Prof. Joi Ito, director of the Media Lab, writes for Wired about how AI systems can help perpetuate longstanding discriminatory practices. “By merely relying on historical data and current definitions of fairness, we will lock in the accumulated unfairnesses of the past,” argues Ito, “and our algorithms and the products they support will always trail the norms.”
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.
MIT researchers have developed a robot that can learn how to successfully play Jenga, reports Brian Heater for TechCrunch. “The robot has to learn in the real world, by interacting with the real Jenga tower,” explains Prof. Alberto Rodriguez. “The key challenge is to learn from a relatively small number of experiments by exploiting common sense about objects and physics.”
Gizmodo reporter Andrew Liszewski writes that MIT researchers have developed a robot that can play Jenga using visual and physical cues. The ability to feel “facilitated the robot’s ability to learn how to play all on its own, both in terms of finding a block that was loose enough to remove, and repositioning it on the top of the tower without upsetting the delicate balance.”
MIT researchers have developed a robot that can play Jenga by combining interactive perception and manipulations, reports Mattha Busby for The Guardian. “In what marks significant progress for robotic manipulation of real-world objects, a Jenga-playing machine can learn the complex physics involved in withdrawing wooden blocks from a tower through physical trial and error,” Busby explains.
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.
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.”
In an article for The Wall Street Journal, Benjamin Powers highlights Affectiva and Koko, two MIT startups developing AI systems that respond to human emotions.