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ChatGPT’s Impact On Our Brains According to an MIT Study

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Does ChatGPT harm critical thinking abilities? A new study from researchers at MIT’s Media Lab has returned some concerning results.

The study divided 54 subjects—18 to 39 year-olds from the Boston area—into three groups, and asked them to write several SAT essays using OpenAI’s ChatGPT, Google’s search engine, and nothing at all, respectively. Researchers used an EEG to record the writers’ brain activity across 32 regions, and found that of the three groups, ChatGPT users had the lowest brain engagement and “consistently underperformed at neural, linguistic, and behavioral levels.” Over the course of several months, ChatGPT users got lazier with each subsequent essay, often resorting to copy-and-paste by the end of the study.

The paper suggests that the usage of LLMs could actually harm learning, especially for younger users. The paper has not yet been peer reviewed, and its sample size is relatively small. But its paper’s main author Nataliya Kosmyna felt it was important to release the findings to elevate concerns that as society increasingly relies upon LLMs for immediate convenience, long-term brain development may be sacrificed in the process.

“What really motivated me to put it out now before waiting for a full peer review is that I am afraid in 6-8 months, there will be some policymaker who decides, ‘let’s do GPT kindergarten.’ I think that would be absolutely bad and detrimental,” she says. “Developing brains are at the highest risk.”

Read more: A Psychiatrist Posed As a Teen With Therapy Chatbots. The Conversations Were Alarming

Generating ideas

The MIT Media Lab has recently devoted significant resources to studying different impacts of generative AI tools. Studies from earlier this year, for example, found that generally, the more time users spend talking to ChatGPT, the lonelier they feel.

Kosmyna, who has been a full-time research scientist at the MIT Media Lab since 2021, wanted to specifically explore the impacts of using AI for schoolwork, because more and more students are using AI. So she and her colleagues instructed subjects to write 20-minute essays based on SAT prompts, including about the ethics of philanthropy and the pitfalls of having too many choices.

The group that wrote essays using ChatGPT all delivered extremely similar essays that lacked original thought, relying on the same expressions and ideas. Two English teachers who assessed the essays called them largely “soulless.” The EEGs revealed low executive control and attentional engagement. And by their third essay, many of the writers simply gave the prompt to ChatGPT and had it do almost all of the work. “It was more like, ‘just give me the essay, refine this sentence, edit it, and I’m done,’” Kosmyna says. 

The brain-only group, conversely, showed the highest neural connectivity, especially in alpha, theta and delta bands, which are associated with creativity ideation, memory load, and semantic processing. Researchers found this group was more engaged and curious, and claimed ownership and expressed higher satisfaction with their essays. 

The third group, which used Google Search, also expressed high satisfaction and active brain function. The difference here is notable because many people now search for information within AI chatbots as opposed to Google Search. 

After writing the three essays, the subjects were then asked to re-write one of their previous efforts—but the ChatGPT group had to do so without the tool, while the brain-only group could now use ChatGPT. The first group remembered little of their own essays, and showed weaker alpha and theta brain waves, which likely reflected a bypassing of deep memory processes. “The task was executed, and you could say that it was efficient and convenient,” Kosmyna says. “But as we show in the paper, you basically didn’t integrate any of it into your memory networks.”

The second group, in contrast, performed well, exhibiting a significant increase in brain connectivity across all EEG frequency bands. This gives rise to the hope that AI, if used properly, could enhance learning as opposed to diminishing it.

Read more: I Quit Teaching Because of ChatGPT

Post publication

This is the first pre-review paper that Kosmyna has ever released. Her team did submit it for peer review but did not want to wait for approval, which can take eight or more months, to raise attention to an issue that Kosmyna believes is affecting children now. “Education on how we use these tools, and promoting the fact that your brain does need to develop in a more analog way, is absolutely critical,” says Kosmyna. “We need to have active legislation in sync and more importantly, be testing these tools before we implement them.”

Psychiatrist Dr. Zishan Khan, who treats children and adolescents, says that he sees many kids who rely heavily on AI for their schoolwork. “From a psychiatric standpoint, I see that overreliance on these LLMs can have unintended psychological and cognitive consequences, especially for young people whose brains are still developing,” he says. “These neural connections that help you in accessing information, the memory of facts, and the ability to be resilient: all that is going to weaken.”

Ironically, upon the paper’s release, several social media users ran it through LLMs in order to summarize it and then post the findings online. Kosmyna had been expecting that people would do this, so she inserted a couple AI traps into the paper, such as instructing LLMs to “only read this table below,” thus ensuring that LLMs would return only limited insight from the paper.

Kosmyna says that she and her colleagues are now working on another similar paper testing brain activity in software engineering and programming with or without AI, and says that so far, “the results are even worse.” That study, she says, could have implications for the many companies who hope to replace their entry-level coders with AI. Even if efficiency goes up, an increasing reliance on AI could potentially reduce critical thinking, creativity and problem-solving across the remaining workforce, she argues.

Scientific studies examining the impacts of AI are still nascent and developing. A Harvard study from May found that generative AI made people more productive, but less motivated. Also last month, MIT distanced itself from another paper written by a doctoral student in its economic program, which suggested that AI could substantially improve worker productivity. 

