Uber’s new assignment for gig workers: AI data labeling

The gig economy giant Uber is expanding into AI training services by leveraging its existing independent contractor model to provide data labeling and testing services to AI companies.

Key development: Uber’s new “Scaled Solutions” division aims to connect businesses with independent contractors who can perform AI training tasks, marking a significant pivot in the company’s business strategy.

• The division builds upon an existing internal team based in the US and India that handles feature testing and content conversion
• Notable clients already include Aurora, Luma AI, and Niantic
• Workers are being recruited from multiple countries including Canada, India, Poland, Nicaragua, and the US

Business model and compensation: Uber’s approach mirrors its ride-sharing platform by connecting AI companies with gig workers who perform various data-related tasks.

• Workers are paid per completed task, with payments distributed monthly
• One example from India shows workers being paid approximately $2.37 per set of AI-generated coding response evaluations
• The company seeks workers from diverse cultural backgrounds to enhance AI adaptability across different markets

Task specifications: The work primarily involves essential but repetitive tasks necessary for training AI models.

• Tasks include selecting optimal chatbot responses
• Workers label obstacles in self-driving car footage on a frame-by-frame basis
• Additional responsibilities include testing and localization services

Historical context: Uber’s venture into AI is not its first experience with advanced technology initiatives.

• The company previously invested billions in autonomous vehicle development before shutting down the program following a fatal accident
• In 2016, Uber acquired an AI research lab established by cognitive scientist Gary Marcus and other computer science professors

Market implications: This move positions Uber to capitalize on the growing demand for AI training services while potentially raising questions about labor practices in the AI development ecosystem.

• The expansion leverages Uber’s established contractor management infrastructure
• The approach could set new precedents for how AI training data is collected and processed
• The payment model may face scrutiny given ongoing debates about gig economy compensation