Machine learning

WHDH-TV spotlights how research engineer Dane Kouttron has created a self-driving snow blower “powered by a lithium battery that can keep the robot running for four hours continuously.”

CBS Boston highlights how research engineer Dane Kouttron has developed a snow blower that can be operated remotely. Kouttron explains that the idea behind the machine is to, “sit out with your cup of tea and remotely pilot your snow moving machine from the comfort of your own home.”

New York Times reporter Janet Morrissey spotlights Prof. Regina Barzilay and Prof. Dina Katabi’s work developing new AI systems aimed at improving health care. “It’s absolutely the future; it’s even the present,” says Barzilay. “The question is how fast do we adopt it?”

In an article for the Financial Times, President L. Rafael Reif calls for government investment in AI research, and educational offerings that integrate the study of AI into every discipline. “Those nations and institutions which act now to help shape the future of AI will help shape the future for us all,” writes Reif.

Graduate student Joy Buolamwini writes for TIME about the need to tackle gender and racial bias in AI systems. “By working to reduce the exclusion overhead and enabling marginalized communities to engage in the development and governance of AI, we can work toward creating systems that embrace full spectrum inclusion,” writes Buolamwini.

In this video, graduate student Nima Fazeli speaks with the BBC News about his work developing a robot that uses sensors and cameras to learn how to play Jenga. “It’s using these techniques from AI and machine learning to be able to predict the future of its actions and decide what is the next best move,” explains Fazeli.

CBS This Morning spotlights how MIT researchers have developed a new robot that can successfully play Jenga. “It is an automated system that has had a learning period first,” explains Prof. Alberto Rodriguez. “It uses the information from the camera and the force sensor to interpret its interactions with the Jenga tower.”

MIT researchers have developed a robot that can play Jenga. “It "learns" whether to remove a specific block in real time, using visual and tactile feedback, in much the same way as a human player would switch blocks if the tower started to wobble,” reports Jack Guy for CNN.

A new robot developed by MIT researchers uses AI and sensors to play the game of Jenga, reports Rob Verger for Popular Science. “It decides on its own which block to push, [and] which blocks to probe; it decides on its own how to extract them; and it decides on its own when it’s a good idea to keep extracting them, or to move to another one,” says Prof. Alberto Rodriguez.

Wired reporter Matt Simon writes that MIT researchers have engineered a robot that can teach itself to play the game of Jenga. As Simon explains, the development is a “big step in the daunting quest to get robots to manipulate objects in the real world.”

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.