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Uber Expands Gig Economy Offerings with AI Data Labeling Division

Uber Expands Gig Economy Offerings with AI Data Labeling Division

Uber has introduced a new gig economy initiative, expanding its workforce to support AI development through data labeling and coding services. The company’s newly branded Scaled Solutions division hires independent contractors to handle AI annotation, data labeling, and coding tasks.

Initially serving Uber’s internal projects, the division now extends its services to external companies, including autonomous vehicle firm Aurora Innovation and game developer Niantic, according to Bloomberg.

Scaled Solutions emerged as an internal team tasked with managing large-scale annotation for Uber’s operations. Now positioned as an external service provider, the division supplies analysts, testers, and data operators to meet growing industry demands. Aurora, which acquired Uber’s self-driving unit in 2020, counts Uber among its investors.

Recruitment for Scaled Solutions spans multiple countries, including the United States, Canada, India, Poland, and Nicaragua, with corporate positions available in San Francisco, New York, and Chicago. Contractors are paid monthly based on completed tasks, though specific rates remain undisclosed.

The timing of this move aligns with a surge in demand for data labeling fueled by AI advancements. Competitors like Scale AI have seen similar growth, with Scale raising $1 billion at a valuation of $13.8 billion earlier this year.

With Scaled Solutions, Uber is not only leveraging its gig economy expertise but also tapping into the lucrative AI data labeling market, potentially setting the stage for broader participation in the AI ecosystem.

Uber’s move into AI data labeling with Scaled Solutions signals the gig economy’s growing role in tech. By expanding into high-demand services like data annotation and coding, Uber diversifies its business while leveraging its gig expertise. However, with pay tied to task completion and little transparency, the shift highlights ongoing challenges in balancing innovation with fair treatment for workers.

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