The program aims to create the largest distributed data-collection network in the gig economy, leveraging DoorDash's global network of Dashers.

The initial rollout excludes California, New York City, Seattle, and Colorado due to regulatory considerations, with expansion planned as rules allow.

Analysts say the move could shift gig workers’ earnings expectations, draw regulatory scrutiny over compensation and privacy, and spur broader industry adoption of distributed data collection as a revenue stream.

Pay for tasks is disclosed upfront and varies by complexity, though there are no published averages or guaranteed minimums.

Couriers can earn by activities such as filming daily tasks or translating in other languages, with upfront pay set by the task’s effort.

The rollout arrives amid ongoing lawsuits over unauthorized use of copyrighted material in AI training and may address some concerns by paying contributors directly.

Tasks incorporates multi-layered quality control and privacy safeguards, including automatic validation, metadata tagging, secure storage, automated blurring of faces and plates, and permission requirements for private spaces.

DoorDash positions Tasks within a broader paid-content-for-AI trend, offering a direct compensation model for individuals contributing training data.

Industry context shows competitors like Uber pursuing similar data-labeling programs, signaling a broader push toward distributed data collection.

DoorDash today launches Tasks, a standalone app that turns couriers into data collectors to help train AI and robotic models, starting in select markets.

Participants can earn upfront pay for tasks that involve filming, photographing, or other data-collection activities, with payments determined by task effort and complexity.