A study by MIT researchers has found “our behavior is often more predictable than we think,” reports Diane Hamilton for Forbes. “This research focused on how people pay attention in complex situations,” explains Hamilton. “The AI model learned what people remembered and what they ignored. It identified patterns in memory and focus.”
Prof. Danielle Li speaks with New York Times reporter Noam Scheiber about the various impacts of AI in the workplace on employees. “That state of the world is not good for experienced workers,” says Li. “You’re being paid for the rarity of your skill, and what happens is that A.I. allows the skill to live outside of people.”
Forbes reporter Eric Wood spotlights various studies by MIT researchers exploring the impact of ChatGPT use on behavior and the brain. “As stated, the impact of AI assistants is likely dependent on the users, but since AI assistants are becoming normative, it’s time for counseling centers to assess for maladaptive uses of AI, while also promoting the possible benefits,” explains Wood.
Prof. Asu Ozdaglar, Deputy Dean of MIT Schwarzman College of Computing, speaks with Is Business Broken? podcast host Curt Nickish to explore AI’s opportunities and risks — and whether it can be regulated without stifling progress. “AI is a very promising and transformative technology,” says Ozdaglar. “But regulation should be designed very carefully so that it does not block or impede the development of the technology.” Given AI’s potential harms or misuses, she added that it's important to think about the correct regulatory framework. “For it to be successful, it should focus on where harms can come from.”
In an Opinion piece for The New York Times, columnist David Brooks highlights a recent MIT study that explores the impact of ChatGPT use on brain function by asking subjects to write essays while using large language models, traditional search engines, or only their own brains. “The subjects who relied only on their own brains showed higher connectivity across a bunch of brain regions,” explains Brooks. “Search engine users experienced less brain connectivity and A.I. users least of all.”
Researchers at MIT have developed an “AI-powered tool that scans scientific literature and over 1 million rock samples to identify materials that can partially replace cement in concrete,” reports Samanatha Hindman for Yahoo! News. The new system could “change how we build cities forever,” says Hindman. “The system sorts materials based on their physical and chemical properties, narrowing them down by how well they hold concrete together when mixed with water (hydraulic reactivity) and how they strengthen it over time (pozzolanicity).”
A study by MIT researchers monitored and compared the brain activity of participants using large language models, traditional search engines, and only their brains to write an essay on a given topic, reports Hessie Jones for Forbes. The study “found that the brain-only group showed much more active brain waves compared to the search-only and LLM-only groups,” Jones explains. “In the latter two groups, participants relied on external sources for information. The search-only group still needed some topic understanding to look up information, and like using a calculator — you must understand its functions to get the right answer. In contrast, the LLM-only group simply had to remember the prompt used to generate the essay, with little to no actual cognitive processing involved.”
In an effort to help “build the tools and talent to shape a more productive and sustainable future for manufacturing,” MIT has launched the Initiative for New Manufacturing (INM), reports Nathan Owens for Manufacturing Dive. Owens explains that to help accelerate technology adoption and manufacturing productivity, the INM has "mapped out a series of education and industry partnership programs, including plans to establish new labs and a 'factory observation' effort that allows students to visit production sites.”
Researchers at MIT have found that ChatGPT users “showed minimal brain engagement and consistently fell short in neural linguistic, and behavioral aspects,” reports Kyle Wiggers for TechCrunch. “To conduct the test, the lab split 54 participants from the Boston area into three groups, each consisting of individuals ages 18 to 39,” explains Wiggers. “The participants were asked to write multiple SAT essays using tools such as OpenAI’s ChatGPT, the Google search engine, or without any tools.”
The New Yorker reporter Kyle Chayka spotlights a study by MIT researchers examining the impact of AI chatbot use on the brain. “The results from the analysis showed a dramatic discrepancy: subjects who used ChatGPT demonstrated less brain activity than either of the other groups,” explains Chayka.
Noman Bashir, a fellow with MIT’s Climate and Sustainability Consortium, speaks with Abby Acone of FOX 13 about the environmental impacts of generative AI, and the benefits and challenges posed by increasing use of AI tools. Bashir emphasizes that the use of generative AI should be “very judicious, not a blind application of AI for all applications.”
A study by researchers from MIT and elsewhere compares productivity differences between remote and in-person work attendance, reports Gleb Tsipursky for The Hill. The study found that “employees do not simply become more efficient because a manager watches their every move,” explains Tsipursky. “Rather, they want clarity, communication, and trust.”
Researchers from MIT have found that “extended use of LLMs for research and writing could have long-term behavioral effects, such as lower brain engagement and laziness,” reports Theo Burman for Newsweek. “The study found that the AI-assisted writers were engaging their deep memory processes far less than the control groups, and that their information recall skills were worse after producing work with ChatGPT,” explains Burman.
Researchers at MIT have found that “AI agents can make the workplace more productive when fine-tuned for different personality types, but human co-workers pay a price in lost socialization,” reports Kaustuv Basu for Bloomberg. The researchers concluded “found that humans using AI raised their productivity by 60%—partly because those workers sent 23% fewer social messages,” writes Basu.
Sloan Lecturer Michael Schrage speaks with Fortune reporter Sheryl Estrada about prompt-a-thons, “structured, sprint-based sessions for developing prompts for large language models (LLMs).” The “prompt-a-thon process reframes prompting as a high-impact diagnostic and design discipline—engineered for fast, actionable insight,” explains Estrada. “It’s not just about using AI more effectively—it’s about thinking and collaborating more intelligently with it,” adds Schrage.