The launch adds a new layer to DoorDash’s platform by turning its delivery workforce into a distributed source of real-world training data. Tasks can range from simple recordings to more structured activities—such as capturing step-by-step footage of routine actions—designed to help AI systems better interpret physical environments. The company said this type of data helps machines “understand the physical world.”
DoorDash is also integrating Tasks directly into its existing Dasher app. In addition to AI-related assignments, workers may be asked to photograph restaurant menu items, document building entrances to improve navigation, or assist with logistics tied to autonomous delivery partnerships. One example includes couriers being paid to close the doors of Waymo’s self-driving vehicles after drop-offs.
Ethan Beatty, general manager of DoorDash Tasks, said the initiative is intended to expand earning opportunities while giving businesses better visibility into real-world conditions. “There are more than 8 million Dashers who can reach almost anywhere in the U.S. and who want to earn flexibly beyond delivery. That’s a powerful capability to digitize the physical world,” he said.
The move places DoorDash alongside other gig platforms experimenting with similar models. Uber, for example, previously introduced programs allowing drivers to complete small data collection jobs, such as uploading images to support AI training.
For DoorDash, the approach leverages an existing workforce that already operates in varied, real-world environments—potentially giving it access to large volumes of diverse data without building a separate data collection infrastructure. At the same time, it reflects a broader shift in how companies gather training data, moving toward continuous, on-the-ground collection tied to everyday work.
The Tasks app and in-app features are currently available in select U.S. markets, excluding California, New York City, Seattle, and Colorado. DoorDash said it plans to expand the program to additional locations and introduce new types of assignments over time.
This analysis is based on reporting from TechCrunch.and Bloomberg.
Image courtesy of ZDNET.
This article was generated with AI assistance and reviewed for accuracy and quality.
