One of the most notable companies among the new specialized firms was (and still is) Scale AI.
Other older platforms, like Appen, adapted to the newer approach. MTurk fell out of favor, and the specialized platforms took over. When the automakers came along in 2017, they wanted not just better performance but accuracy of 99% or more. “As crises move around, it’s quite likely there will be another country that could fulfill that role.”Īs deep learning began to take off in the early 2010s, a new generation of more specialized AI crowdworking platforms emerged, seeking to ensure better accuracy with a more hands-on approach to both the clients and workers. “The Venezuela example made so clear how it’s a mixture of poverty and good infrastructure that makes this type of phenomenon possible,” Schmidt says. What began in Venezuela set an expectation among players in the AI industry for how little they should have to pay for such services, and it created a playbook for how to meet the prices that clients have come to rely on. Now, as some platforms are turning their attention to other countries in search of even cheaper pools of labor, the model could continue to spread. To a growing chorus of experts, the arrangement echoes a colonial past when empires exploited the labor of more vulnerable countries and extracted profit from them, further impoverishing them of the resources they needed to grow and develop. “There are huge power imbalances,” says Julian Posada, a PhD candidate at the University of Toronto who studies data annotators in Latin America.
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