Uber now wants a lot more from its drivers than just completed trips. The company plans to use drivers’ cars as mobile data collection tools for autonomous vehicle companies training self-driving systems.
The proposal came from TechCrunch during an interview with Uber chief technology officer Praveen Neppalli Naga at the StrictlyVC event in San Francisco.
“That is the direction we want to go eventually,” Naga said of equipping human drivers’ vehicles. “But first we need to get the understanding of the sensor kits and how they all work. There are some regulations – we have to make sure every state has [clarity on] what sensors mean, and what sharing it means.”
Uber already runs a smaller programme called AV Labs using company owned vehicles fitted with sensors. The long term idea is much larger. Uber has millions of drivers worldwide, giving it access to roads, traffic conditions, junctions and driving behaviour across countless cities every day.
Impact Newswire says the proposal is “a distributed network of moving sensors” capable of collecting far more driving data than a single autonomous vehicle company could gather alone.
The timing is worth noting because if you’ll remember, Uber no longer builds its own self-driving cars. The company sold its self-driving unit in 2020 and now works with autonomous vehicle developers instead. Uber has partnerships with 25 autonomous vehicle companies, including Wayve in London.
Are Drivers Helping To Train Their Replacements?
That question hangs over the entire proposal because the data collected today could help autonomous vehicles operate without human drivers tomorrow.
Naga openly explained that autonomous vehicle companies need more real world data to improve their systems. “The bottleneck is data,” he said.
“[Companies like Waymo] need to go around and collect the data, collect different scenarios. You may be able to say: In San Francisco, ‘At this school intersection, I want some data at this time of day so I can train my models.’ The problem for all these companies is access to that data, because they don’t have the capital to deploy the cars and go collect all this information.”
Uber already has the vehicles and the drivers moving through those streets every day. That gives the company something autonomous vehicle developers badly need.
The arrangement does however bring up some difficult questions for drivers. Human drivers would continue doing the work, covering fuel, maintenance and vehicle costs, while the information collected during those journeys could help self-driving systems become more capable.
Impact Newswire reported that questions around “data privacy, driver consent, and compensation” are likely to receive attention if Uber moves forward with the proposal at scale.
Uber says the project is about access to information rather than profit. “Our goal is not to make money out of this data,” Naga said. “We want to democratize it.”
That statement may face a lot of critique because large scale driving data has commercial value. TechCrunch reported that Uber is already investing directly in autonomous vehicle companies and building what Naga calls an “AV cloud” containing labelled sensor data.
What Does Uber Gain From Becoming The Data Layer?
Uber’s long term position in transport has become uncertain as robotaxi technology improves. Autonomous vehicle companies could eventually operate ride services without relying on human drivers.
TechCrunch reported that many people in the sector have questioned whether Uber could one day become irrelevant if autonomous vehicle companies build their own transport networks.
And Uber’s answer? Infrastructure, it seems. Instead of manufacturing self-driving cars, the company wants to become the system connecting passengers, autonomous vehicle operators and now training data.
The company is also developing a system allowing autonomous vehicle partners to run software in “shadow mode” during real Uber trips. That lets developers simulate how a self-driving vehicle would behave during an actual journey without placing a robotaxi on the road.
Impact Newswire said Uber’s scale gives it a potential goldmine of driving insights because millions of trips happen daily across different cities and road conditions.
Drivers may eventually find themselves in a tricky position. Their work would keep the platform running while also helping autonomous systems learn how to replace human labour.
Uber presents the idea as shared progress for the autonomous vehicle ecosystem. Drivers may see it as unpaid training work for the machines coming after their jobs.
