Artificial intelligence

Prof. Daniela Rus, director of CSAIL, speaks with Boston Globe reporter Evan Sellinger about her new book, “The Heart and the Chip: Our Bright Future With Robots,” in which she makes the case that in the future robots and humans will be able to team up to create a better world. “I want to highlight that machines don’t have to compete with humans, because we each have different strengths. Humans have wisdom. Machines have speed, can process large numbers, and can do many dull, dirty, and dangerous tasks,” Rus explains. “I see robots as helpers for our jobs. They’ll take on the routine, repetitive tasks, ensuring human workers focus on more complex and meaningful work.”

Prof. Stuart Madnick speaks with CNBC reporter Kevin Williams about how the rise of generative AI technologies could lead to cyberattacks on physical infrastructure. “If you cause a power plant to stop from a typical cyberattack, it will be back up and online pretty quickly,” Madnick explains, “but if hackers cause it to explode or burn down, you are not back online a day or two later; it will be weeks and months because a lot of the parts in these specialized systems are custom made.”

Senior Lecturer Guadalupe Hayes-Mota writes for Forbes about the ways AI is reshaping drug development. “In the next three years, we can anticipate a more streamlined, efficient and cost-effective drug development process, ultimately leading to faster access to life-saving drugs for patients worldwide,” Hayes-Mota writes. “This is not just an evolution; it is a revolution in healthcare powered by the intelligence of machines.”

Researchers at MIT and elsewhere have developed a machine-learning model that can identify which drugs should not be taken together, reports Politico. “The researchers built a model to measure how intestinal tissue absorbed certain commonly used drugs,” they write. “They then trained a machine-learning algorithm based on their new data and existing drug databases, teaching the new algorithm to predict which drugs would interact with which transporter proteins.”

Quartz reporter Michelle Cheng spotlights a working paper by Prof. David Autor which shows that “AI could enable more workers to perform higher-stakes, decision-making tasks that are currently relegated to highly-educated workers such as doctors and lawyers.” As Autor explains, “in essence, AI used well can assist with restoring the middle-skill, middle-class heart of the US labor market that has been hollowed out by automation and globalization.”

MIT researchers have developed a new technique “that could allow most large language models (LLMs) like ChatGPT to retain memory and boost performance,” reports Tony Ho Tran for the Daily Beast. “The process is called StreamingLLM and it allows for chatbots to perform optimally even after a conversation goes on for more than 4 million words,” explains Tran.

In an article co-authored for The Economist, Senior Lecturer Donald Sull explores the impact of artificial intelligence and large language models (LLMs) on corporate company culture. “Leaders who do adopt AI for cultural insights can use these to make their employees happier, lower the odds of reputational disasters and, ultimately, boost their profits,” writes Sull. “Measurement is not the only piece of the ‘successful culture’ puzzle, but it is a crucial one. Culture has always been an enigma at the heart of organizational performance: undoubtedly important, but inscrutable. With AI, meaningful progress can be made in deciphering it.”

Prof. David Rand speaks with VOA News about the potential impact of adding watermarks to AI generated materials. “My concern is if you label as AI-generated, everything that’s AI-generated regardless of whether it’s misleading or not, people essentially are going to stop really paying attention to it,” says Rand.

Researchers at MIT and elsewhere have found that while AI systems could help doctors come to the right diagnosis more often, the diagnostic gains aren’t always distributed evenly, with more improvements tied to patients with lighter skin, report Daniel Payne, Erin Schumaker, and Ruth Reader for Politico. “AI could be a powerful tool to improve care and potentially offer providers a check on their blindspots," they write. "But that doesn’t mean AI will reduce bias. In fact, the study suggests, AI could cause greater disparities in care.”

Corey Jaskolski SM '02 founded Synthetaic, a software company that uses AI to “automate the analysis of large datasets, namely satellite imagery and video, not containing labels,” reports Kyle Wiggers for TechCrunch. “Synthetaic’s technology offers a transformative approach to AI model training and creation, addressing the critical needs of technical decision makers,” says Jaskolski.

Joy Buolamwini PhD '22 speaks with MSNBC reporter Daniela Pierre-Bravo about her new book, Unmasking AI: My Mission To Protect What is Human in a World of Machines, which explores the intersection of AI development and the, “dangers of bias in its algorithmic systems.” Buolamwini emphasizes that: “We need legislation — at the federal level — because the legislation then puts in the guard rails for the tech companies. And also, we need to think about AI governance globally. I do think that all of our stories matter. When you share your experience with AI or your questions about it, you encourage other people to share their stories.”

Researchers from MIT and elsewhere have developed an AI model that is capable of identifying 3 ½ times more people who are at high-risk for developing pancreatic cancer than current standards, reports Felice J. Freyer for The Boston Globe. “This work has the potential to enlarge the group of pancreatic cancer patients who can benefit from screening from 10 percent to 35 percent,” explains Freyer. “The group hopes its model will eventually help detect risk of other hard-to-find cancers, like ovarian.”

In a new study examining the potential impact of AI on jobs that employ computer vision, MIT researchers found, “a vast majority of jobs previously identified as vulnerable to AI are not economically beneficial for employers to automate at this time,” reports Catherine Thorbecke for CNN. “In many cases, humans are the more cost-effective way, and a more economically attractive way, to do work right now,” says Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL. “What we’re seeing is that while there is a lot of potential for AI to replace tasks, it’s not going to happen immediately.”

A new working paper by MIT researchers finds that artificial intelligence is not currently a cost-effective replacement in jobs where computer vision is employed, reports Saritha Rai for Bloomberg. “Our study examines the usage of computer vision across the economy, examining its applicability to each occupation across nearly every industry and sector,” explains Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL. “We show that there will be more automation in retail and healthcare, and less in areas like construction, mining or real estate.”

A new working paper by MIT researchers focuses on whether human work, including vision tasks, are worth replacing with AI computer vision, reports Jeremy Hsu for New Scientist. “There are lots of tasks that you can imagine AI applying to, but actually cost-wise you just wouldn’t want to do it,” says Research Scientist Neil Thompson, director of the FutureTech Research Project at CSAIL.