A French startup that set out to bring a new approach to driver education and road safety, and then used that foothold to expand into the related area of car insurance, is today announcing a big round of funding to continue building its service across Europe.
Ornikar, which prepares people for driving tests by providing online drivers education courses, lets those users organize in-person lessons with driving instructors, provides a booking system for taking their written and practical examinations, and finally provides them with competitive rates for getting car insurance as new drivers, has raised €100 million ($120 million).
The company intends to use the funding to expand its business. Drivers education services are live today in France and Spain, while insurance is offered today only in France: the plan will be to expand both of those to more markets.
The Series C is being led by KKR, with previous investors Idinvest, BPI, Elaia, Brighteye, and H14 also participating. Benjamin Gaignault, Ornikar’s CEO who co-founded the company with Flavien LeRendu (who also jointly holds the title of CEO), said the startup is not disclosing its valuation, but we understand from a source that it is around $750 million. The company has raised $175 million to date.
Ornikar has been around since 2013 and was founded, in Gaignault’s words, “to disrupt driving education.”
Coming into the market at a time when most of the process of organizing, learning and booking your driving education was not only very fragmented but completely offline, Ornikar’s internet-based offering represented a step change in how French people learned to drive: the process not only became easier, but on average about 40% cheaper to arrange.
Ornikar’s driving education business today includes not just online course materials and booking services, but a network of instructors across 1,000 towns and cities in France, and a business that launched last year in Spain, under the Onroad brand. Some 1.5 million people have taken Ornikar’s driving education courses to date, with another 2 million using its driving school, with growth accelerating: 420,000 new customers signed up with Ornikar in the last year alone.
Last year was a tricky one for companies in the business of transportation. People were generally staying put and not traveling anywhere, but when they were getting around, they wanted plenty of their own space to do so.
Translating that to markets like France and Spain where many towns will have solid public transportation and taxi services, people might have opted to use these less, looking instead to private vehicles in their place. And translating that to Ornikar, Gaignault said that people being at home more, and looking to use the time productively with a view to driving more in the future, the startup saw business growing by 30% each month last year.
Interestingly, it was in the middle of the pandemic that Ornikar launched its car insurance product, which came out of the same impetus as the driver education services: it was built to fill a hole in the market rethought with Ornikar’s users in mind.
Car insurance in France — a €17 billion ($20 billion) market annually — is dominated by big players, and when it comes to first-time drivers and looking for competitive rates, “the bigger companies are not comfortable with user experience,” said Gaignault. “It’s pretty poor and not aligned with expectations of the customers.”
The car insurance product — sold as Ornikar Assurance — is now on track to hit some 20,000 users by August (when it will have been in the market for a year).
While it accounts today for a small fraction of Ornikar’s revenues compared to its driver education platform, that take up — not just from alums of Ornikar’s drivers ed, but from those who had never used an Ornikar service before — is a good sign that it’s on to something big, Gaignault said.
“In October we noticed that 80% of our new insurance customers were not coming from Ornikar but from social media, Google ads and other outside sources,” he said. “That’s why we decided to create a new business unit and explore a business as an insuretech.”
But, he added, that will not be at the expense of the driving education: the two go hand in hand for a common goal of improving how people drive and improving road safety. Indeed, Gaignault said he envisions a time when one will feed into the other: not only will the driving school serve as a way of bringing in new insurance customers, but insurance rates can be impacted by how many driving courses a person takes to keep their knowledge of the driving code and best practices fresh.
“Ornikar has done a tremendous job creating a great experience for students and driving instructors through engaging online education courses and a well-designed marketplace,” said Patrick Devine, director at KKR and member of the Next Generation Technology Growth investment team. “We are thrilled to invest behind Benjamin, Flavien, and their talented team as they expand internationally and accelerate their insurance offering following the successful launches of Onroad in Spain and Ornikar Assurance.”
Labor activists challenging Uber over what they allege are ‘robo-firings’ of drivers in Europe have trumpeted winning a default judgement in the Netherlands — where the Court of Amsterdam ordered the ride-hailing giant to reinstate six drivers who the litigants claim were unfairly terminated “by algorithmic means”.
The court also ordered Uber to pay the fired drivers compensation.
The challenge references Article 22 of the European Union’s General Data Protection Regulation (GDPR) — which provides protects for individuals against purely automated decisions with a legal or significant impact.
The activists say this is the first time a court has ordered the overturning of an automated decision to dismiss workers from employment.
However the judgement, which was issued on February 24, was issued by default — and Uber says it was not aware of the case until last week, claiming that was why it did not contest it (nor, indeed, comply with the order).
It had until March 29 to do so, per the litigants, who are being supported by the App Drivers & Couriers Union (ADCU) and Worker Info Exchange (WIE).
Uber argues the default judgement was not correctly served and says it is now making an application to set the default ruling aside and have its case heard “on the basis that the correct procedure was not followed”.
