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DoorDash has launched a standalone app called "Tasks" that allows its 8 million U.S. gig workers to earn money by training AI and robotics. Announced on Thursday, the app enables couriers to record themselves performing various physical activities. This data is intended to help artificial intelligence models better understand and navigate the physical world.
Tasks available on the new app include everyday chores like folding clothes, handwashing dishes and making a bed, with each gig offering a payment sum based on effort and complexity. Harder tasks, like pruning and repotting plants, offer more money.
Couriers can also get paid for recording speaking content in other languages. One listing on the app prompts Spanish speakers to have a “natural, unscripted conversation with your friends or family on everyday topics.”
“We think this will be huge for building the frontier of physical intelligence,” DoorDash cofounder and chief technology officer Andy Fang wrote in a social media post about the launch. “Look forward to seeing where this goes!”
A spokesperson for DoorDash said that the app will initially focus on activities that could help train AI or robotics, but the company plans to add other types of activities over time. The company added that the Tasks app is a small pilot compared to what’s available in the general Dasher app, where a wider array of tasks are listed for couriers to complete in between deliveries.
It’s part of a growing ecosystem of gigs that aim to farm AI training data from willing humans.
Last year, Uber piloted a similar initiative allowing its U.S. gig workers to perform additional digital tasks for money, including uploading photos and recordings used to train AI. And the data annotation industry has boomed in recent years, with dozens of platforms hiring contractors to help train AI models online.
Now, companies are increasingly seeking to capture physical data about how people move in the world. Such content is then used to help a humanoid robot, for example, learn how to load a dishwasher.
