Computer science and technology

Chronicle of Philanthropy reporter Maria Di Mento spotlights how the creation of the MIT Schwarzman College of Computing allowed MIT to develop new “interdisciplinary programs to prepare students for an AI-saturated world and help them understand the social and ethical implications of digital technologies.” Prof. Daniel Huttenlocher, dean of the Schwarzman College of Computing, explains that: “MIT realized that effective education in the age of AI has to look different than it has in the past. Traditional siloing of expertise won’t work when AI is expected to touch nearly every part of people’s lives and is changing the way people in disciplines outside of computing are advancing their work.”

Writing for Forbes about efforts to improve air travel safety, Tanya Eves highlights the Air-Guardian system, an eye-tracking monitor for pilots developed by CSAIL researchers that assists when attention wavers. “In tests, it reduced flight risk and improved navigation success rates,” writes Eves. “It's a model for how the virtual co-pilot relationship should work: not replacement, but a seamless, intelligent partnership that understands when to act and when to stay silent.”

Writing for Forbes, contributor Ron Schmelzer highlights Describe Anything, Anywhere, at Any Moment (DAAAM), a new system developed by MIT researchers that could enable robots to capture details of objects they see while exploring an environment. In the future, the system could allow factory workers to send robotic assistants to find items. DAAAM “lets a robot build a detailed map of a space, attach descriptions to objects in that map, and answer plain English questions later,” Schmelzer explains. 

Writing for IEEE Spectrum, reporter Matthew S. Smith highlights Fractal, a new operating system hand-coded by CSAIL researchers to provide a clear view of security vulnerabilities. “We paved the way with techniques such as custom kernel patches and kernel extensions,” says graduate student Joseph Ravichandran. “The dream was always to have a completely custom operating system which would make these hacks unnecessary.”

In an effort to defend medical devices against quantum attacks, MIT researchers have engineered an ultra-efficient microchip that can protect wireless biomedical devices, such as insulin pumps and pacemakers, reports Katie Hunt for CNN. The microchip, which is around the size of an extremely fine needle tip, “includes built-in protection needed for post-quantum cybersecurity. The device achieved between 20 and 60 times higher energy efficiency than other post-quantum security techniques.”

In an article republished by Scientific American, Manon Bischoff delves into the history of Margaret Hamilton’s work at the MIT Instrumentation Lab, where she “was one of the people responsible for the features that ultimately made the moon landing possible.” Hamilton helped “program ‘emergency fixes,’ contingency procedures that were implemented when something unexpected happened during a mission.”

New research co-authored by Prof. Michiel Bakker examines the impact of using AI tools on an individual’s ability to solve a set of math problems, writes Jude Cramer for Fast Company. The researchers found that participants “who asked the AI for direct solutions saw the largest decline in solve rate and the largest increase in skip rate.” 

Sybil, a new AI tool developed by researchers from MIT and Mass General Brigham Cancer Institute, “analyzes a single CT scan and generates a risk score predicting the likelihood of developing lung cancer over a period of up to six years,” reports Ivan Rodriguez for WCVB-TV. “In 2023, researchers reported that Sybil achieved an accuracy rate of 86% to 94% in distinguishing high-risk patients from low-risk patients within a year.”

Reporting for CNN, Caleb Hellerman spotlights how MIT computer scientists developed an AI program called Sybil that can “‘look’ at a single CT scan and generate a ‘risk score’ corresponding to the likelihood of the person developing cancer over any period up to six years.”

Fortune reporter Nick Lichtenberg highlights research by MIT economists that finds “automation doesn’t affect all parts of a job equally. The critical variable is whether the tasks being automated are the expert parts of a role or the administrative scaffolding around them.” 

Prof. Sinan Aral joins CNBC’s “Squawk Box” to discuss the state of AI data center construction across the U.S. and the impact of new AI technologies on the power grid. “Data center and compute demand is so large and growing,” says Aral. He adds that hybrid models that “combine the benefit of connecting to the [power] grid with the benefit of an energy island model, where you have onsite storage of energy, you have battery and you have onsite generation to offload during peak times. The hybrid model is really good because it gets the best of both worlds.” 

A new working paper by researchers from MIT FutureTech finds that “AI’s march through the labor market looks far less like a sudden catastrophe and far more like a slow, rising flood — serious and accelerating, but not the overnight apocalypse that has dominated headlines and executive anxiety for the past two years,” writes Nick Lichtenberg for Fortune. “Rather than arriving in crashing waves that transform a certain set of tasks at a time,” the researchers write, “progress typically resembles a rising tide, with widespread gains across many tasks simultaneously.”

According to the 2026 QS World University Rankings, MIT has been earned a No. 1 global ranking in 12 subject areas, including chemical engineering; chemistry; civil and structural engineering; computer science and information systems; data science and artificial intelligence; electrical and electronic engineering; engineering and technology; linguistics; materials science; mechanical, aeronautical, and manufacturing engineering; mathematics; and physics and astronomy, reports Michael T. Nietzel for Forbes.

Writing for Forbes, Senior Lecturer Guadalupe Hayes-Mota 08, SM '16, MBA '16 explores how businesses can best prepare for the rapid advancements underway in the field of neurotechnology. “I believe that one of the most important steps companies can take regarding this emerging technology is to act now, without waiting for regulatory clarity first,” writes Hayes-Mota. “Treat neural data as categorically sensitive from day one—not because you are forced to, but because you understand that operating this close to the human mind demands a higher threshold of trust than almost any technology before it.” 

Writing for the Financial Times, Prof. Danielle Li examines the risks for highly skilled workers whose expertise is used as training data for AI systems. “As workers, people should think about how to use AI to expand their skills: whether by building complementary capabilities or by finding ways to scale their expertise through AI systems,” Li writes. “As citizens, they should press for policies that give workers clearer rights over the data generated by their work and compensation for it.”