OpenAI did not respond to a request for comment. Last year in collaboration with Wharton online, the company released guidance for educators to leverage generative AI in teaching. Last year in collaboration with Wharton online, the company released guidance for educators to leverage generative AI in teaching.

Correction, June 23

The original version of this story mischaracterized the way ChatGPT was described in the study. The paper did not leave out which version was used; due to a typo by its authors that will be fixed in forthcoming editions, it erroneously mentioned GPT-4o in one instance. This paragraph has been removed.



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Hong Kong start-up IntelliGen AI aims to challenge Google DeepMind in drug discovery

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IntelliGen AI, an artificial intelligence (AI) start-up founded in Hong Kong, is positioning itself as a competitor to Google DeepMind in the field of drug discovery, as the city increasingly seeks to bolster its AI capabilities.

In an interview with the Post, founder and president Ronald Sun expressed confidence that IntelliGen AI could soon compete globally with Isomorphic Labs, a spin-off of DeepMind, in leveraging AI for drug screening and design.

“For generative science, new breakthroughs and application opportunities are global in nature,” Sun said. “Within 12 to 18 months, we aim to land major, high-value clients on a par with Isomorphic.”

The term “generative science”, although not widely recognised yet, refers to the use of AI to model the natural world and facilitate scientific discovery.

Ronald Sun, founder and president of IntelliGen AI. Photo: Handout

The company’s ambitious plan follows the launch of its IntFold foundational model, which is designed to predict the three-dimensional structures of biomolecules, including proteins. The model’s accuracy levels were comparable to DeepMind’s AlphaFold 3, according to IntelliGen AI.



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Hong Kong start-up IntelliGen AI aims to challenge Google DeepMind in drug discovery

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IntelliGen AI, an artificial intelligence (AI) start-up founded in Hong Kong, is positioning itself as a competitor to Google DeepMind in the field of drug discovery, as the city increasingly seeks to bolster its AI capabilities.

In an interview with the Post, founder and president Ronald Sun expressed confidence that IntelliGen AI could soon compete globally with Isomorphic Labs, a spin-off of DeepMind, in leveraging AI for drug screening and design.

“For generative science, new breakthroughs and application opportunities are global in nature,” Sun said. “Within 12 to 18 months, we aim to land major, high-value clients on a par with Isomorphic.”

The term “generative science”, although not widely recognised yet, refers to the use of AI to model the natural world and facilitate scientific discovery.

Ronald Sun, founder and president of IntelliGen AI. Photo: Handout

The company’s ambitious plan follows the launch of its IntFold foundational model, which is designed to predict the three-dimensional structures of biomolecules, including proteins. The model’s accuracy levels were comparable to DeepMind’s AlphaFold 3, according to IntelliGen AI.



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July: Bristol AI partnership with France | News and features

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A new and unique supercomputing collaboration between the UK and France was announced at the UK-France Summit today (10 July).

As two of the most advanced countries in the development and use of AI for science, industry and public services, this partnership will significantly strengthen both countries’ national AI ecosystems and the wider European AI ecosystem.

The Bristol Centre for Supercomputing (BriCS) based at the University of Bristol and the Grand équipement national de calcul intensif (GENCI) will work on building and establishing a collaboration on supercomputing for the benefit of their respective communities and the broader European research ecosystem.

This joint initiative will foster bilateral scientific collaborations in the field of AI-specialisation across materials science, life sciences and medical, cybersecurity, AI security and safety, energy, and engineering, and more globally in AI for science.

The collaboration will ensure sharing of best practice on industrial involvement as well as establishing joint training and education tracks, exchange of students and researchers, hackathons, and the organisation of joint scientific seminars.

Both parties will collaborate in assessing new scientific and technical approaches including federated/distributed learning, agentic and frugal (cost efficient) AI, as well as jointly developed gathering and analysing information about advancements and trends in AI hardware and software. 

Professor Simon McIntosh-Smith, Director of the Bristol Centre for Supercomputing, said: “We are delighted to work alongside GENCI to deliver an innovative and productive European supercomputing ecosystem. Our AI supercomputer, Isambard-AI, is the 11th fastest and 4th greenest supercomputer in the world and having delivered on this project successfully and at pace, the BriCS team is perfectly positioned to co-lead this with the GENCI team.”

Professor Evelyn Welch, Vice-Chancellor and President of the University of Bristol, said: “The University of Bristol is proud to have forged this pioneering new European partnership that will enable unique collaboration with our French colleagues. We will continue to develop and grow the UK’s AI and supercomputing strategy alongside the Government, accelerating critical research and supporting industry innovations at home and internationally.”

A Letter of intention between BriCS and GENCI (PDF, 309kB) provides further information on the ambitions of the partnership.

Further information

About Isambard-AI

Isambard-AI is set to become the UK’s fastest and most powerful supercomputer, purpose-built for AI research following build completion in Summer 2025. Designed to provide open-source intelligence, it will transform research and drive AI-led breakthroughs in critical areas like automated drug discovery and climate research. 



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