Forbes contributor Adi Gaskell spotlights how the MIT Task Force on the Work of the Future recently released a comprehensive report examining the future of work. Gaskell writes that the Task Force's report emphasizes the “pressing issues of our time as one of improving the quality of jobs to ensure that prosperity is shared across the economy.”
Forbes contributor Louis Columbus spotlights Verta, an MIT startup that is “dedicated to solving the complex problems of managing machine learning model versions and providing a platform where they can be launched into production.”
Writing for the Financial Times, Ryosuke Harada highlights a new MIT report that emphasizes the “importance of education and investment in human resources and warns that in the absence of a strategy, jobs will be lost and divisions in society will widen.”
Forbes contributor Rob Toews spotlights the work of Professor Daniela Rus, the deputy dean of research for the Schwarzman College of Computing and director of CSAIL; graduate student Joy Buolamwini; and former MIT postdoc Rana el Kaliouby for their work shaping the future of AI. “They also serve as role models for the next generation of AI leaders, reflecting what a more inclusive AI community can and should look like," writes Toews.
Writing for Wired, Will Knight spotlights how MIT researchers developed a new technique to squeeze an AI vision algorithm onto a low-power computer chip that can run for months on a battery. The advance “could help bring more advanced AI capabilities, like image and voice recognition, to home appliances and wearable devices, along with medical gadgets and industrial sensors.”
Research scientist Brian Subirana speaks with The Economist’s Babbage podcast about his work developing a new AI system that could be used to help diagnose people asymptomatic Covid-19.
Elisabeth Reynolds, executive director of the MIT Task Force on the Work of the Future, speaks with Annie Nova of CNBC about the Task Force’s new report, which lays out recommendations for ensuring Americans are able to secure good jobs in an era of automation. “We’re suggesting that people have access to affordable education and training,” says Reynolds. “I think there’s a real opportunity to help transition people and educate workers without four-year degrees.”
Axios reporter Bryan Walsh writes that a new report by MIT’s Task Force on the Work of the Future makes policy recommendations for ensuring American workers are able to secure good jobs. “If we deploy automation in the same labor market system we have now," says Prof. David Mindell, "we're going to end up with the same results.”
Three years after President L. Rafael Reif delivered an “intellectual call to arms” to examine the impact of technology on jobs, the MIT Task Force on the Work of the Future has published its final set of recommendations. “In an extraordinarily comprehensive effort, they included labor market analysis, field studies and policy suggestions for changes in skills-training programs, the tax code, labor laws and minimum-wage rates,” writes Steve Lohr for The New York Times.
Prof. James Collins speaks with Boston 25 reporter Julianne Lima about the growing issue of antibiotic resistant bacteria and his work using AI to identify new antibiotics. Collins explains that a new platform he developed with Prof. Regina Barzilay uncovered “a host of new antibiotics including one that we call halicin that has remarkable activity against multi drug-resistant pathogens.”
Fast Company reporter KC Ifeanyi writes about “Coded Bias,” which explores how graduate student Joy Buolamwini’s “groundbreaking discovery and subsequent studies on the biases in facial recognition software against darker-skinned individuals and women led to some of the biggest companies including Amazon and IBM rethinking their practices.”
A new algorithm developed by MIT researchers could be used to help detect people with Covid-19 by listening to the sound of their coughs, reports Zoe Kleinman for BBC News. “In tests, it achieved a 98.5% success rate among people who had received an official positive coronavirus test result, rising to 100% in those who had no other symptoms,” writes Kleinman.
Mashable reporter Rachel Kraus writes that a new system developed by MIT researchers could be used to help identify patients with Covid-19. Kraus writes that the algorithm can “differentiate the forced coughs of asymptomatic people who have Covid from those of healthy people.”
A new took developed by MIT researchers uses neural networks to help identify Covid-19, reports Alyse Stanley for Gizmodo. The model “can detect the subtle changes in a person’s cough that indicate whether they’re infected, even if they don’t have any other symptoms,” Stanley explains.
TechCrunch reporter Devin Coldewey writes that MIT researchers have built a new AI model that can help detect Covid-19 by listening to the sound of a person’s cough. “The tool is detecting features that allow it to discriminate the subjects that have COVID from the ones that don’t,” explains Brian Subirana, a research scientist in MIT’s Auto-ID Laboratory.