Wall Street Journal reporter Sara Castellanos spotlights how researchers from MIT and Microsoft participated in a two-day hackathon with curators and digital experts from the Metropolitan Museum of Art. Together, they aimed to develop new AI technologies that could deliver new and personalized experiences “with a view toward deepening user engagement.”
Reporting for Scientific American’s “60-Second Science” podcast, Christopher Intagliata explores how MIT developed a device, called a rectenna, that can capture energy from Wi-Fi signals and convert them into electricity. The scientists “envision a smart city where buildings, bridges and highways are studded with tiny sensors to monitor their structural health, each sensor with its own rectenna,” Intagliata explains.
Scientific American reporter Jeff Hecht writes that MIT researchers developed a new flexible material that can harvest energy from wireless signals. “The future of electronics is bringing intelligence to every single object from our clothes to our desks and to our infrastructure,” explains Prof. Tomás Palacios.
MIT researchers developed a super-thin, bendy material that converts WiFi signals into electricity, reports Ian Sample for The Guardian. “In the future, everything is going to be covered with electronic systems and sensors. The question is going to be how do we power them,” says Prof. Tomás Palacios. “This is the missing building block that we need.”
Associated Press reporter Tali Arbel writes that MIT researchers have found that Amazon’s facial detection technology often misidentifies women and women with darker skin. Arbel writes that the study, “warns of the potential of abuse and threats to privacy and civil liberties from facial-detection technology.”
A new study by Media Lab researchers finds that Amazon’s Rekognition facial recognition system performed more accurately when identifying lighter-skinned faces, reports Drew Harrell for The Washington Post. The system “performed flawlessly in predicting the gender of lighter-skinned men,” writes Harrell, “but misidentified the gender of darker-skinned women in roughly 30 percent of their tests.”
Verge reporter James Vincent writes that Media Lab researchers have found that the facial recognition system Rekognition performed worse at identifying an individual’s gender if they were female or dark-skinned. In experiments, the researchers found that the system “mistook women for men 19 percent of the time and mistook darker-skinned women for men 31 percent of the time,” Vincent explains.
MIT researchers have found that the Rekognition facial recognition system has more difficulty identifying the gender of female and darker-skinned faces than similar services, reports Natasha Singer for The New York Times. Graduate student Joy Buolamwini said “the results of her studies raised fundamental questions for society about whether facial technology should not be used in certain situations,” writes Singer.
New York Times reporter Steve Lohr writes about the MIT AI Policy Conference, which examined how society, industry and governments should manage the policy questions surrounding the evolution of AI technologies. “If you want people to trust this stuff, government has to play a role,” says CSAIL principal research scientist Daniel Weitzner.
TechCrunch reporter John Biggs writes that MIT researchers have developed a new system that allows users to reverse-engineer complex items by deconstructing objects and turning them into 3-D models. Biggs writes that the system is a “surprisingly cool way to begin hacking hardware in order to understand it’s shape, volume and stability.”
Writing for Wired, Prof. Carlo Ratti predicts that in 2019 researchers will develop new methods for allowing people to use the internet in less intrusive ways. “The internet of things will continue to grow, and we will work out more ways to develop ‘things’ that allow us to enjoy the internet without being overwhelmed by it,” writes Ratti.
In a piece about the growing field of origami, The Economist highlights Prof. Erik Demaine’s work proving that “any straight-sided figure—an octagon, a cityscape silhouette or a blocky Bart Simpson—can be extracted with exactly one straight cut if you fold the paper up the right way first.”
Provost Martin Schmidt and SHASS Dean Melissa Nobles speak with Wall Street Journal reporter Sara Castellanos about MIT’s efforts to advance the study of AI and its ethical and societal implications through the MIT Stephen A. Schwarzman College of Computing. Schmidt says this work “requires a deep partnership between the technologists and the humanists.”
Boston Globe reporter Jessie Scanlon spotlights Prof. Regina Barzilay’s work developing machine learning systems that can identify patients at risk of developing breast cancer. Barzilay is creating “software that aims to teach a computer to analyze mammogram images more effectively than the human eye can and to catch signs of cancer in its earliest phases.”
MIT researchers have found that it’s easy to reidentify anonymized data compiled in massive datasets, reports Kelsey Campbell-Dollaghan for Fast Company. The findings show that urban planners, tech companies and designers, “who stand to learn so much from these big urban datasets,” writes Campbell-Dollaghan, “need to be careful about whether all that data could be combined to deanonymize it.”