Brian Heater for TechCrunch covers how researchers are creating a system that will allow robots to develop motor skills and process abstract concepts. “With this system, the robots can perform complex tasks without getting bogged down in the minutia required to complete them,” Heater writes.
MIT researchers have designed a new chip to enhance the functionality of neural networks while simultaneously reducing the consumption of power, writes Darrell Etherington of TechCrunch. “The basic concept involves simplifying the chip design so that shuttling of data between different processors on the same chip is taken out of the equation,” he explains.
Graduate student Joy Buolamwini tested three different face-recognition systems and found that the accuracy is best when the subject is a lighter skinned man, reports Timothy Revell for New Scientist. With facial recognition software being used by police to identify suspects, “this means inaccuracies could have consequences, such as systematically ingraining biases in police stop and searches,” writes Revell.
Molly Wood at Marketplace speaks with Media Lab graduate student Joy Buolamwini about the findings of her recent research, which examined widespread bias in AI-supported facial recognition programs. “At the end of the day, data reflects our history, and our history has been very biased to date,” Buolamwini said.
Recent research from graduate student Joy Buolamwini shows that facial recognition programs, which are increasingly being used by law enforcement, are failing to identify non-white faces. “When these systems can’t recognize darker faces with as much accuracy as lighter faces, there’s a higher likelihood that innocent people will be targeted by law enforcement,” writes Katharine Schwab for Co. Design.
Writing for Gizmodo, Sidney Fussell explains that a new Media Lab study finds facial-recognition software is most accurate when identifying men with lighter skin and least accurate for women with darker skin. The software analyzed by graduate student Joy Buolamwini “misidentified the gender of dark-skinned females 35 percent of the time,” explains Fussell.
A study co-authored by MIT graduate student Joy Buolamwini finds that facial-recognition software is less accurate when identifying darker skin tones, especially those of women, writes Josh Horwitz of Quartz. According to the study, these errors could cause AI services to “treat individuals differently based on factors such as skin color or gender,” explains Horwitz.
Natasha Singer of The New York Times writes about a joint course from MIT and Harvard to teach the ethics and regulation of artificial intelligence. “As we start to see things, like autonomous vehicles, that clearly have the ability to save people but also cause harm, I think that people are scrambling to build a system of ethics,” says Joi Ito, director of the MIT Media Lab.
Steve Lohr writes for the New York Times about graduate student Joy Buolamwini’s findings on the biases of artificial intelligence in facial recognition. “You can’t have ethical A.I. that’s not inclusive,” Buolamwini said. “And whoever is creating the technology is setting the standards.”
Profs. James DiCarlo and Daniela Rus talk to the BBC’s Click about MIT Intelligence Quest. As they explain, the program aims to encourage discoveries in the areas of natural and artificial intelligence.
MIT spinout Lightmatter, which makes photonic chips that allow AI to perform calculations at the speed of light, has secured $11 million in funding, reports Devin Coldewey of TechCrunch.
When computing, the chip solves problems “by running a beam of light through a gauntlet of tiny, configurable lenses and sensors” instead of in a series of basic operations, explains Coldewey.
As noted by the Associated Press, former Google CEO Eric Schmidt will be joining MIT as an innovation fellow beginning this Spring, where he will advise the recently launched MIT Intelligence Quest.
In an article for Wired, Prof. James J. DiCarlo explains how artificial intelligence can transcend algorithm-based decision making by reverse-engineering the brain. “Armed with an engineering description of the brain, scientists will see new ways to repair, educate, and augment our own minds,” writes DiCarlo.
As Steve Rosenbush notes in the Wall Street Journal, MIT Intelligence Quest hopes to answer two questions: “How does human intelligence work, in engineering terms? And how can we use that deep grasp of human intelligence to build wiser and more useful machines?” explains President Reif.
Dean Anantha Chandrakasan speaks with Kristin Toussaint of Metro about MIT Intelligence Quest. “When you bring together researchers from different disciplines, they end up collaborating and creating something very new that they individually couldn't have created,” said Chandrakasan.