Uber plans to launch data labelling tasks in the US for some drivers to earn extra money, appearing under “digital tasks” in the driver app, later this fall
Uber Technologies Inc. is giving some drivers in the US the option to earn money by completing tasks related …
Context & Ripple Effects
Uber had already opened its Scaled Solutions data-labeling service to gig-worker signups across several countries, including the US, in its earlier Scaled Solutions expansion. It subsequently put similar microtasks in front of drivers in India through its AI Solutions unit, creating a direct operational precedent for this rollout the Indian driver microtask program.
The move matters because it places a second kind of paid work inside the driver app, rather than treating labeling as a separate labor marketplace. It extends Uber's existing practice of using app design and earnings information to shape driver participation.
First-order effects
- Some US drivers will be able to earn from data-labeling work through a new in-app digital-tasks section, alongside their usual driving activity.
- Uber gains access to a US-based pool of workers for its labeling operation without requiring those workers to join a separate platform.
Second-order effects
- Task availability and pay will become another lever in Uber's driver-engagement system; drivers may weigh digital work against waiting for or accepting trips.
- The rollout tests whether Uber can turn its existing driver network into a dependable source of on-demand labeling capacity, building on its use of Indian drivers for photo-tagging tasks.
Third-order effects
- If these tasks scale, ride-hailing platforms may increasingly treat their apps as multi-work marketplaces, with transportation workers supplying both physical services and inputs for AI systems.
- That model could increase scrutiny of how platform workers are compensated, informed about task terms, and able to move work across marketplaces; the corpus does not yet show how Uber will set those terms.
The trend: Uber is extending gig-work infrastructure from matching drivers with rides to routing small AI-production tasks to the same workforce.