It envisages the hearing taking place within four weeks of its Dutch entity, Uber BV, being made aware of the judgement — which it says occurred on April 8.
“Uber only became aware of this default judgement last week, due to representatives for the ADCU not following proper legal procedure,” an Uber spokesperson told TechCrunch.
A spokesperson for WIE denied that correct procedure was not followed but welcomed the opportunity for Uber to respond to questions over how its driver ID systems operate in court, adding: “They [Uber] are out of time. But we’d be happy to see them in court. They will need to show meaningful human intervention and provide transparency.”
Uber pointed to a separate judgement by the Amsterdam Court last month — which rejected another ADCU- and WIE-backed challenge to Uber’s anti-fraud systems, with the court accepting its explanation that algorithmic tools are mere aids to human ‘anti-fraud’ teams who it said take all decisions on terminations.
“With no knowledge of the case, the Court handed down a default judgement in our absence, which was automatic and not considered. Only weeks later, the very same Court found comprehensively in Uber’s favour on similar issues in a separate case. We will now contest this judgement,” Uber’s spokesperson added.
However WIE said this default judgement ‘robo-firing’ challenge specifically targets Uber’s Hybrid Real Time ID System — a system that incorporates facial recognition checks and which labor activists recently found mis-identifying drivers in a number of instances.
It also pointed to a separate development this week in the UK where it said the City of London Magistrates Court ordered the city’s transport regulator, TfL, to reinstate the licence of one of the drivers revoked after Uber routinely notified it of a dismissal (also triggered by Uber’s real time ID system, per WIE).
Reached for comment on that, a TfL spokesperson said: “The safety of the travelling public is our top priority and where we are notified of cases of driver identity fraud, we take immediate licensing action so that passenger safety is not compromised. We always require the evidence behind an operator’s decision to dismiss a driver and review it along with any other relevant information as part of any decision to revoke a licence. All drivers have the right to appeal a decision to remove a licence through the Magistrates’ Court.”
Since then Uber has been able to continue to operate in the UK capital but the company remains under pressure to comply with a laundry list of requirements set by TfL as it tries to regain a full operator licence.
Commenting on the default Dutch judgement on the Uber driver terminations in a statement, James Farrar, director of WIE, accused gig platforms of “hiding management control in algorithms”.
“For the Uber drivers robbed of their jobs and livelihoods this has been a dystopian nightmare come true,” he said. “They were publicly accused of ‘fraudulent activity’ on the back of poorly governed use of bad technology. This case is a wake-up call for lawmakers about the abuse of surveillance technology now proliferating in the gig economy. In the aftermath of the recent UK Supreme Court ruling on worker rights gig economy platforms are hiding management control in algorithms. This is misclassification 2.0.”
In another supporting statement, Yaseen Aslam, president of the ADCU, added: “I am deeply concerned about the complicit role Transport for London has played in this catastrophe. They have encouraged Uber to introduce surveillance technology as a price for keeping their operator’s license and the result has been devastating for a TfL licensed workforce that is 94% BAME. The Mayor of London must step in and guarantee the rights and freedoms of Uber drivers licensed under his administration.”
When pressed on the driver termination challenge being specifically targeted at its Hybrid Real-Time ID system, Uber declined to comment in greater detail — claiming the case is “now a live court case again”.
But its spokesman suggested it will seek to apply the same defence against the earlier ‘robo-firing’ charge — when it argued its anti-fraud systems do not equate to automated decision making under EU law because “meaningful human involvement [is] involved in decisions of this nature”.
Elon Musk famously said any company relying on lidar is “doomed.” Tesla instead believes automated driving functions are built on visual recognition and is even working to remove the radar. China’s Xpeng begs to differ.
Founded in 2014, Xpeng is one of China’s most celebrated electric vehicle startups and went public when it was just six years old. Like Tesla, Xpeng sees automation as an integral part of its strategy; unlike the American giant, Xpeng uses a combination of radar, cameras, high-precision maps powered by Alibaba, localization systems developed in-house, and most recently, lidar to detect and predict road conditions.
“Lidar will provide the 3D drivable space and precise depth estimation to small moving obstacles even like kids and pets, and obviously, other pedestrians and the motorbikes which are a nightmare for anybody who’s working on driving,” Xinzhou Wu, who oversees Xpeng’s autonomous driving R&D center, said in an interview with TechCrunch.
“On top of that, we have the usual radar which gives you location and speed. Then you have the camera which has very rich, basic semantic information.”
Xpeng is adding lidar to its mass-produced EV model P5, which will begin delivering in the second half of this year. The car, a family sedan, will later be able to drive from point A to B based on a navigation route set by the driver on highways and certain urban roads in China that are covered by Alibaba’s maps. An older model without lidar already enables assisted driving on highways.
