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Uber Tests Model That Allows Drivers and Deliverers to Complete Paid Digital Tasks Via App, Like Sending Photos and Recording Audio, While Awaiting New Rides. Pilot Project Begins in the United States and Involves the Company’s Internal AI Group.
Uber will begin offering paid digital tasks within the app itself, allowing drivers and deliverers to earn additional income during breaks between rides and deliveries.
The project, led by the internal AI Solutions group, debuts as a pilot in the United States and incorporates quick activities aimed at training AI models, such as recording voice clips, sending photos, and submitting documents in specific languages.
The initiative was announced by CEO Dara Khosrowshahi as part of the plan to turn the platform into the “best environment for flexible work.”
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How It Will Work in the Driver App
Within the app for those who already drive or deliver, a new category called Digital Tasks will appear.
There, the worker will be able to see which tasks are available, with payment tied to the time and complexity of each activity.
According to the company, these are microtasks that can be completed in a few minutes and that can be performed on the mobile device itself.
Among the examples shared are recording audio in specific languages or accents, capturing and sending images under guidance, and submitting documents in other languages.
In some instructions, the app may ask the driver to record their own voice saying specific phrases or to photograph objects according to predefined descriptions.
There are also requests for uploading menus or materials in other languages, which feed linguistic databases.
An example cited by the trade press is the submission of a menu in Spanish, compensated at up to US$ 1 per item.
The amounts vary according to the task, and the company does not disclose an average earning per hour.
Objective and Scope of the Pilot
Uber states that the proposal meets a recurring demand from those using the platform to work: more ways to earn when the demand for rides or deliveries is low.
The pilot originates in the United States and was preceded by tests in India, where drivers were already responding to prompts in the app for similar tasks.
The development and operation of the activities are the responsibility of the Uber AI Solutions Group, the area that combines “human-in-the-loop” processes to train models.
By opening this front, the company also positions itself in the market for labeling and data generation for AI, currently dominated by companies like Scale AI and microtask platforms.
The bet is to use the base of registered drivers and deliverers to execute short and distributed missions, with identity verification and native app mechanisms.
Reports published by technology outlets indicate that the strategy puts Uber on a path to compete with services like Amazon Mechanical Turk, but with the advantage of an active and geographically broad network of workers.
What the Company Says About Compensation and Protection
Although Uber emphasizes that payments are transparent before execution and proportional to the complexity of the task, there is no disclosure of a public price list or an average earning estimate per hour.
The company stresses that Digital Tasks are optional and that the worker can switch between rides, deliveries, and tasks according to their routine.
In parallel to the pilot, the company announced adjustments to the trip offer card, a new heatmap to indicate areas with shorter wait times, and additional security and control functions, such as preferences for rides with female passengers and adjusting the minimum passenger rating.
These changes appear in the “Only on Uber 2025” package, announced at an event in Washington, and are part of the argument that the platform has been expanding income, transparency, and protection tools.
The company has also been reviewing deactivation rules, anticipating instances where drivers’ access is not completely blocked and allowing them to present their version before a final decision.
Relationship With the AI Wave and the Future of App Work
In the announcement, Uber ties the pilot to a broader vision of on-demand work, where digital tasks coexist with mobility and delivery activities.
By using its own network to generate training data, the company seeks to reduce costs, scale volume, and offer complementary income during idle periods.
This movement comes as industry executives admit that automation is expected to advance in the coming years and reconfigure part of the traditional driving opportunities.
Therefore, Uber claims to be expanding new types of work within its ecosystem.
Trade press observes that if adoption is high, Uber could compete for contracts with companies that need annotated and verified data to train generative AI and computer vision models.
The global volume of the base of drivers and deliverers, combined with the app’s anti-fraud instruments, is an asset that the company leverages to validate submitted content.
Still, aspects such as which clients hire the tasks, how the data is stored, and what privacy safeguards apply have not been publicly detailed so far.
Differences in Relation to Other Microtask Platforms
Comparison with traditional microtask services is inevitable.
Platforms like Mechanical Turk connect companies to remote workers who perform small jobs of annotation and data validation.
In the case of Uber, the intermediation occurs within the driver app, visible only to those who are already registered and active in the company’s ecosystem.
This entry barrier, according to analysts, may reduce classic problems of identity, quality, and payment that affect open markets, although it also limits reach to those who are not part of Uber’s base.
What Is Left to Know
Uber confirmed the start of the pilot in the U.S., the origin of the program in tests in India, and the management by the AI Solutions area.
There are also examples of tasks and indicators of payment per item, such as the submission of a menu compensated at up to US$ 1.
Official disclosure is still lacking regarding the average earnings per hour, the copyright policy for submitted content, and the list of sectors served by the collected data.
These points will be central to evaluate driver adoption, the quality of the generated material, and the impact on the income of those relying on the app in their daily lives.
As the pilot progresses, drivers and deliverers will test the novelty to see if it is worth spending idle minutes on digital tasks.
The question that arises, in light of this new arrangement of app work, is straightforward: would you be willing to turn your idle time between rides into AI microtasks to boost your income?
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