Wall Street Journal reporter Alicia Wallace spotlights MIT’s AI executive education course, which “aims to make a technologically complicated topic accessible by the pacing of the course and by providing examples of practical applications.”
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.
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.”
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.”
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.”
President Reif speaks with Gerry Baker of WSJ at Large about the impact of AI on the future of education and work. “Part of the goal of the [MIT Schwarzman] college is, as we educate people to use these [AI] tools, to educate them in a way that empowers human beings, not replaces human beings,” says Reif.
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.”