Technology and society

Prof. Tod Machover’s composition “already and not yet,” was performed by members of the Boston Symphony Orchestra along with an AI system that listens to musicians and adds improvisations, reports A.Z. Madonna for The Boston Globe. “Music is something that’s meant to plumb your soul, and have you discover things,” says Machover. The composition is “about my view of where we are, how to take a deep breath and figure out, gather strength to go somewhere else, and then what a possible future of democracy might be.”  

Prof. Tod Machover speaks to WBUR’s Andrea Shea about “already and not yet” an interactive composition he wrote for the Boston Symphony Orchestra and an AI instrument developed by Machover and graduate student Manaswi Mishra. Machover explains that they designed the AI tools so that they’re “always going to make a kind of variation, a coloration, an extension of what the musician's playing – but exactly what it's going to do I do not have complete control over. I'm trying to show that it [AI] can be integrated in a beautiful, provocative and interesting way in a serious piece of music.”  

Prof. Daron Acemoglu joins “The Claman Countdown” on Fox Business to discuss the possibility that largescale deployment of AI could triple unemployment within the next decade. “There is so much uncertainty about AI,” says Acemoglu. “It’s very difficult to know exactly when we’re going to see the productivity gains, which will come, and when we’re going to see job losses, and whether we’ll actually see some job creation as well. But on the current path where AI is being prepared and developed as a labor replacing technology, I would be very worried that within the next ten years we’ll see a lot of jobs disappear.”  

For Manufacturing Dive, reporter Nathan Owens spotlights MIT’s Technologist Advanced Manufacturing Program (TechAMP), a 12-mong-long program that combines online instruction with hands-on lab work to bridge the gap between technical engineering and management skills, designed for working technicians or operators. “Students gain foundational leadership, process control and systems thinking skills,” notes Owens. TechAMP has “really shown me how to communicate more, communicate problems more, communicate solutions more,” says Brian Coppenrath, who completed the program.  

Principal Research Scientist Deepjyoti Deka speaks to MassLive’s Tréa Lavery about the possibility of large data centers being located in greater Boston. “Anything, mostly, that you are using the computer for, that you are getting some information from, is housed in a data center,” says Deka. “When you talk about data centers in greater Boston, I doubt if we have any hyperscale, because there would need to be a gigantic factory that you could observe from a distance. But there are small ones.” 

Postdoctoral Associate Iman YeckehZaare speaks to El País reporter Jordi Pérez Colomé about his research on RentAHuman, a platform that allows AI agents to hire people to do physical labor. “RentAHuman has shown that many people are willing to sign up to be hired by AI agents. What it still hasn’t shown is that many AI agents are doing the hiring,” says YeckehZaare. “Listings posted by agents will increase as AI agents become capable of acting and paying on their own.”  

Financial Times reporter Clive Cookson details how the late Margaret Hamilton engineered code that would play a crucial role in achieving the first moon landing, at MIT’s Instrumentation Lab. When Apollo 11’s onboard computer flashed alarms minutes from landing on the moon, “Hamilton and colleagues had engineered the software to dump non-essential background tasks under those circumstances and prioritize procedures needed for the landing,” writes Cookson. “NASA controllers in Houston trusted the software, so they decided not to abort the mission, allowing Neil Armstrong and Buzz Aldrin to touch down safely in their Eagle module.”  

Fast Company’s Adele Peters highlights Firma Power, a clean energy developer co-founded by MIT alumni aimed at working with data centers to use clean alternatives to gas power. “We started the company with the hypothesis that despite the fact that 98% of what’s in the queue is wind, solar and storage, that’s not getting tapped as the default path to power for large loads—so there’s got to be some market frictions and barriers there,” says Jesse Jenkins SM ’14, PhD ’18.  

Prof. Emilio Castilla discusses the factors companies must consider when deploying AI to help in the hiring process, in an article by USA Today’s Greta Reich. “We should evaluate not only whether the algorithm predicts historical hiring decisions, but whether it helps identify candidates who subsequently perform well in the job,” writes Castilla. “The most exciting possibility is not simply that AI might help us find the best talent more efficiently. It is that AI might help us recognize talent that our traditional hiring practices have systematically overlooked.”  

Research Affiliate Paul Kedrosky joins The New York Times’ “The Ezra Klein Show” to discuss how the development of AI is creating an economic bubble, where asset prices are detached from economic reality. “We’re building it [AI] out like we were the railroads, like we were electrification, like we were the canals, like we were the interstate highways. And every one of those moments has led to overbuild,” says Kedrosky. “The reality is we’ve never seen a general-purpose technology that had such broad applicability, was adopted so quickly and was repricing labor at the same time.”  

Testing 1,000 synthetically generated client profiles against AI chatbots for investment advice, Prof. Andrew Lo and Research Affiliate Jillian Ross identified “heuristic collapse,” where chatbots based their recommendations almost entirely on self-reported risk tolerance, while ignoring income and other variables, writes Damilola Esebame for The Street. “Lo has recommended that investors use chatbots for orientation, leveraging them to frame questions, map out available options, and prepare for conversations with a human advisor rather than treating the output as a finished plan,” notes Esebame. 

Maxime Cohen PhD ‘15 speaks to Forbes’ Karl Moore about his latest book “Pricing in the Age of AI,” that explores how AI is transforming pricing decisions for businesses, consumers and society. “We may be entering an era of agent-to-agent commerce, in which AI systems negotiate directly with one another on behalf of consumers and businesses,” says Cohen. “This could fundamentally reshape how prices are determined and how transactions take place.” 

Prof. Daron Acemoglu joins CNBC’s “Closing Bell” to discuss how AI could cause mass job displacement due to companies deploying rapidly advancing technologies. “AI’s capabilities are real and powerful, but human jobs are also complex. I don’t think you want AI to take over air traffic controller jobs right now; you don’t want AI to do CEO jobs,” says Acemoglu. “What we are seeing when these models escape their sandboxes and create havoc—it's not that they are necessarily super intelligent, it is that they don’t have judgement and they are optimized for certain narrow metrics and when you let them loose, they are going to do lots of unforeseeable things. You don’t want that in many jobs.”  

Writing for Nature, Deputy Editorial Director Maia Weinstock honors the life and legacy of the late Margaret Hamilton, a pioneer of the software engineering field, who, at MIT’s Instrumentation Lab, led the team that wrote and tested software for the Apollo Guidance Computer onboard Apollo 11. Hamilton’s story “was also my inspiration for one of the vignettes in a Lego set that I created in 2016, featuring Hamilton and several other women in NASA history,” writes Weinstock. “She continued work at [her Universal Systems Language company] Hamilton Technologies well into her 80s, never failing to inspire me and countless others with her tenacity, humour, warmth and childlike wonder.”

Research led by Principal Research Scientist Neil Thompson suggests that AI is likely to be upend theoretical scientific fields within a few years, writes Wired’s Will Knight. “As with math, Thompson says, we should expect advances in other areas to have both positive and negative effects,” writes Knight. “He notes that theoretical advances sometimes drive practical advances in science and suggests that greater use of AI may mean that more progress happens this way.”