President Reif spoke with Abraham González of El Financiero about the rapid advance of technology. “Machine learning will not replace us, on the contrary, it will help us. Just as computers help us get the job done today and just as cars help us get from one place to another,” explains Reif.
CSAIL researchers have developed software that allows users to design and virtually test drones, writes Alex Davies for Wired. Graduate student Tao Du explains that the software can help users “explore and try different shapes and different controllers.”
A new paper co-authored by Prof. Daron Acemoglu examines the impact of automation on the U.S. job market, according to The Economist. The researchers found that “between 1990 and 2007, each industrial robot added per thousand workers reduced employment in America by nearly six workers.”
A study co-written by Prof. Daron Acemoglu examines the impact of autonomous robots on local labor markets, writes Gillian White for The Atlantic. “While the findings might seem grim for workers, the authors note that just because an industry can automate doesn’t mean that it will,” concludes White.
Claire Cain Miller writes for The New York Times about a study by Prof. Daron Acemoglu that shows how robots are impacting the American job market. “The conclusion is that even if overall employment and wages recover, there will be losers in the process, and it’s going to take a very long time for these communities to recover,” says Acemoglu.
A study co-authored by Prof. Daron Acemoglu finds that every new robot added to American factories reduced employment in the surrounding areas, reports Cora Lewis for CNBC. According to the study, the areas experiencing major decline were “routine manual occupations, blue-collar workers, operators and assembly workers, and machinists and transport workers.”
A study by MIT researchers finds that robots have negatively impacted American employment and wages, reports Andrew Soergel for U.S. News & World Report. After accounting for enhancements in productivity and growth in other sectors, researchers found that “automation's rise isn't entirely a bad thing for the labor market,” explains Soergel.
Prof. Daniela Rus speaks to the BBC’s Gareth Mitchell about the robots developed by CSAIL that can modify their behavior based on brain waves detected by a human operator. “We imagine operating prosthetic devices, a wheelchair, even autonomous vehicles,” says Prof. Rus.
CSAIL researchers have developed a system that allows robots to correct their mistakes based on input from the brainwaves of human operators, reports Wired’s Matt Simon. “It’s a new way of controlling the robot,” explains Prof. Daniela Rus, “in the sense that we aim to have the robot adapt to what the human would like to do.”
Anthony Cuthbertson of Newsweek writes that CSAIL researchers have developed a system that allows robots to change their actions based on feedback from the brain waves of a human operator. “Imagine robots or smartphones that could immediately correct themselves when you realize they’re making a mistake,” says PhD candidate Joseph DelPreto.
CSAIL researchers have developed a system that allows robots to detect brain signals generated by human operators, writes Oscar Williams of Huffington Post. The researchers hope the new system could “pave the way for more seamless interactions between robots and humans.”
A feedback system developed by CSAIL researchers allows humans to correct a robot’s mistakes using brain signals, writes Janet Burns for Forbes. The system could be used as a “communication method for those who can't use verbal means, such as immobilized or even 'locked in' victims of paralysis,” explains Burns.
MIT researchers have developed a device that allows humans to guide robots using brainwaves, reports Clive Cookson for the Financial Times. The prototype brain-computer interface “enables a human observer to transmit an immediate error message to a robot, telling it to fix a mistake when it does something wrong.”
New Scientist reporter Matt Reynolds writes that MIT researchers have developed a new brain-computer interface that enables people to correct robots’ mistakes using brain signals. “We’re taking baby steps towards having machines learn about us, and having them adjust to what we think,” explains Prof. Daniela Rus, director of CSAIL.
In this video, TechCrunch explores how MIT researchers are designing new techniques to make it easier for robots to grasp and manipulate objects. Graduate student Nikhil Chavan-Dafle explains that he and his colleagues developed a model that allows robots to “predict how an object is going to move in the grasp.”