The demand for data labeling in the artificial intelligence industry — tagging videos, sorting photos, and transcribing audio in order to train AI — has created a massive need for cheap labor, leading data-labeling platforms such as Appen to hire low-pay workers in countries like Venezuela, the Philippines, and Kenya to do these tasks. In this story, Karen Hao and Andrea Paola Hernández report on what it’s really like to do this “ghost work.”
Simala Leonard, a computer science student at the University of Nairobi who studies AI and worked several months on Remotasks, says the pay for data annotators is “totally unfair.” Google’s and Tesla’s self-driving-car programs are worth billions, he says, and algorithm developers who work on the technology are rewarded with six-figure salaries.
Meanwhile, the people who do “the most fundamental part of machine learning” are paid a pittance, he says. “Without the data labeled well, the models can’t predict properly.”
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