The Very Human Labor That Powers Artificial Intelligence

In 2015, Caroline Sinders was working as a design researcher at IBM when she began to have questions about how Watson, the company's artificial intelligence system, was being developed. AI systems like Watson must be "trained" with data sets--for example, given a large batch of confirmed photographs of stop signs from different angles, in different lighting, and of different quality to be able to recognize stop signs on their own. Sinders was curious about these data sets: The process of correctly categorizing millions of data points seemed like a herculean task in its own right; where, exactly, was all this data coming from? "A lot of my coworkers were like, 'I don't know why you're asking us these questions, we're just supposed to build this system out,'" she recalls. While Sinders's coworkers may have been able to push the question aside, finding the answer of where the data sets necessary to train artificial intelligence systems come from eventually led her to the world of crowd-working platforms.