Research assistant Blakeley Payne speaks with Wall Street Journal reporter Michelle Ma about her work developing a curriculum that teaches kids about the ethics of AI. “You have to integrate the ethics piece at every point, because you never want to fall into the trap of presenting an AI system as like a mathematical equation,” explains Payne, “with the authority of a mathematical equation.”
New Yorker reporter Adam Gopnick visits the MIT AgeLab to explore how researchers are developing new technologies aimed at improving the quality of life for people as they age. “Now that we’re living longer, how do we plan for what we’re going to do?” says AgeLab Director Joseph Coughlin of the lab’s mission.
Boston Globe reporter Ben Volin speaks with graduate student John Urschel about his new book “Mind and Matter: A Life in Math and Football.” “I love solving sort of interesting and tough problems that have to do with our world in some way,” says Urschel of his dreams for after he graduates from MIT. “And I also love teaching.”
A study by MIT researchers examines the historical impact of technology on the labor market in an attempt to better understand the potential effect of AI systems, reports Adi Gaskell for Forbes. “The authors propose a number of solutions for improving data on the skills required in the workforce today, and from that the potential for AI to automate or augment those skills,” Gaskell explains.
Newsweek reporter Aristos Georgiou writes that MIT researchers have found that explosions of our universe’s first stars sent the first heavy elements into neighboring galaxies. “These elements provided the raw material for the formation of a second generation of stars, some of which survive to this day,” Georgiou explains.
Writing for The Wall Street Journal, senior lecturer Hal Gregersen examines how managers can ask questions that can help prompt creative thinking. “Bosses should reconceive what their primary job is,” writes Gregersen. “They aren’t there to come up with today’s best answers, or even just to get their teams to come up with them. Their job is to build their organization’s capacity for constant innovation.”
Blue Origin unveiled plans to send a spaceship to the moon, reports Seth Borenstein for the AP. Prof. Dava Newman explained that the newly designed rocket engine is what makes Blue Origin’s attempt to reach the moon unique. “It’s for real,” said Newman.
The Economist highlights a study co-authored by research affiliate Ashley Nunes that examines the economic feasibility of driverless taxis. The researchers found that riding in a driverless taxi is more expensive per mile than driving your own car.
Writing for Nature, research affiliate Ashley Nunes cautions that the role of driverless cars in society must be closely investigated before they are integrated into mainstream modes of transportation. “Driverless-car technology might have the potential to improve public health and save lives,” Nunes writes, “but if those who most need it don’t have access, whose lives would we actually be saving?”
WCVB-TV’s Jennifer Eagan reports that researchers from MIT and MGH have developed a deep learning model that can predict a patient’s risk of developing breast cancer in the future from a mammogram image. Prof. Regina Barzilay explains that the model “can look at lots of pixels and variations of the pixels and capture very subtle patterns.”
Fast Company reporter Michael Grothaus writes that CSAIL researchers have developed a deep learning model that could predict whether a woman might develop breast cancer. The system “could accurately predict about 31% of all cancer patients in a high-risk category,” Grothaus explains, which is “significantly better than traditional ways of predicting breast cancer risks.”
A study by MIT researchers examining adversarial images finds that AI systems pick up on tiny details in images that are imperceptible to the human eye, which can lead to misidentification of objects, reports Louise Matsakis for Wired. “It’s not something that the model is doing weird, it’s just that you don’t see these things that are really predictive,” says graduate student Shibani Santurkar.
Writing for The Wall Street Journal, Edward Glaeser spotlights a new book from Profs. Johnathan Gruber and Simon Johnson titled, “Jump-Starting America.” Glaeser writes that Gruber and Johnson have “produced a superbly argued case for public and private investment in education and research.”
Researchers at MIT have found that adversarial examples, a kind of optical illusion for AI that makes the system incorrectly identify an image, may not actually impact AI in the ways computer scientists have previously thought. “When algorithms fall for an adversarial example, they’re not hallucinating—they’re seeing something that people don’t,” Louise Matsakis writes for Wired.
Boston Globe reporter Laura Krantz visits MIT’s Haystack Observatory to learn more about the place where scientists played a key role in developing the first image of a black hole and created a supercomputer used to compile the image. Krantz notes that researchers at Haystack also study the Earth, not-far-away planets, and stars, and are creating devices to track the decay of icebergs.