The system, called Navigation Guided Pilot, is benchmarked against Tesla’s Navigate On Autopilot, said Wu. It can, for example, automatically change lanes, enter or exit ramps, overtake other vehicles, and maneuver another car’s sudden cut-in, a common sight in China’s complex road conditions.
“The city is super hard compared to the highway but with lidar and precise perception capability, we will have essentially three layers of redundancy for sensing,” said Wu.
By definition, NGP is an advanced driver-assistance system (ADAS) as drivers still need to keep their hands on the wheel and take control at any time (Chinese laws don’t allow drivers to be hands-off on the road). The carmaker’s ambition is to remove the driver, that is, reach Level 4 autonomy two to four years from now, but real-life implementation will hinge on regulations, said Wu.
“But I’m not worried about that too much. I understand the Chinese government is actually the most flexible in terms of technology regulation.”
Musk’s disdain for lidar stems from the high costs of the remote sensing method that uses lasers. In the early days, a lidar unit spinning on top of a robotaxi could cost as much as $100,000, said Wu.
“Right now, [the cost] is at least two orders low,” said Wu. After 13 years with Qualcomm in the U.S., Wu joined Xpeng in late 2018 to work on automating the company’s electric cars. He currently leads a core autonomous driving R&D team of 500 staff and said the force will double in headcount by the end of this year.
“Our next vehicle is targeting the economy class. I would say it’s mid-range in terms of price,” he said, referring to the firm’s new lidar-powered sedan.
The lidar sensors powering Xpeng come from Livox, a firm touting more affordable lidar and an affiliate of DJI, the Shenzhen-based drone giant. Xpeng’s headquarters is in the adjacent city of Guangzhou about 1.5 hours’ drive away.
Xpeng isn’t the only one embracing lidar. Nio, a Chinese rival to Xpeng targeting a more premium market, unveiled a lidar-powered car in January but the model won’t start production until 2022. Arcfox, a new EV brand of Chinese state-owned carmaker BAIC, recently said it would be launching an electric car equipped with Huawei’s lidar.
Musk recently hinted that Tesla may remove radar from production outright as it inches closer to pure vision based on camera and machine learning. The billionaire founder isn’t particularly a fan of Xpeng, which he alleged owned a copy of Tesla’s old source code.
In 2019, Tesla filed a lawsuit against Cao Guangzhi alleging that the former Tesla engineer stole trade secrets and brought them to Xpeng. XPeng has repeatedly denied any wrongdoing. Cao no longer works at Xpeng.
While Livox claims to be an independent entity “incubated” by DJI, a source told TechCrunch previously that it is just a “team within DJI” positioned as a separate company. The intention to distance from DJI comes as no one’s surprise as the drone maker is on the U.S. government’s Entity List, which has cut key suppliers off from a multitude of Chinese tech firms including Huawei.
Other critical parts that Xpeng uses include NVIDIA’s Xavier system-on-the-chip computing platform and Bosch’s iBooster brake system. Globally, the ongoing semiconductor shortage is pushing auto executives to ponder over future scenarios where self-driving cars become even more dependent on chips.
Xpeng is well aware of supply chain risks. “Basically, safety is very important,” said Wu. “It’s more than the tension between countries around the world right now. Covid-19 is also creating a lot of issues for some of the suppliers, so having redundancy in the suppliers is some strategy we are looking very closely at.”
Xpeng could have easily tapped the flurry of autonomous driving solution providers in China, including Pony.ai and WeRide in its backyard Guangzhou. Instead, Xpeng becomes their competitor, working on automation in-house and pledges to outrival the artificial intelligence startups.
“The availability of massive computing for cars at affordable costs and the fast dropping price of lidar is making the two camps really the same,” Wu said of the dynamics between EV makers and robotaxi startups.
“[The robotaxi companies] have to work very hard to find a path to a mass-production vehicle. If they don’t do that, two years from now, they will find the technology is already available in mass production and their value become will become much less than today’s,” he added.
“We know how to mass-produce a technology up to the safety requirement and the quarantine required of the auto industry. This is a super high bar for anybody wanting to survive.”
Xpeng has no plans of going visual-only. Options of automotive technologies like lidar are becoming cheaper and more abundant, so “why do we have to bind our hands right now and say camera only?” Wu asked.
“We have a lot of respect for Elon and his company. We wish them all the best. But we will, as Xiaopeng [founder of Xpeng] said in one of his famous speeches, compete in China and hopefully in the rest of the world as well with different technologies.”
5G, coupled with cloud computing and cabin intelligence, will accelerate Xpeng’s path to achieve full automation, though Wu couldn’t share much detail on how 5G is used. When unmanned driving is viable, Xpeng will explore “a lot of exciting features” that go into a car when the driver’s hands are freed. Xpeng’s electric SUV is already available in Norway, and the company is looking to further expand globally.
