The Toyota Research Institute (TRI) announced that it will be extending its AI research collaboration with MIT. TRI, which also has existing relationships with Stanford and the University of Michigan, has selected 13 additional academic institutions to participate in the next five-year phase of its research initiative.

MIT neuroscientists have found that reading computer code does not activate the regions of the brain that are involved in language processing. Instead, it activates a distributed network called the multiple demand network, which is also recruited for complex cognitive tasks such as solving math problems or crossword puzzles.

In this report, we conclude that recent fears about AI leading to mass unemployment are unlikely to be realized. Instead, we believe that—like all previous labor-saving technologies—AI will enable new industries to emerge, creating more new jobs than are lost to the technology.

MIT study shows the power of adaptive training tools, like a basketball hoop that shrinks and raises as you make shots.

As more intelligent, independent machines make their way into the public sphere, engineers Julie Shah and Laura Major are urging designers to rethink not just how robots fit in with society, but also how society can change to accommodate these new, “working” robots.

Stefanie Mueller leads the HCI Engineering Group at CSAIL. In her work, she develops novel hardware and software systems that advance personal fabrication technologies.

Arvind Satyanarayan, who leads the MIT Visualization Group, uses visualization to study intelligence augmentation, specifically how software systems can help amplify our cognition and creativity, while respecting our agency.