#Mit

A new study from the Massachusetts Institute of Technology (MIT) has ignited debate over the cognitive impact of AI writing tools like ChatGPT, revealing that their use significantly reduces brain activity and leads to less creative, more “soulless” work. The findings, published in June 2025, raise questions over the future role of artificial intelligence in education, as policymakers and educators across the world—including in Thailand—navigate the integration of new technologies in the classroom.

A new MIT study raises critical questions about how AI writing tools like ChatGPT affect student thinking and creativity. Published in June 2025, the research suggests that using AI writing aids can blunt brain activity and produce more formulaic essays. The findings spark a global conversation, including in Thailand, about how to balance digital tools with foundational skills in classrooms.

The study followed 54 college students who wrote SAT-style essays on philosophical topics, such as the desirability of a perfect society and the moral obligations of the fortunate to help others. Participants were assigned to three conditions: using ChatGPT, using Google Search, or writing without digital help. Researchers tracked brain activity with EEG across 32 brain regions during the writing tasks.

In an event reverberating across the scientific community, the Massachusetts Institute of Technology (MIT) has publicly rescinded its institutional support for a recent artificial intelligence (AI) research paper. The move, reported by Retraction Watch, raises fundamental questions about the future of AI-authored academic articles and the ethical challenges facing research institutions worldwide.

The decision by MIT, a global powerhouse in science and technology innovation, has significant implications for the credibility and accountability of scientific literature. AI-generated content, increasingly prevalent in both drafting and data analysis duties, is under the microscope for issues relating to originality, transparency, and academic integrity. For Thai academic institutions, researchers, and the broader public, this case exemplifies the urgent need to establish clear policies and ethical guardrails as the adoption of AI tools accelerates throughout the research landscape.

A move with wide reverberations in science circles: MIT has publicly withdrawn its institutional support for a recent AI-driven research paper. The decision, reported by Retraction Watch, highlights ongoing questions about AI’s role in drafting and analyzing scientific work and the ethical responsibilities of research institutions worldwide. For Thai readers, the episode signals a crucial moment to establish clear policies on AI use in research and publication.

MIT’s reversal raises questions about how much credit AI should receive in scholarly work and whether automated systems can or should participate as contributors or co-authors. The cited paper reportedly used advanced language models to generate substantial portions of text and analysis, prompting concerns that automation could bypass essential peer review steps or recycle unverifiable content. A technology ethics expert noted that while AI can summarize or rephrase existing research, it cannot reliably assess the validity of scientific claims or ensure precise citations.

A major shake-up in the global research community follows MIT’s formal withdrawal of support for a widely circulated AI study. The paper, titled Artificial Intelligence, Scientific Discovery, and Product Innovation, was posted on arXiv in November 2024 and drew attention for claims that AI could dramatically accelerate scientific progress and product development. After a confidential internal review, MIT stated it has no confidence in the data, provenance, or validity of the research, marking a rare public reversal from a leading research university.

In a move that has reverberated throughout the global academic community, the Massachusetts Institute of Technology (MIT) has formally withdrawn its support for a widely circulated research paper on artificial intelligence (AI) authored by a former PhD student in its economics program. The paper, titled “Artificial Intelligence, Scientific Discovery, and Product Innovation,” was first posted to the preprint server arXiv in November 2024 and quickly garnered high-profile attention for purportedly showing how AI can significantly boost scientific discovery and product innovation. However, following a confidential review, MIT has announced it has “no confidence in the provenance, reliability or validity of the data and [has] no confidence in the veracity of the research contained in the paper,” marking a rare and public reversal from one of the world’s top research universities (source).

A leading center at MIT is accelerating our understanding of the human brain and turning discoveries into practical tools for health, learning, and inclusion. The McGovern Institute for Brain Research is identified as a hub of cutting-edge neuroscience, bringing together researchers across disciplines to tackle questions that matter to public health and education in Thailand and Southeast Asia. New projects point to breakthroughs in treating psychiatric disorders, supporting neurodiverse learners, and strengthening community health systems.

A new MIT study upends decades of neuroscience by showing the brain’s object-recognition pathway may also play a crucial role in processing spatial information. This could transform approaches to learning, AI, and brain health, including in Thailand.

For years, scientists have said the ventral visual stream is mainly about identifying objects—think recognizing a coffee cup on a Bangkok Skytrain or a rambutan vendor at Chatuchak. This view guided neuroscience education and powered computer-vision advances used in smartphones and smart cars. Now, MIT researchers led by graduate student Yudi Xie demonstrate that training deep learning models to grasp spatial details like location, rotation, and size yields brain activity in the ventral stream that matches, or even exceeds, traditional object-recognition models. The ventral stream may be a versatile toolkit for seeing and interacting with the world, not just a face- or product-recognition system.

A groundbreaking study from MIT is shaking up decades of neuroscience wisdom, revealing the brain’s “object recognition” pathway may also play a significant role in understanding spatial information—an insight that could revolutionize our approach to learning, artificial intelligence, and brain health around the world, including here in Thailand.

For years, scientists have believed the ventral visual stream, a key pathway in the human brain, is dedicated to recognizing objects—like a Starbucks cup on a Bangkok Skytrain or a rambutan vendor at the Chatuchak Market. This idea shaped not just neuroscience textbooks, but also inspired computer vision systems now used in everything from smartphones to smart cars. Yet, new research led by MIT graduate student Yudi Xie suggests the story is far more nuanced. Their findings, presented at the prestigious International Conference on Learning Representations, show that when deep learning models are trained not only to identify objects, but also to understand spatial features like location, rotation, and size, these models mirror neural activity in the ventral stream just as accurately as traditional object recognition models. In other words, the ventral stream might be wired for much more than recognizing faces or products—it could be a multifaceted toolkit for seeing and interacting with the world.

A new study from researchers at MIT and Harvard Medical School reveals that the immune molecule IL-17 can influence social behavior and anxiety by acting directly on specific brain regions. The research shows IL-17 has a dual role: it enhances sociability by dampening neuron activity in the cortex, while it increases anxiety by heightening excitability in the amygdala. In effect, IL-17 appears to function as a neuromodulator, linking immune system activity with how we feel and behave. This insight could inform future approaches to conditions such as autism and depression, according to the study’s findings and interpretations from leading neuroscience outlets.

Recent research led by MIT and Harvard Medical School has uncovered the intriguing role that the immune molecule interleukin-17 (IL-17) plays in shaping social behavior and anxiety by acting directly on specific brain regions. This groundbreaking study reveals that IL-17 serves dual functions: enhancing sociability by reducing neuron excitability in the brain’s cortex and triggering anxiety by increasing excitability in the amygdala. These findings suggest IL-17 acts like a neuromodulator, drawing a fascinating link between immune system activity and behavioral outcomes, with potential implications for the treatment of conditions like autism and depression (Neuroscience News).