Despite the classification of ride-hail drivers as “essential workers” during the early days of the pandemic, last April Uber’s business dropped by 80%. Drivers decided they’d rather not risk contracting or spreading COVID-19 for the measly revenue provided by the few rides per day they were getting, so when the federal CARES Act extended the Pandemic Unemployment Assistance to gig workers, many Uber drivers decided to hang up their keys.
With more than a quarter of the U.S. population already vaccinated, Uber is now in a sticky situation wherein there are more riders requesting trips than there are drivers available. The ride-hailing giant not only wants drivers to know that there’s business to be had once again, but they also want to sweeten the deal with incentives.
On Wednesday, the company announced the launch of a $250 million driver stimulus to welcome drivers back into the fold and recruit new ones as the pandemic begins to ease in the U.S. Both returning drivers and new drivers will be receiving bonuses over the coming months, according to an Uber spokesperson.
“In 2020, many drivers stopped driving because they couldn’t count on getting enough trips to make it worth their time,” reads the blog post announcing the stimulus. “In 2021, there are more riders requesting trips than there are drivers available to give them—making it a great time to be a driver.”
Due to high rider demand and low supply of drivers, the current median hourly rate for cities like Philadelphia, Austin, Chicago, Miami and Phoenix is $26.66, which is 25% to 75% higher than they were in March of last year. Uber wants drivers to take advantage of the higher earnings now because “this is likely a temporary situation.” Meaning as the country recovers and more gig workers get back behind the wheel, earnings will likely decrease from their current levels.
The stimulus money will go on top of those hourly rates, a spokesperson told TechCrunch. The incentive structure will be based on individual activity, as well as location. For example, in Austin, drivers are guaranteed $1,100 if they complete 115 trips. In Phoenix, drivers can earn an extra $1,775 for 200 trips.
The money will also go towards guaranteed minimum pay and on-boarding for new Uber drivers, and the full $250 million pool is coming directly from Uber’s pockets. The company’s shares declined as much as 3.6% during trading on Wednesday.
Uber is also aiming to help streamline the process of getting drivers vaccinated with an in-app booking portal as part of its partnership with Walgreens.
Self-driving and robotics startup Cartken has partnered with REEF Technology, a startup that operates parking lots and neighborhood hubs, to bring self-driving delivery robots to the streets of downtown Miami.
With this announcement, Cartken officially comes out of stealth mode. The company, founded by ex-Google engineers and colleagues behind the unrequited Bookbot, was formed to develop market-ready tech in self-driving, AI-powered robotics and delivery operations in 2019, but the team has kept operations under wraps until now. This is Cartken’s first large deployment of self-driving robots on sidewalks.
After a few test months, the REEF-branded electric-powered robots are now delivering dinner orders from REEF’s network of delivery-only kitchens to people located within a 3/4-mile radius in downtown Miami. The robots, which are insulated and thus can preserve the heat of a plate of spaghetti or other hot food, are pre-stationed at designated logistics hubs and dispatched with orders for delivery as the food is prepared.
“We want to show how future-forward Miami can be,” Matt Lindenberger, REEF’s chief technology officer, told TechCrunch. “This is a great chance to show off the capabilities of the tech. The combination of us having a big presence in Miami, the fact that there are a lot of challenges around congestion as Covid subsides, still shows a really good environment where we can show how this tech can work.”
Lindenberg said Miami is a great place to start, but it’s just the beginning, with potential for the Cartken robots to be used for REEF’s other last-mile delivery businesses. Currently, only two restaurant delivery robots are operating in Miami, but Lindenberger said the company is planning to expand further into the city and outward into Fort Lauderdale, as well as other large metros the company operates in, such as Dallas, Atlanta, Los Angeles and eventually New York.
Lindenberger is hoping the presence of robots in the streets can act as a “force multiplier” allowing them to scale while maintaining quality of service in a cost-effective way.
“We’re seeing an explosion in deliveries right now in a post-pandemic world and we foresee that to continue, so these types of no-contact, zero-emission automation techniques are really critical,” he said.
Cartken’s robots are powered by a combination of machine learning and rules-based programming to react to every situation that could occur, even if that just means safely stopping and asking for help, Christian Bersch, CEO of Cartken, told TechCrunch. REEF would have supervisors on site to remotely control the robot if needed, a caveat that was included in the 2017 legislation that allowed for the operation of self-driving delivery robots in Florida.
“The technology at the end of the day is very similar to that of a self-driving car,” said Bersch. “The robot is seeing the environment, planning around obstacles like pedestrians or lampposts. If there’s an unknown situation, someone can help the robot out safely because it can stop on a dime. But it’s important to also have that level of autonomy on the robot because it can react in a split second, faster than anybody remotely could, if something happens like someone jumps in front of it.”
