The labor force for teleoperated robots could be sourced from the gig economy. Ride-share drivers, for instance, could operate robots during their downtime between rides, creating a flexible, scalable, and cost-effective pool of on-demand human operators.
The future of gig work on Lyft isn't just about replacing drivers with corporate AV fleets. CEO David Risher envisions a model where individuals can own a self-driving car and add it to the Lyft platform, trading their vehicle's time for money instead of their own.
The integration of AI into human-led services will mirror Tesla's approach to self-driving. Humans will remain the primary interface (the "steering wheel"), while AI progressively automates backend tasks, enhancing capability rather than eliminating the human role entirely in the near term.
The 1X robot's teleoperation, often seen as a sign of immaturity, is actually a key feature. It allows for both a "human-in-the-loop" expert service for complex tasks and personal remote control, like checking on a pet, creating immediate utility beyond full autonomy.
Instead of creating bespoke self-driving kits for every car model, a humanoid robot can physically sit in any driver's seat and operate the controls. This concept, highlighted by George Hotz, bypasses proprietary vehicle systems and hardware lock-in, treating the car as a black box.
The seamless experience of an autonomous vehicle hides a complex backend. A subsidiary company, FlexDrive, manages a fleet for services like cleaning, charging, maintenance, and teleoperation. This "fleet management" layer represents a significant, often overlooked, part of the AV value chain and business model.
A user speculates on a future where you could buy a humanoid robot, get hired by the robot's manufacturer as a remote operator, and then get paid (with benefits) to teleoperate your own robot to do chores in your own house. This highlights a potential, albeit absurd, evolution of labor markets.
Companies developing humanoid robots, like One X, market a vision of autonomy but will initially ship a teleoperated product. This "human-in-the-loop" model allows them to enter the market and gather data while full autonomy is still in development.
While Figure's CEO criticizes competitors for using human operators in robot videos, this 'wizard of oz' technique is a critical data-gathering and development stage. Just as early Waymo cars had human operators, teleoperation is how companies collect the training data needed for true autonomy.
To achieve scalable autonomy, Flywheel AI avoids expensive, site-specific setups. Instead, they offer a valuable teleoperation service today. This service allows them to profitably collect the vast, diverse datasets required to train a generalizable autonomous system, mirroring Tesla's data collection strategy.
Uber's initiative to offer drivers short, digital tasks for money while they wait for passengers marks a new phase in the gig economy. It aims to monetize every moment of a worker's time, effectively merging the roles of gig worker and crowdsourced data labeler to maximize platform labor efficiency.