Speaking to Bloomberg’s Emily Chang and Selina Wang, Lecturer Luis Perez-Breva suggests that fear of AI stems from confusing it with automation. Perez-Breva explains that in his view, “we need to make better businesses that actually use this technology and AI to take advantage of the automation and create new jobs.”
Graduate student Joy Buolamwini is featured on NPR’s TED Radio Hour explaining the racial bias of facial recognition software and how these problems can be rectified. “The minimum thing we can do is actually check for the performance of these systems across groups that we already know have historically been disenfranchised,” says Buolanwini.
Wired reporter Sandy Ong highlights the work of Prof. Suranga Nanayakkara, who as a postdoc at MIT helped develop the Finger Reader, a device aimed at helping people with visual impairments read without the need for clunky hardware. The Finger Reader, “lets people read only what they’re pointing at, promising a relatively fuss-free experience, especially when out and about.”
Writing for Forbes, Charlie Fink writes about the AR in Action (ARiA) conference, which was held at the MIT Media Lab, and how the event focuses on new ideas rather than products. Fink notes that the conference, “is filled with the innovators and thinkers who are poised to create the next wave of groundbreaking products destined to disrupt the status quo.”
With virtual personal assistants becoming more commonplace, Research Affiliate Jimena Canales suggests in an NPR article that it may be time to reconsider our views of them. Despite knowing that AI is not real, “the boundary between the simulated and the real is as contested as it ever was,” she writes.
Neural networks developed by CSAIL researchers that can identify the contents of images, videos, and audio are the basis for a new system that has added background sound to Google Street View, writes Mark Wilson of Co.Design.
Tony Dokoupil of CBS This Morning visits MIT to learn more about how researchers are working on developing robots that will improve our daily lives. Dokoupil highlights how researchers are, “perfecting the material for a new breed of robot – one that's light and flexible,” adding that the researchers hope, “we'll be able to wear the robot like Tony Stark in ‘Iron Man’."
Hamza Shaban of The Washington Post speaks with Prof. Christian Catalini about how bitcoin fared in 2017. Catalini explains that, “the space is maturing, and that also means more pressure on bitcoin core developers and open-source developers to really get this technology and scale it.”
In an article for The Wall Street Journal, Greg Ip highlights a new study by Prof. Erik Brynjolfsson and graduate student Daniel Rock that examines why advances in technology have not yet led to increases in productivity. Ip writes that, “the authors blame these lags on the cost and time it takes for businesses to adapt to new technologies.”
Fortune reporter David Morris writes that MIT researchers have tricked an artificial intelligence system into thinking that a photo of a machine gun was a helicopter. Morris explains that, “the research points towards potential vulnerabilities in the systems behind technology like self-driving cars, automated security screening systems, or facial-recognition tools.”
In an article for The Wall Street Journal, Visiting Lecturer Irving Wladawsky-Berger spotlights MIT’s AI and the Future of Work Conference. Wladawsky-Berger writes that participants, “generally agreed that AI will have a major impact on jobs and the very nature of work. But, for the most part, they viewed AI as mostly augmenting rather than replacing human capabilities.”
Abigail Beall of New Scientist writes that MIT researchers have developed an algorithm that can trick an AI system, highlighting potential weaknesses in new image-recognition technologies used in everything from self-driving cars to facial recognition systems. “If a driverless car failed to spot a pedestrian or a security camera misidentified a gun the consequences could be incredibly serious.”
CSAIL researchers have tricked a machine-learning algorithm into misidentifying an object, reports Louise Matsakis for Wired. The research, “demonstrates that attackers could potentially create adversarial examples that can trip up commercial AI systems,” explains Matsakis.
Wired reporter Lauren Smiley speaks with a number of MIT experts about the growing use of technology as a home health care aid for the elderly. “I would always prefer the human touch over a robot,” explains Joseph Coughlin, director of the AgeLab. “But if there’s no human available, I would take high tech in lieu of high touch.”
Forbes reporter Laurie Winkless writes that MIT researchers have found that if drivers maintained fixed distances between the cars in front of and behind them they would be able to reduce traffic jams. “We humans tend to view the world in terms of what’s ahead of us, so it might seem counter-intuitive to look backwards,” explains Prof. Berthold Horn.