REEF marks specific operating areas on the map for the robots and Cartken tweaks the configuration for the city, accounting for specific situations a robot might need to deal with, so that when the robots are given a delivery address, they can make moves and operate like any other delivery driver. Only this driver has an LTE connection and is constantly updating its location so REEF can integrate it into its fleet management capabilities.
Eventually, Lindenberger said, they’re hoping to be able to offer the option for customers to choose robot delivery on the major food delivery platforms REEF works with like Postmates, UberEats, DoorDash or GrubHub. Customers would receive a text when the robot arrives so they could go outside and meet it. However, the tech is not quite there yet.
Currently the robots only make it street-level, and then the food is passed off to a human who delivers it directly to the door, which is a service that most customers prefer. Navigating into an apartment complex and to a customer’s unit is difficult for a robot to manage just yet, and many customers aren’t quite ready to interact directly with a robot.
“It’s an interim step, but this was a path for us to move forward quickly with the technology without having any other boundaries,” said Lindenberger. “Like with any new tech, you want to take it in steps. So a super important step which we’ve now taken and works very well is the ability to dispatch robots within a certain radius and know that they’re going to arrive there. That in and of itself is a huge step and it allows us to learn what kind of challenges you have in terms of that very last step. Then we can begin to work with Cartken to solve that last piece. It’s a big step just being able to do this automation.”
Motional will integrate its driverless technology into Hyundai’s new all-electric SUV to create the company’s first robotaxi. At the start of 2023, customers in certain markets will be able to book the fully electric, fully autonomous taxi through the Lyft app.
The Hyundai IONIQ 5, which was revealed in February with a consumer release date expected later this year, will be fully integrated with Motional’s driverless system. The vehicles will be equipped with the hardware and software needed for Level 4 autonomous driving capabilities, including LiDAR, radar and cameras to provide the vehicle’s sensing system with 360 degrees of vision, and the ability to see up to 300 meters away. This level of driverless technology means a human will not be required to take over driving.
The interior living space will be similar to the consumer model, but additionally equipped with features needed for robotaxi operation, according to a Motional spokesperson. Motional did not reveal whether or not the vehicle would still have a steering wheel, and images of the robotaxi aren’t yet available.
Motional’s IONIQ 5 robotaxis have already begun testing on public roads and closed courses, and they’ll be put through more months of testing and real-world experience before being deployed on Lyft’s platform. The company says it’ll complete testing only once it’s confident that the taxis are safer than a human driver.
Motional, the Aptiv-Hyundai $4 billion joint venture aimed at commercializing driverless cars, announced its partnership with Lyft in December, signaling the ride-hailing company’s primary involvement in Motional’s plans. The company recently announced that it began testing its driverless tech on public roads in Las Vegas. Hyundai’s IONIQ 5 is Motional’s second platform to go driverless on public roads.
The coming wave of electric vehicles will require more than thousands of charging stations. In addition to being installed, they also need to work — and today, that isn’t happening.
If a station doesn’t send out an error or a driver doesn’t report it, network providers might never know there’s even a problem. Kameale C. Terry, who co-founded ChargerHelp!, an on-demand repair app for electric vehicle charging stations, has seen these issues firsthand.
One customer assumed that poor usage rates at a particular station was due to a lack of EVs in the area, Terry recalled in a recent interview. That wasn’t the problem.
“There was an abandoned vehicle parked there and the station was surrounded by mud,” said Terry who is CEO and co-founded the company with Evette Ellis.
Demand for ChargerHelp’s service has attracted customers and investors. The company said it has raised $2.75 million from investors Trucks VC, Kapor Capital, JFF, Energy Impact Partners and The Fund. This round values the startup, which was founded in January 2020, at $11 million post-money.
The funds will be used to build out its platform, hire beyond its 27-person workforce and expand its service area. ChargerHelp works directly with the charging manufacturers and network providers.
“Today when a station goes down there’s really no troubleshooting guidance,” said Terry, noting that it takes getting someone out into the field to run diagnostics on the station to understand the specific problem. After an onsite visit, a technician then typically shares data with the customer, and then steps are taken to order the correct and specific part — a practice that often doesn’t happen today.
While ChargerHelp is couched as an on-demand repair app, it is also acts as a preventative maintenance service for its customers.
The idea for ChargerHelp came from Terry’s experience working at EV Connect, where she held a number of roles, including head of customer experience and director of programs. During her time there, she worked with 12 manufacturers, which gave her knowledge into inner workings and common problems with the chargers.
It was here that she spotted a gap in the EV charging market.
“When the stations went down we really couldn’t get anyone on site because most of the issues were communication issues, vandalism, firmware updates or swapping out a part — all things that were not electrical,” Terry said.
And yet, the general practice was to use electrical contractors to fix issues at the charging stations. Terry said it could take as long as 30 days to get an electrical contractor on site to repair these non-electrical problems.
