Uber Expands Gig Economy with AI Micro-Tasks for Drivers During Downtime

Uber Drivers to Supplement Income with AI Tasks

Uber is reportedly launching a new initiative that will enable its U.S. drivers to earn additional income by completing artificial intelligence-related micro-tasks during downtime between passenger rides, according to company announcements. The program, currently being tested in India before its planned U.S. rollout, represents Uber’s entry into the rapidly growing market for human-verified AI training data.

Uber Drivers to Supplement Income with AI Tasks
The New “Work Hub” Platform
Addressing AI’s Hidden Workforce Needs
Strategic Expansion and Future Plans
Broader Implications for the Gig Economy

The New “Work Hub” Platform

Sources indicate that Uber’s newly developed Work Hub platform will function similarly to established crowdsourcing services like Amazon Mechanical Turk, but specifically tailored for drivers already using the Uber app. The system reportedly offers brief tasks that can be completed in approximately one minute while vehicles are parked, including data labeling, audio recording, and document upload assignments.

According to Uber Chief Product Officer Sachin Kansal’s statements to Bloomberg, the platform is designed to function offline and requires no specialized skills beyond basic smartphone operation. “The new service gives drivers another way to earn money,” the report states, with compensation varying based on the complexity and time requirements of each task.

Addressing AI’s Hidden Workforce Needs

Analysts suggest this initiative highlights the increasingly significant role of human workers in correcting AI errors and refining algorithmic outputs. The growing demand for what industry observers call “AI chores” has created an invisible workforce that performs low-paid labeling tasks essential for improving generative models and reducing hallucinations in AI systems.

Uber’s expansion into this market comes as AI training and data verification become increasingly valuable services. Recent valuations of specialized AI data-labeling startups like Scale AI and Surge AI have reportedly reached approximately $30 billion, indicating substantial market potential that Uber and other gig economy platforms are positioned to capture.

Strategic Expansion and Future Plans

While the initial rollout focuses exclusively on current Uber drivers, company executives have suggested the system could eventually expand to include non-drivers. However, according to Kansal, the immediate priority remains engaging existing drivers who already use the Uber platform regularly.

The introduction of AI tasks reportedly does not relate to Uber’s parallel investments in autonomous vehicle technology, despite timing coincidences. Company representatives have emphasized that these micro-jobs are not intended to replace income drivers might eventually lose to automation, but rather to provide supplemental earnings during natural downtime in their existing work schedules.

Broader Implications for the Gig Economy

Industry observers note that Uber’s move signals a significant expansion of the gig economy into AI infrastructure support. This development comes as human input becomes increasingly crucial for addressing AI limitations, including tendencies to generate low-quality content or fabricate information with unwarranted confidence.

Meanwhile, critics have raised concerns about the lack of regulatory frameworks and safety measures for this emerging workforce category. The growing army of digital laborers—known as “Turkers” in reference to the Amazon platform that pioneered this model—face uncertain working conditions and compensation structures as they perform the essential but often invisible work of making AI systems appear more reliable than their underlying technology might otherwise allow.

According to Uber’s official blog announcement, the company plans to continuously add new task types to the Work Hub platform, potentially creating additional revenue streams for drivers while simultaneously addressing the AI industry’s persistent need for human-verified training data.