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This August 2017 photo provided by Shamima Khatoon shows Khatoon in New Delhi. Khatoon's job of annotating cars, lane markers and traffic lights at an all-female outpost of data-labeling company iMerit in Metiabruz, India, represents the only chance she has to work outside the home in a conservative Muslim region of India. (Mushtari Fatma Zarin/Courtesy of Shamima Khatoon via AP) SAN FRANCISCO (AP) — There’s a dirty little secret about artificial intelligence: It’s powered by hundreds of thousands of real people. From makeup artists in Venezuela to women in conservative parts of India, people around the world are doing the digital equivalent of needlework —drawing boxes around cars in street photos, tagging images, and transcribing snatches of speech that computers can’t quite make out. Such data feeds directly into “machine learning” algorithms that and let Alexa figure out that you want the lights on. Many such technologies wouldn’t work without massive quantities of this human-labeled data. These repetitive tasks pay pennies apiece.
But in bulk, this work can offer a decent wage in many parts of the world — even in the U.S. This burgeoning but largely unseen cottage industry represents the foundation of a technology that could change humanity forever: AI that will drive us around, execute verbal commands without flaw, and, possibly, one day think on its own.
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Blood collection device problems may go unnoticed by laboratorians since routine quality control (QC) practice typically does not assess all aspects of laboratory testing from blood collection, including specimen processing, analytical testing, and test reporting (7,8).
___ This human input industry has long been nurtured by search engines Google and Bing, who for more than a decade have used people to rate the accuracy of their results. Since 2005, Amazon’s Mechanical Turk service, which matches freelance workers with temporary online jobs, has also made crowd-sourced data entry available to researchers worldwide. More recently, investors have poured tens of millions of dollars into startups like Mighty AI and CrowdFlower, which are developing software that makes it easier to label photos and other data, even on smartphones.
Venture capitalist S. “Soma” Somasegar says he sees “billions of dollars of opportunity” in servicing the needs of machine learning algorithms. His firm, Madrona Venture Group, invested in Mighty AI. Humans will be in the loop “for a long, long, long time to come,” he says. Peek behind the curtain as reveals the dirty little secret of AI – it’s made of people! Well, powered by them, anyway.
— AP Business News (@APBusiness) Accurate labeling could make the difference between a self-driving car distinguishing between the sky and the side of a truck — a distinction Tesla’s Model S failed in the involving self-driving systems in 2016. “We’re not building a system to play a game, we’re building a system to save lives,” says Mighty AI CEO Daryn Nakhuda. ___ Marjorie Aguilar, a 31-year-old freelance makeup artist in Maracaibo, Venezuela, spends four to six hours a day drawing boxes around traffic objects to help train self-driving systems for Mighty AI. She earns about 50 cents an hour, but in a crisis-wracked country with runaway inflation, just a few hours’ work can pay a month’s rent in bolivars.