Terry often took matters in her own hands if issues arose with stations located in Los Angeles, where she is based.
“If there was a part that needed to be swapped out, I would just go do it myself,” Terry said, adding she didn’t have a background in software or repairs. “I thought, if I can figure this stuff out, then anyone can.”
In January 2020, Terry quit her job and started ChargerHelp. The newly minted founder joined the Los Angeles Cleantech Incubator, where she developed a curriculum to teach people how to repair EV chargers. It was here that she met Ellis, a career coach at LACI who also worked at the Long Beach Job Corp Center. Ellis is now the chief workforce officer at ChargerHelp.
Since then, Terry and Ellis were accepted into Elemental Excelerator’s startup incubator, raised about $400,000 in grant money, launched a pilot program with Tellus Power focused on preventative maintenance and landed contracts with EV charging networks and manufacturers such as EV Connect, ABB and SparkCharge. Terry said they have also hired their core team of seven employees and trained their first tranche of technicians.
ChargerHelp takes a workforce-development approach to finding employees. The company only hires in cohorts, or groups, of employees.
The company received more than 1,600 applications in its first recruitment round for electric vehicle service technicians, according to Terry. Of those, 20 were picked to go through training and 18 were ultimately hired to service contracts across six states, including California, Oregon, Washington, New York and Texas. Everyone picked to go through training is paid a stipend and earn two safety licenses.
The startup will begin its second recruitment round in April. All workers are full-time with a guaranteed wage of $30 an hour and are being given shares in the startup, Terry said. The company is working directly with workforce development centers in the areas where ChargerHelp needs technicians.
Uber’s use of facial recognition technology for a driver identity system is being challenged in the U.K., where the App Drivers & Couriers Union (ADCU) and Worker Info Exchange (WIE) have called for Microsoft to suspend the ride-hailing giant’s use of B2B facial recognition after finding multiple cases where drivers were mis-identified and went on to have their licence to operate revoked by Transport for London (TfL).
The union said it has identified seven cases of “failed facial recognition and other identity checks” leading to drivers losing their jobs and licence revocation action by TfL.
When Uber launched the “Real Time ID Check” system in the U.K. in April 2020, it said it would “verify that driver accounts aren’t being used by anyone other than the licensed individuals who have undergone an Enhanced DBS check”. It said then that drivers could “choose whether their selfie is verified by photo-comparison software or by our human reviewers”.
In one misidentification case the ADCU said the driver was dismissed from employment by Uber and his licence was revoked by TfL. The union adds that it was able to assist the member to establish his identity correctly, forcing Uber and TfL to reverse their decisions. But it highlights concerns over the accuracy of the Microsoft facial recognition technology — pointing out that the company suspended the sale of the system to U.S. police forces in the wake of the Black Lives Matter protests of last summer.
Research has shown that facial recognition systems can have an especially high error rate when used to identify people of color — and the ADCU cites a 2018 MIT study that found Microsoft’s system can have an error rate as high as 20% (accuracy was lowest for dark-skinned women).
The union said it’s written to the mayor of London to demand that all TfL private-hire driver licence revocations based on Uber reports using evidence from its Hybrid Real Time Identification systems are immediately reviewed.
Microsoft has been contacted for comment on the call for it to suspend Uber’s licence for its facial recognition tech.
The ADCU said Uber rushed to implement a workforce electronic surveillance and identification system as part of a package of measures implemented to regain its license to operate in the U.K. capital.
Back in 2017, TfL made the shocking decision not to grant Uber a licence renewal — ratcheting up regulatory pressure on its processes and maintaining this hold in 2019 when it again deemed Uber “not fit and proper” to hold a private hire vehicle licence.
Safety and security failures were a key reason cited by TfL for withholding Uber’s licence renewal.
Uber has challenged TfL’s decision in court and it won another appeal against the licence suspension last year — but the renewal granted was for only 18 months (not the full five years). It also came with a laundry list of conditions — so Uber remains under acute pressure to meet TfL’s quality bar.
Now, though, Labor activists are piling pressure on Uber from the other direction too — pointing out that no regulatory standard has been set around the workplace surveillance technology that the ADCU says TfL encouraged Uber to implement. No equalities impact assessment has even been carried out by TfL, it adds.
WIE confirmed to TechCrunch that it’s filing a discrimination claim in the case of one driver, called Imran Raja, who was dismissed after Uber’s Real ID check — and had his licence revoked by TfL.
His licence was subsequently restored — but only after the union challenged the action.
A number of other Uber drivers who were also misidentified by Uber’s facial recognition checks will be appealing TfL’s revocation of their licences via the U.K. courts, per WIE.
A spokeswoman for TfL told us it is not a condition of Uber’s licence renewal that it must implement facial recognition technology — only that Uber must have adequate safety systems in place.
