In a Huffington Post article, Prof. David Autor lists the pressing long-and short-term issues that economists will focus on in 2017. Among the long-term concerns are the effects of artificial intelligence and machine learning, which could potentially disrupt “the value of products produced using manual labor in the developing world.”
CSAIL researchers have developed a wearable AI system that allows users to detect the tone of a conversation in real-time, reports Janet Burns for Forbes. Using two algorithms to analyze data, the researchers were able to “classify each five-second chunk of conversation as positive, neutral, or negative,” explains Burns.
The Media Lab will serve as one of the first anchor institutions for a new initiative, the Ethics and Governance of Artificial Intelligence Fund, which will “support research and development to make AI beneficial for humans,” reports Jordan Graham for the Boston Herald.
The Media Lab will serve as a founding institution for a new effort focused on advancing artificial intelligence research for the public good, reports April Glaser for CNBC. Research will focus on everything from investigating how” socially responsible artificially intelligent systems can be designed” to fostering “understanding of the complexities of artificial intelligence.”
CSAIL researchers have found that ride-sharing taxis controlled by a citywide computer system could decrease the number of cars on the road in New York City, reports Clive Cookson for the Financial Times. The researchers found that “3,000 four-passenger cars could satisfy 98 per cent of the city’s demand.”
Guardian reporter Nicola Davis spotlights Prof. Hugh Herr’s development of an autonomous exoskeleton device that could reduce the amount of energy humans use to walk. “We are taking a first principle approach, and joint by joint understanding deeply what has to be done scientifically and technologically to augment a human,” Herr explains.
MIT researchers have developed a technique to make big data more manageable, writes Kevin Murnane for Forbes. The technique creates "coresets" that can be used by data analysis tools “often applied in computer vision, natural language processing, neuroscience, weather prediction, recommendation systems and more.”
A new system developed by MIT researchers can predict how a scene will unfold, similar to how humans can visually imagine the future, reports Ed Gent for Scientific American. Graduate student Carl Vondrick explains that the system is “an encouraging development in suggesting that computer scientists can imbue machines with much more advanced situational understanding."
In an article for The New York Times, Joi Ito, director of the Media Lab, underscores the need to create new technologies that are not only smart, but also socially responsible. “Unless we embed ethical and moral grounding, technology meant to advance our well-being could, in fact, end up amplifying the worst aspects of our society,” Ito explains.
Steven Melendez of NBC News writes that a new system developed by CSAIL researchers can predict the future by examining a photograph. Grad student Carl Vondrick explains that the system’s ability to forecast normal behavior could allow it to be used for applications like self-driving cars.
MIT researchers have created a self-driving scooter that can be used both indoors and outdoors, reports Siyi Chen for Quartz. The scooter will “slow down or stop in order to calibrate a new route” when faced with an obstacle, explains Chen.
New Scientist reporter Victoria Turk writes that MIT researchers have developed a system that can predict the future based off of a still image. Turk writes that the system could enable “an AI assistant to recognize when someone is about to fall, or help a self-driving car foresee an accident.”
Reuters reporter Yiming Woo highlights a new autonomous scooter developed by researchers from MIT, the National University of Singapore and the Singapore-MIT Alliance for Research and Technology (SMART). The scooter should be able to help “improve mobility for all ages, cut down on the need for cars and also lower accident rates.”
In this WCVB segment, CSAIL postdocs Robert MacCurdy and Jeffrey Lipton explain their work developing a shock-absorbing material that could be used to help protect robots and smartphones, or in helmets. Liquid is used in the material to “absorb the energy and keep it inside,” Lipton explains.
Researchers at MIT have created an algorithm that transforms faces and popular landmarks into scarier versions with impressionistic, sketchy qualities, according to the BBC News. To help teach the algorithm about the concept of scariness, the researchers are asking people vote for the scariest images.