In a study of developers using GitHub Copilot, MIT researchers found AI shifted time away from teamwork and toward coding, writes Forbes’ Sarah Davis. “If AI reduces the need to ask colleagues for help and advice, workplaces become the mechanism for creating human interactions that promote connection and knowledge sharing,” writes Davis.
Prof. Emilio J. Castilla speaks to Forbes’ Lauren Russell about how bias can shape employee performance reviews. “Bias—whether explicit or unconscious—can potentially shape employment decisions at every stage, from who is interviewed and hired to who is promoted and who is rewarded for excellent performance,” says Castilla.
In an opinion piece for Fast Company, Hala Hanna, Executive Director of MIT Solve, outlines a blueprint for solving the world’s hardest problems in the next decade. “The last decade rewarded whoever could invent the best solution. The next one will belong to whoever can build the conditions for good solutions to survive, spread, and rewire the systems around them,” writes Hanna.
Research Scientist Giovanni Lavezzi speaks to Scientific American’s Jonathan O’Callaghan about managing the number of satellites in Earth’s orbit. “So far [the amount] seems manageable” through active coordination, says Lavezzi. “The problem is how much can we push.”
MIT researchers found the more data an AI model is trained on could complicate AI copyright, auditing, and governance, writes Computer World’s Taryn Plumb. “[S]ingle artworks by specific artists, or photographs of certain people, could be entirely removed from datasets, and the model could still reproduce that image or style,” writes Plumb. “Essentially, tangible connections are lost, and linking to specific data points responsible for generated samples is ‘practically impossible,’ or can even vanish, the researchers explained.”
The Register’s Thomas Claburn highlights a new study by MIT researchers that found large AI models can still reproduce an artist’s style, even when the artist’s work is removed from its training data, making attribution more difficult. “[G]iven the contemporary adoption of these models for creative and commercial purposes, attributability also carries ethical, policy, financial, and legal implications,” the researchers note.
The New York Times’ Dana Goldstein highlights an MIT study that found individuals who used AI for writing assistance recorded lower brain activity than those who worked without LLMs. “The writers who used AI struggled to remember what, exactly, they had written, and felt little ownership over their work,” writes Goldstein. “The findings join a growing body of research suggesting that frequent AI use can degrade critical thinking.”
Prof. Max Tegmark joins Steve Clemons, host of Al Jazeerah’s, “The Bottom Line,” to discuss regulating AI. “Normally with technology we have a problem we want to solve: cure cancer, be able to get faster from point A to point B, and then we develop technology to meet those needs, to solve those problems—and that’s how we should deal with AI also,” says Tegmark. “We should look at what we would like to have accomplished in our society and then companies can sell products that solve those problems without causing a bunch of harm.”
Prof. Kristin Forbes speaks to Bloomberg’s Daniel Moss about how governments can prepare to restore inflation targets in the event of a prolonged miss and highlights the value of providing a clear timeline. “You don’t want to be responsible for hitting a target each month when a global shock will veer you off course,” says Forbes. “It’s about the direction of inflation, the path.”
Alumni Erin Dawicki MBA ‘24 and Michelle Ewy MBA ‘24 speak to Boston 25 about developing LymeAlert, the first at-home test kit to detect Lyme disease in ticks. “The faster you treat it [Lyme disease], the way easier it is to treat and have complete resolution of symptoms for a lot of people,” says Dawicki. “But the second challenge is the current diagnostics we have miss 64 to 78 percent of early-stage cases.”
Prof. Daron Acemoglu discusses how issues with AI and social media inform his new book, “What Happened to Liberal Democracy?” in an article by Fortune’s Nick Lichtenberg. “We live in an environment that’s been partly shaped by social media, and there is a tendency to escalate everything, because that gets attention,” says Acemoglu. “Politics is like that. The other topic like that, unfortunately, is AI.”
VICE’s Luis Prada spotlights Prof. Tristan Brown’s discovery that a Chinese tea label on display as a Boston Tea Party artifact at Boston’s Old South Meeting House was actually created during the 19th century. After Brown translated the label from Cantonese, it “revealed an American name, 'Smith, Archer,' as it identified Smith, Archer and Co., a New York trading firm active in East Asia during the 1860s and 1870s,” writes Prada.
By analyzing brain scans from 772 people, MIT researchers have identified 17 additional language-responsive regions in the brain, reports The Dallas Express (DX). “For decades, scientists have focused on regions such as Broca’s area and areas of the left frontal and temporal lobes as the brain’s primary language-processing centers,” writes DX. “The new study found that language-responsive regions are also located in other parts of the brain, including the cerebellum, hippocampus, amygdala, medial frontal cortex, and temporal lobe.”
MIT researchers found that contrary to popular assumptions, lower birth rates have raised rather than lowered the Gross Domestic Product globally, writes The Dispatch’s Eli Kronenberg. “Across the board, we found that these lower birth rates were leading to a faster pace of technological adoption and progress,” says graduate student Keelan Beirne, a co-author on the paper.
Gizmodo’s Gayoung Lee describes how Prof. Tristan Brown found that a tea chest label, on originally thought to be an artifact of the Boston Tea Party, actually originated from 19th century trade between China and America. “The discovery doesn’t diminish the label; it replaces one story with a richer one,” says Brown. “That broader story, of how revolutionary memory gets made through objects whose own histories stretch across the globe, is what I hope the paper contributes to ongoing conversations about history, material culture, and American identity.”