Artificial intelligence

Metropolis reporter Anthony Paletta details how MIT’s inaugural Future Fest “brought together visionary leaders across design, technology, and art to address the world’s most pressing problems,” and also featured the public debut of the redesigned Metropolitan Warehouse. The festival featured discussions, exhibits and demonstrations on architecture, design and technology, including a new technique that utilizes knitted fibers as a flexible formwork for concrete, a discussion on how AI could be used to increase sustainability in construction and exploration of how “reef legos” can rebuild beaches and combat costal erosion. “There are no shortage of things going wrong in the world, and others likely to follow,” writes Paletta, “but MIT’s Future Fest offered reassuring proof that we’ve not run out of means to address these problems.” 

Flapping Airplanes, a startup co-founded by Benjamin Spector ’22, MEng ’22, has developed a framework for AI models to run efficiently while being trained on less data and in a single graphics processing unit (GPU), writes Julie Bort for TechCrunch. The framework “can run a task that spends most of its time waiting for data to be fetched alongside one that spends most of its time doing math, so the chip is rarely sitting idle,” notes Bort. “The premise is that AI has barely scratched the surface of what GPUs can do, and they believe it can create intelligent systems ‘without ingesting half the internet.’”  

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.”  

Eka Robotics, a startup cofounded by Prof. Pulkit Agrawal, has developed a robot with  a force-sensitive gripper that can “pick up about 1,500 objects that weigh up to 1 kg in an hour, compared to about 600 for a human” with 95% accuracy, reports Tim Fernholz for TechCrunch.  “We are starting off being very pragmatic, and saying here are two verticals in pick, arrange, place, and wire handling, let’s make them be home runs,” says Agrawal. “Once we have made home runs on them, the sky is the limit in how much we can do with the approach we are developing.” 

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.  

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.”  

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. Jacob Andreas speaks with CNN’s Lisa Eadicicco about deciphering the chain-of-thought behind complex AI neural networks. “I think we’re still very far from being able to claim that we have any sort of fine-grained understanding of how the model is actually arriving at a solution,” says Andreas.  

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.”  

In The Boston Globe’s “Starting Point Newsletter,” reporter Anna Kusmer features Prof. Sherry Turkle’s insights from her latest book “Artificial Intimacy: Who We Become When We Talk to Machines,” including the risks that AI companionship poses to school-aged children. “Children are bringing the world inside; they’re bringing the people around them inside them to create an inner life,” says Turkle. “And when you talk to a chatbot, there is nothing to bring inside. There is no caring person.” 

In an interview with Wired’s Steven Levy, Prof. Sherry Turkle discusses how she witnessed chatbots with human-like features becoming “dangerously enmeshed” with people, during research for her latest book “Artificial Intimacy: Who We Become When We Talk to Machines.” “In every serious interview I do, people invoke this myth about practice—that you use chatbots to practice for talking to your boss, your lover, your teacher,” says Turkle. “But when you’re bathing in the warm soup of total acceptance, talking to chatbots becomes the endgame.” 

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.”