The relevant condition of its provisional licence on “driver identity” states:
ULL shall maintain appropriate systems, processes and procedures to confirm that a driver using the app is an individual licensed by TfL and permitted by ULL to use the app.
We’ve also asked TfL and the U.K.’s Information Commissioner’s Office for a copy of the data protection impact assessment Uber says was carried before the Real-Time ID Check was launched — and will update this report if we get it.
Uber, meanwhile, disputes the union’s assertion that its use of facial recognition technology for driver identity checks risks automating discrimination because it says it has a system of manual (human) review in place that’s intended to prevent failures.
Albeit it accepts that that system clearly failed in the case of Raja — who only got his Uber account back (and an apology) after the union’s intervention.
Uber said its Real-Time ID system involves an automated “picture matching” check on a selfie that the driver must provide at the point of log in, with the system comparing that selfie with a (single) photo of them held on file.
If there’s no machine match, the system sends the query to a three-person human review panel to conduct a manual check. Uber said checks will be sent to a second human panel if the first can’t agree.
In a statement the tech giant told us:
Our Real-Time ID Check is designed to protect the safety and security of everyone who uses the app by ensuring the correct driver or courier is using their account. The two situations raised do not reflect flawed technology — in fact one of the situations was a confirmed violation of our anti-fraud policies and the other was a human error.
“While no tech or process is perfect and there is always room for improvement, we believe the technology, combined with the thorough process in place to ensure a minimum of two manual human reviews prior to any decision to remove a driver, is fair and important for the safety of our platform.
In two of the cases referred to by the ADCU, Uber said that in one instance a driver had shown a photo during the Real-Time ID Check instead of taking a selfie as required to carry out the live ID check — hence it argues it was not wrong for the ID check to have failed as the driver was not following the correct protocol.
In the other instance Uber blamed human error on the part of its manual review team(s) who (twice) made an erroneous decision. It said the driver’s appearance had changed and its staff were unable to recognize the face of the (now bearded) man who sent the selfie as the same person in the clean-shaven photo Uber held on file.
Uber was unable to provide details of what happened in the other five identity check failures referred to by the union.
It also declined to specify the ethnicities of the seven drivers the union says were misidentified by its checks.
Asked what measures it’s taking to prevent human errors leading to more misidentifications in the future, Uber declined to provide a response.
Uber said it has a duty to notify TfL when a driver fails an ID check — a step that can lead to the regulator suspending the license, as happened in Raja’s case. So any biases in its identity check process clearly risk having disproportionate impacts on affected individuals’ ability to work.
WIE told us it knows of three TfL licence revocations that relate solely to facial recognition checks.
“We know of more [UberEats] couriers who have been deactivated but no further action since they are not licensed by TfL,” it noted.
TechCrunch also asked Uber how many driver deactivations have been carried out and reported to TfL in which it cited facial recognition in its testimony to the regulator — but again the tech giant declined to answer our questions.
WIE told us it has evidence that facial recognition checks are incorporated into geo-location-based deactivations Uber carries out.
It said that in one case a driver who had their account revoked was given an explanation by Uber relating solely to location but TfL accidentally sent WIE Uber’s witness statement — which it said “included facial recognition evidence”.
That suggests a wider role for facial recognition technology in Uber’s identity checks versus the one the ride-hailing giant gave us when explaining how its Real-Time ID system works. (Again, Uber declined to answer follow-up questions about this or provide any other information beyond its on-the-record statement and related background points.)
But even just focusing on Uber’s Real-Time ID system there’s the question of how much say Uber’s human review staff actually have in the face of machine suggestions combined with the weight of wider business imperatives (like an acute need to demonstrate regulatory compliance on the issue of safety).
James Farrer, the founder of WIE, queries the quality of the human checks Uber has put in place as a backstop for facial recognition technology, which has a known discrimination problem.
“Is Uber just confecting legal plausible deniability of automated decision making or is there meaningful human intervention,” he told TechCrunch. “In all of these cases, the drivers were suspended and told the specialist team would be in touch with them. A week or so typically would go by and they would be permanently deactivated without ever speaking to anyone.”
“There is research out there to show when facial recognition systems flag a mismatch humans have bias to confirm the machine. It takes a brave human being to override the machine. To do so would mean they would need to understand the machine, how it works, its limitations and have the confidence and management support to over rule the machine,” Farrer added. “Uber employees have the risk of Uber’s license to operate in London to consider on one hand and what… on the other? Drivers have no rights and there are in excess so expendable.”
He also pointed out that Uber has previously said in court that it errs on the side of customer complaints rather than give the driver benefit of the doubt. “With that in mind can we really trust Uber to make a balanced decision with facial recognition?” he asked.
Farrer further questioned why Uber and TfL don’t show drivers the evidence that’s being relied upon to deactivate their accounts — to given them a chance to challenge it via an appeal on the actual substance of the decision.
