Technology and society

Prof. Cynthia Breazeal discusses her work exploring how artificial intelligence can help students impacted by Covid, including refugees or children with disabilities, reports Ryan Heath for Politico. “We want to be super clear on what the role is of the robot versus the community, of which this robot is a part of. That's part of the ethical design thinking,” says Breazeal. “We don't want to have the robot overstep its responsibilities. All of our data that we collect is protected and encrypted.”

TechCrunch reporter Kyle Wiggers spotlights DynamoFl, a company founded by Christian Lau PhD ’20 and Vaikkunth Mugunthan PhD ’22 that is developing a federated learning platform, a technique for preserving data privacy in AI systems. 

A new study co-authored by MIT researchers demonstrates that forming weak ties on LinkedIn can help people find new jobs, reports Vivianne Callier for Scientific American.  “One thing the study highlights is the degree to which algorithms are guiding fundamental, baseline, important outcomes, like employment and unemployment,” says Prof. Sinan Aral.

Fast Company reporter Sam Becker writes that a study co-authored by MIT researchers finds that weaker social connections on LinkedIn have a greater impact on job mobility than stronger relationships. The findings demonstrate that “the best thing many job seekers can do, as counterintuitive as it sounds, is to mine their lesser-known or secondary connections for opportunities,” writes Becker.

Research by Prof. Sinan Aral and his colleagues has found that having “moderately weak ties” can positively facilitate job shifts, reports Nicola Davis for The Guardian. Aral said that as well as examining the importance of weak ties, the study highlighted the degree to which social media algorithms “are turning the knobs on our economies and fundamental indicators like employment." 

The MIT Educational Justice Initiative has developed a 12-week program called Brave Behind Bars that teaches inmates “basic coding languages such as JavaScript and HTML in hopes of opening the door for detainees to one day pursue high-paying jobs,” reports Washington Post reporter Emily Davies. “The level of 21st century technology skills they just learned, I can’t do those things,” said Amy Lopez, deputy director of college and career readiness for the D.C. Department of Corrections. “They are transferrable, employable skills.”

Researchers from MIT are working with the Staten Island Performing Provider System to develop an algorithm that can predict who in the system is at risk for an opioid overdose, reports Maddie Bender for the Daily Beast. “In preliminary testing, Conte’s team and MIT Sloan researchers found their model was highly accurate at predicting overdoses and fatal overdoses, even with delays in the data of up to 180 days,” writes Bender.

Washington Post reporter Pranshu Verma writes about how Prof. Dina Katabi and her colleagues developed a new AI tool that could be used to help detect early signs of Parkinson’s by analyzing a patient’s breathing patterns. For diseases like Parkinson’s “one of the biggest challenges is that we need to get to [it] very early on, before the damage has mostly happened in the brain,” said Katabi. “So being able to detect Parkinson’s early is essential.”

Forbes contributor Jennifer Kite-Powell spotlights how MIT researchers created a new AI system that analyzes radio waves bouncing off a person while they sleep to monitor breathing patterns and help identify Parkinson’s disease. “The device can also measure how bad the disease has become and could be used to track Parkinson's progression over time,” writes Kite-Powell.

A new tool for diagnosing Parkinson’s disease developed by MIT researchers uses an AI system to monitor a person’s breathing patterns during sleep, reports Hiawatha Bray for The Boston Globe. “The system is capable of detecting the chest movements of a sleeping person, even if they’re under a blanket or lying on their side,” writes Bray. “It uses software to filter out all other extraneous information, until only the breathing data remains. Using it for just one night provides enough data for a diagnosis.”

Boston Globe reporter Hiawatha Bray speaks with Radio Boston host Tiziana Dearing about how MIT researchers developed an artificial intelligence model that uses a person’s breathing patterns to detect Parkinson’s Disease. The researchers “hope to continue doing this for other diseases like Alzheimer’s and potentially other neurological diseases,” says Bray.

Researchers at MIT have developed an artificial intelligence sensor that can track the progression of Parkinson’s disease in patients based on their breathing while they sleep, reports Conor Hale for Fierce Biotech. “The device emits radio waves and captures their reflection to read small changes in its immediate environment,” writes Hale. “It works like a radar, but in this case, the device senses the rise and fall of a person’s chest.”

Writing for The Hill, President L. Rafael Reif and Stephen A. Schwarzman, chairman, CEO & co-founder of Blackstone, praise the new “CHIPS and Science Act” and highlight the need for further action on the ‘Science’ part of the law. “We urge Congress to capitalize on this bipartisan momentum and appropriate the funds that the bill authorizes,” they write. The nation's "future competitiveness, prosperity and security all rely on technological leadership. To sustain its strength in the long term, the U.S. needs to invent and manufacture the next new technologies.”

MIT researchers have developed a new artificial intelligence system that uses a person’s breathing pattern to help detect Parkinson’s sisease, reports Susannah Sudborough for Boston.com. “The device emits radio signals, analyzes reflections off the surrounding environment, and monitors the person’s breathing patterns without any bodily contact,” writes Sudborough.

Researchers at MIT and other institutions have developed an artificial intelligence tool that can analyze changes in nighttime breathing to detect and track the progression of Parkinson’s disease, reports Casey Ross for STAT. “The AI was able to accurately flag Parkinson’s using one night of breathing data collected from a belt worn around the abdomen or from a passive monitoring system that tracks breathing using a low-power radio signal,” writes Ross.