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Chronicles

The story behind the story

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Uber launches a data labeling service called Scaled Solutions, accepting gig worker signups from India, the US, Canada, Poland, and Nicaragua

- Rideshare giant wants to help other businesses train AI models  — Company accepting signups from India, US, Canada and Poland

Bloomberg Natalie Lung

Context & Ripple Effects

Uber had already used its driver network as a channel to surface work beyond ride-hailing, including job openings for US drivers during the ride-hailing slowdown. Scaled Solutions applies that distribution model to AI-training work while turning Uber into a service provider for outside businesses.

The subsequent arc shows the initial service becoming embedded in the driver app: Indian drivers were assigned image-tagging microtasks, while Uber also planned US “digital tasks.” That makes this launch the starting point for a broader AI-services unit rather than a standalone gig-work feature.

First-order effects

  • Uber gains a business-to-business data-labeling offering and begins recruiting a multicountry pool of workers for it.
  • Eligible workers in India, the US, Canada, Poland, and Nicaragua can sign up for AI-training tasks alongside Uber’s existing platform work.

Second-order effects

  • Uber now competes with specialist labeling providers for client contracts and for the workers who complete annotation tasks; its existing app and worker base reduce the friction of recruiting supply.
  • Businesses seeking labeled training data gain a potential vendor whose workforce can be activated through a consumer-platform network rather than assembled solely through dedicated annotation operations.

Third-order effects

  • If the model scales, ride-hailing platforms can become labor-distribution layers for AI production, monetizing worker availability beyond trips and deliveries.
  • The later addition of Segments.ai’s lidar-labeling capabilities suggests that broad task supply and specialized annotation tooling may increasingly be combined inside the same AI-services provider.

The trend: This is part of AI infrastructure platformization, in which large consumer platforms turn their user and worker networks into commercial inputs for building AI systems.