“IMHO this all comes down to tech governance,” he added. “I don’t doubt that Microsoft facial recognition is a powerful and mostly accurate tool. But the governance of this tech must be intelligent and responsible. Microsoft are smart enough themselves to acknowledge this as a limitation.
“The prospect of Uber pressured into surveillance tech as a price of keeping their licence… and a 94% BAME workforce with no worker rights protection from unfair dismissal is a recipe for disaster!”
The latest pressure on Uber’s business processes follows hard on the heels of a major win for Farrer and other former Uber drivers and labor rights activists after years of litigation over the company’s bogus claim that drivers are “self employed”, rather than workers under U.K. law.
However, the litigants immediately pointed out that Uber’s “deal” ignored the Supreme Court’s assertion that working time should be calculated when a driver logs onto the Uber app. Instead Uber said it would calculate working time entitlements when a driver accepts a job — meaning it’s still trying to avoid paying drivers for time spent waiting for a fare.
The ADCU therefore estimates that Uber’s “offer” underpays drivers by between 40%-50% of what they are legally entitled to — and has said it will continue its legal fight to get a fair deal for Uber drivers.
At an EU level, where regional lawmakers are looking at how to improve conditions for gig workers, the tech giant is now pushing for an employment law carve out for platform work — and has been accused of trying to lower legal standards for workers.
In additional Uber-related news this month, a court in the Netherlands ordered the company to hand over more of the data it holds on drivers, following another ADCU+WIE challenge. Although the court rejected the majority of the drivers’ requests for more data. But notably it did not object to drivers seeking to use data rights established under EU law to obtain information collectively to further their ability to collectively bargain against a platform — paving the way for more (and more carefully worded) challenges as Farrer spins up his data trust for workers.
The applicants also sought to probe Uber’s use of algorithms for fraud-based driver terminations under an article of EU data protection law that provides for a right not to be subject to solely automated decisions in instances where there is a legal or significant effect. In that case the court accepted Uber’s explanation at face value that fraud-related terminations had been investigated by a human team — and that the decisions to terminate involved meaningful human decisions.
But the issue of meaningful human invention/oversight of platforms’ algorithmic suggestions/decisions is shaping up to be a key battleground in the fight to regulate the human impacts of and societal imbalances flowing from powerful platforms which have both god-like view of users’ data and an allergy to complete transparency.
The latest challenge to Uber’s use of facial recognition-linked terminations shows that interrogation of the limits and legality of its automated decisions is far from over — really, this work is just getting started.
Uber’s use of geolocation for driver suspensions is also facing legal challenge.
While pan-EU legislation now being negotiated by the bloc’s institutions also aims to increase platform transparency requirements — with the prospect of added layers of regulatory oversight and even algorithmic audits coming down the pipe for platforms in the near future.
Last week the same Amsterdam court that ruled on the Uber cases also ordered India-based ride-hailing company Ola to disclose data about its facial-recognition-based “Guardian” system — aka its equivalent to Uber’s Real-Time ID system. The court said Ola must provide applicants with a wider range of data than it currently does — including disclosing a “fraud probability profile” it maintains on drivers and data within a “Guardian” surveillance system it operates.
Farrer says he’s thus confident that workers will get transparency — “one way or another”. And after years fighting Uber through U.K. courts over its treatment of workers his tenacity in pursuit of rebalancing platform power cannot be in doubt.
California’s Department of Motor Vehicles is warning of a potential data breach after a contractor was hit by ransomware.
The Seattle-based Automatic Funds Transfer Services (AFTS), which the DMV said it has used for verifying changes of address with the national database since 2019, was hit by an unspecified strain of ransomware earlier this month.
In a statement sent by email, the DMV said that the attack may have compromised “the last 20 months of California vehicle registration records that contain names, addresses, license plate numbers and vehicle identification numbers.” But the DMV said AFTS does not have access to customers’ Social Security numbers, dates of birth, voter registration, immigration status or driver’s license information, and was not compromised.
The DMV said it has since stopped all data transfers to AFTS and has since initiated an emergency contract to prevent any downtime.
AFTS is used across the United States to process payments, invoices and verify addresses. Several municipalities have already confirmed that they are affected by the data breach, suggesting it may not be limited to California’s DMV. But it’s not known what kind of ransomware hit AFTS. Ransomware typically encrypts a company’s files and will unlock them in exchange for a ransom. But since many companies have backups, some ransomware groups threaten to publish the stolen files online unless the ransom is paid.
AFTS could not be immediately reached for comment. Its website is offline, with a short message: “The website for AFTS and all related payment processing website [sic] are unavailable due to technical issues. We are working on restoring them as quickly as possible.”
“We are looking at additional measures to implement to bolster security to protect information held by the DMV and companies that we contract with,” said Steve Gordon, the director of the state’s DMV.
California has more than 35 million registered vehicles.