Writing for Forbes, Joseph Coughlin, director of the MIT AgeLab, examines the increasing influence of AI in our lives. Coughlin concludes that in the absence of a human alternative, brief interactions could change our perception of an AI system from “a simple tool that ‘does stuff’ around the house, to a presence that is a real part of our social self.”
A Washington Post article by Prof. Erik Brynjolfsson and Research Affiliate Xiang Hui demonstrates how artificial intelligence is starting to have a positive impact on the U.S. economy by helping with such obstacles as lowering the language barrier to trade. Brynjolfsson and Hui explain that “human intelligence is needed to make sure it benefits the many, not just the few.”
Fortune reporters Aaron Pressman and Adam Lashinsky highlight graduate student Joy Buolamwini’s work aimed at eliminating bias in AI and machine learning systems. Pressman and Lashinsky note that Buolamwini believes that “who codes matters,” as more diverse teams of programmers could help prevent algorithmic bias.
CNBC reporter Catherine Clifford writes that MIT researchers have started a project to spotlight creative collaborations between humans and machines. Postdoctoral associate Pinar Yanardag explains that the project is aimed at showing the public that “we can work together with AI to achieve the most creative and productive outcomes.”
Principal Research Scientist Andrew McAfee speaks with BBC Radio’s David Grossman about the impact that artificial intelligence could have on various aspects of our lives. McAfee predicts that AI will reinvent, not replace capitalism, and that “even if things become very, very cheap because of technological progress that doesn’t strike away at the pillars of the capitalist system.”
MIT researchers have developed a model that can help detect depression by analyzing an individual’s speech patterns, reports Kaveh Waddell for Axios. Waddell explains that the researchers, “trained an AI system using 142 recorded conversations to assess whether a person is depressed and, if so, how severely.”
A study co-authored by MIT researchers finds that robots can develop prejudices against other robots not working on their team, writes John Biggs for TechCrunch. The researchers also found that, like humans, prejudices were reduced when there were “more distinct subpopulations being present within a population.”
MIT researchers have developed a new system that can detect depression by examining a patient’s speech and writing, reports John Biggs for TechCrunch. Biggs writes that the system could “help real therapists find and isolate issues automatically versus the long process of analysis. It’s a fascinating step forward in mental health.”
A study co-authored by Prof. Erik Brynjolfsson and graduate student Daniel Rock finds that specific tasks, not jobs, are likely to become automated, writes Joe McKendrick for Forbes. The researchers explain that, “machine learning technology can transform many jobs in the economy, but full automation will be less significant than the re-engineering of processes and the reorganization of tasks."
MIT researchers have developed a machine learning system that could reduce the number of chemotherapy and radiotherapy treatments that glioblastoma patients receive, reports the Xinhua News Agency. The system “finds an optimal treatment plan, with the lowest possible potency and frequency of doses that should still reduce tumor sizes,” Xinhua explains.
Writing for The New York Times, Prof. Sherry Turkle argues that machines will never be able to replace humans as compassionate companions. “Machines have not known the arc of a human life. They feel nothing of the human loss or love we describe to them,” writes Turkle. “Their conversations about life occupy the realm of the as-if.”
In an article for Popular Mechanics, Tiana Cline spotlights SoFi, an autonomous, soft, robotic fish that can swim alongside real fish. “SoFi has the potential to be a new type of tool for ocean exploration and to open up new avenues for uncovering the mysteries of marine life,” Cline notes.
In an interview with Wynne Parry of NBC Mach, Prof. Sherry Turkle expresses concern that household robots can interfere with children learning to understand and connect with one another. “There are skills of listening, of putting oneself in the place of the other, that are required when two human beings try to deeply understand each other,” Turkle explains.
In an article for Forbes about how AI could improve healthcare, Bernard Marr highlights an algorithm developed by MIT researchers that can analyze 3-D scans up to 1,000 times faster than is currently possible. “When saving minutes can mean saving lives, AI and machine learning can be transformative,” writes Marr.
In an article for the Financial Times, Prof. Erik Brynjolfsson writes about his new research showing that advances in machine learning could help fuel a surge in productivity and economic growth around the world. Brynjolfsson writes that as machine learning systems develop, “we can have not only higher productivity growth, but also more widely shared prosperity.”