. This study focuses on finding out the cognitive cost of using an LLM in the educational context of writing an essay.

We assigned participants to three groups: LLM group, Search Engine group, and Brain-only group, where each participant used a designated tool (or no tool in the latter) to write an essay. We conducted 3 sessions with the same group assignment for each participant.

In the 4th session we asked LLM group participants to use no tools (we refer to them as LLM-to-Brain), and the Brain-only group participants were asked to use LLM (Brain-to-LLM). We recruited a total of 54 participants for Sessions 1, 2, 3, and 18 participants among them completed session 4.

We used electroencephalography (EEG) to record participants’ brain activity in order to assess their cognitive engagement and cognitive load, and to gain a deeper understanding of neural activations during the essay writing task.

We performed NLP analysis, and we interviewed each participant after each session. We performed scoring with the help from the human teachers and an AI judge (a specially built AI agent).

We discovered a consistent homogeneity across the Named Entities Recognition (NERs), n-grams, ontology of topics within each group. EEG analysis presented robust evidence that LLM, Search Engine and Brain-only groups had significantly different neural connectivity patterns, reflecting divergent cognitive strategies.

Brain connectivity systematically scaled down with the amount of external support: the Brain‑only group exhibited the strongest, widest‑ranging networks, Search Engine group showed intermediate engagement, and LLM assistance elicited the weakest overall coupling.

In session 4, LLM-to-Brain participants showed weaker neural connectivity and under-engagement of alpha and beta networks; and the Brain-to-LLM participants demonstrated higher memory recall, and re‑engagement of widespread occipito-parietal and prefrontal nodes, likely supporting the visual processing, similar to the one frequently perceived in the Search Engine group.

The reported ownership of LLM group’s essays in the interviews was low. The Search Engine group had strong ownership, but lesser than the Brain-only group. The LLM group also fell behind in their ability to quote from the essays they wrote just minutes prior.

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As the educational impact of LLM use only begins to settle with the general population, in this study we demonstrate the pressing matter of exploring a possible decrease in learning skills based on the preliminary results of our study.

The use of LLM had a measurable impact on our participants, and while the benefits were initially apparent, as we demonstrated over the course of 4 sessions, which took place over 4 months, the LLM group’s participants performed worse than their counterparts in the Brain-only group at all levels: neural, linguistic, scoring.

We hope this study on How ChatGPT Affects Users serves as a preliminary guide to encourage better understanding of the cognitive and practical impacts of AI on learning environments, the Massachusetts Institute of Technology researchers stated.