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.”
Graduate student Irene Chen speaks with WGBH’s Living Lab Radio about her work trying to reduce bias in health care algorithms. “The results that we’ve shown from healthcare algorithms are so powerful that we really do need to see how we could implement those carefully, safely, robustly and fairly,” she explains.
A new study by MIT researchers provides evidence that compiling massive anonymized datasets of people’s movement patterns can put their private data at risk, reports the Xinhua news agency. The researchers found “data containing ‘location stamps’ – information with geographical coordinates and time stamps – could be used to easily track the mobility trajectories of how people live and work.”
Prof. Aleksander Madry and graduate student Anish Athalye speak with BBC News reporter Linda Geddes about how AI systems can be tricked into seeing or hearing things that aren’t actually there. “People are looking at it as a potential security issue as these systems are increasingly being deployed in the real world,” Athalye explains.
In an article for Forbes, Andrew Raupp highlights a pilot program debuted by MIT last year that allows students the option to receive a tamper-free version of their diploma digitally using Bitcoin’s blockchain technology. Raupp writes that, “Unlike a paper diploma, which could be easily lost or falsified, blockchain ensures that this important piece of data is never lost.”
CSAIL researchers have developed a new technique to recreate paintings from a single photograph, reports John Biggs for TechCrunch. “The project uses machine learning to recreate the exact colors of each painting and then prints it using a high-end 3D printer that can output thousands of colors using half-toning,” Biggs explains.
Forbes reporter Samar Marwan speaks with Rana el Kaliouby, CEO and cofounder of the MIT startup Affectiva, about her work developing new technology that can read human facial expressions. Marwan explains that el Kaliouby and Prof. Rosalind Picard started developing the technology at MIT, “to focus on helping children on the autism spectrum better understand how other people were feeling.”
Forbes contributed Jennifer Kite-Powell writes about a system, called RePaint, developed by MIT researchers that uses AI and 3-D printing to replicate paintings. "We can picture RePaint being applied to restoration practice and education in museums so that greater numbers of people could be exposed to famous pieces of art beyond just the specific museums that house them," explains CSAIL mechanical engineer Mike Foshey.
Prof. Ethan Zuckerman, director of the MIT Center for Civic Media, speaks with Vox about the potential cognitive impact of using new digital technologies. “The interesting question is what are the real problems and how do we address them and make them better?” says Zuckerman. “How would you mitigate those harmful effects? What are the positive effects we want out of it?”
Fast Company reporter Jesus Diaz writes that CSAIL researchers have developed a new technique to replicate works of art. Diaz explains that the system “uses a combination of 10 different transparent inks, placed by a 3D printer and governed by a complex AI system that decides how to layer and mix those inks to match a painting’s original colors.”
BBC News reporter David Robson writes that MIT researchers have devised a simple test to help determine whether you are communicating with a chatbot or a human. Robson writes that the findings suggest “knowingly flouting a taboo and provoking, rather than simply describing, an emotion might be the most straightforward way of conveying your shared humanity.”
Speaking with Mark Jannot of The New York Times Magazine, Prof. Regina Barzilay explores how A.I. could be used to predict risk of certain diseases. “Imagine how it can change the game if these diseases, which are now diagnosed late, when they are largely uncurable, could be detected early — how many lives can be saved,” says Barzilay.
Ray Schroeder writes for Inside Higher Ed about Underlay, a knowledge base developed by MIT researchers to provide web users deeper citations of sources. Schroeder writes that Underlay is “a great example of what may become a new generation of search engines that is able to sort through the fact, opinion and misleading information of the ‘post-truth’ era.”
MIT researchers have developed a new system to detect contaminated food by scanning a product’s RFID tags, reports Devin Coldewey for TechCrunch. The system can “tell the difference between pure and melamine-contaminated baby formula, and between various adulterations of pure ethyl alcohol,” Coldewey explains.