The cameras it builds into vehicles to assist driving, it notes on its website, are “designed from the ground up to protect your privacy.” This is a representational image. Beat Jau/Unsplash.

Tesla Inc. promises the tens of millions of owners of electric vehicles that "is and will always be enormously important to us" their privacy. According to a statement on its website, the driving assistance cameras the company installs in cars are "designed from the ground up to protect your privacy."

According to interviews conducted by Reuters with nine former employees between 2019 and 2022, however, groups of Tesla employees privately discussed via an internal messaging system occasionally extremely intrusive films and photographs taken by customers' car cameras.

A few of the recordings showed Tesla customers in awkward circumstances.

A video of a man approaching a vehicle while entirely naked was described by one ex-employee.

Accidents and cases of road rage are also shared. According to a different ex-employee, a Tesla was seen in a crash video from 2021 traveling quickly through a residential neighborhood before striking a child riding a bike.

Both the toddler and the bike flew in opposite directions.

The ex-employee claimed that the video circulated "like wildfire" through private one-on-one talks within the Tesla headquarters in San Mateo, California.

Other pictures were more mundane; for example, staff added witty comments or commentary to images of dogs and funny road signs to turn them into memes before uploading them in personal group conversations.

According to multiple former employees, some postings were only visible to two individuals, while others were accessible to hundreds of them.

Tesla claims in its online "Customer Privacy Notice" that its "camera recordings remain anonymous and are not linked to you or your vehicle."

However, seven ex-workers revealed to Reuters that a computer tool they used at the time may expose the location of recordings, which might reveal a Tesla owner's residence.

Additionally, according to one ex-employee, several recordings appeared to have been captured while automobiles were parked and switched off.

Tesla used to be able to obtain video records from its vehicles even when they were not in use if the owners gave permission. Since then, it has ceased to do so.

"We could see inside people's garages and their private properties," said another former employee. "Let's say that a Tesla customer had something in their garage that was distinctive, you know, people would post those kinds of things."

Tesla didn't respond to detailed questions sent to the company for this report, reports Reuters.

According to two persons who watched it, a video of an unusual submersible vehicle parked inside a garage was discovered and shared by several employees about three years ago.

The white Lotus Esprit sub, known as "Wet Nellie," appeared in the 1977 James Bond movie "The Spy Who Loved Me."

Elon Musk, the CEO of Tesla, acquired the car in 2013 at an auction for approximately $968,000. Whether Musk was aware of the film or that it had been circulated is unknown.

To report this story Reuters contacted more than 300 former Tesla employees who had worked at the company over the past nine years and were involved in developing its self-driving system.

Sharing private recordings serves to highlight one of the less-noticed characteristics of AI systems: They frequently need armies of people to assist in teaching machines to master automated operations like driving.

In order to train its cars to recognize pedestrians, street signs, construction vehicles, garage doors, and other items encountered on the road or at customers' homes, Tesla has engaged hundreds of people in Africa and later the United States to classify photographs.

To do that, automobile cameras were used to record thousands of movies or photos that data labelers could see and identify objects in.

Tesla has been automating the process more and more, and last year the company closed a data-labeling hub in San Mateo, California.

However, it still has hundreds of data labelers working for it in Buffalo, New York.

Tesla reported in February that there were now 675 employees, up 54% from the previous six months.

Two former employees claimed that they weren't troubled by the sharing of photographs since either client had given their agreement or people had long since abandoned any hope of keeping personal information secret.

Three others, however, said they were troubled by it.

"It was a breach of privacy, to be honest. And I always joked that I would never buy a Tesla after seeing how they treated some of these people," said one former employee.

"I'm bothered by it because the people who buy the car, I don't think they know that their privacy is, like, not respected ... We could see them doing laundry and really intimate things. We could see their kids," another said.

David Choffnes, executive director of the Cybersecurity and Privacy Institute at Northeastern University in Boston, called sharing of sensitive videos and images by Tesla employees "morally reprehensible."

"Any normal human being would be appalled by this," he said. He noted that circulating sensitive and personal content could be construed as a violation of Tesla's own privacy policy — potentially resulting in intervention by the U.S. Federal Trade Commission, which enforces federal laws relating to consumers' privacy.

According to an FTC representative, the agency doesn't comment on specific businesses or their behavior.

Tesla gathers a large amount of data from its global fleet of several million vehicles to develop self-driving car technology.

Before collecting data from customers' automobiles, the firm requests their consent via the touchscreens in their vehicles.

According to Tesla's website, "Your Data Belongs to You."

In its Customer Privacy Notice, Tesla explains that if a customer agrees to share data, "your vehicle may collect the data and make it available to Tesla for analysis.

This analysis helps Tesla improve its products, and features, and diagnose problems quicker."

It also states that the data may include "short video clips or images," but isn't linked to a customer's account or vehicle identification number, "and does not identify you personally."

The National Highway Traffic Safety Administration warned that the Full Self-Driving software in Tesla's recalled more than 362,000 American vehicles in February, raising the possibility of speeding violations and intersection collisions.

Tesla recruited data labelers to identify items in pictures and videos to train the system how to react while the vehicle is on the road or parked, as is the case with many artificial intelligence projects.

According to Reuters, Tesla initially contracted out data tagging to a San Francisco non-profit organization at the time known as Samasource.

The organization, which had a location in Nairobi, Kenya, specialized in providing underprivileged women and young people with training and job possibilities.

According to a person familiar with the situation, Samasource was sending 400 people there for Tesla in 2016, up from just 20 at first.

Tesla, however, was dissatisfied with Samasource's data labelers' work by 2019.

At an event called Tesla AI Day in 2021, Andrej Karpathy, then senior director of AI at Tesla, said: "Unfortunately, we found very quickly that working with a third party to get data sets for something this critical was just not going to cut it ... Honestly the quality was not amazing."

A former Tesla employee said of the Samasource labelers: "They would highlight fi re hydrants as pedestrians ... They would miss objects all the time. Their skill level to draw boxes was very low."

Samasource, now known as Sama, declined to respond to questions about its work with Tesla.

Tesla decided to bring data labeling in-house. "Over time, we've grown to more than a 1,000-person data labeling (organization) that is full of professional labelers who are working very closely with the engineers," Karpathy said in his August 2021 presentation.

Karpathy didn't respond to requests for comment.

At one point, Teslas using Autopilot had trouble backing out of garages and would become confused when they came across items like garden hoses or shadows. In order to identify objects in movies taken within garages, some data labelers were instructed to.

The issue was eventually resolved.

Two former employees who were interviewed claimed that as part of their regular job responsibilities, they occasionally had to examine pictures of clients in and around their houses, including in garages.

"I sometimes wondered if these people know that we're seeing that," said one.

"I saw some scandalous stuff sometimes, you know, like I did see scenes of intimacy but not nudity," said another. "And there was just definitely a lot of stuff that like, I wouldn't want anybody to see about my life."

As an example, this person recalled seeing "embarrassing objects," such as "certain pieces of laundry, certain sexual wellness items ... and just private scenes of life that we really were privy to because the car was charging."

Several former employees claim that some labelers shared screenshots in private group chats on Tesla's internal messaging platform, Mattermost, often annotated with Adobe Photoshop.

Managers and other employees would respond to them there. To keep the dialogue going, participants would also submit their own annotated pictures, jokes, or emoticons.

According to numerous former employees, several of the emojis were specially made to reference company inside jokes.

Sharing pictures was regarded as a means to "break the monotony" by a former labeler. Another person talked about how sharing earned respect from peers.

"If you saw something cool that would get a reaction, you post it, right, and then later, on break, people would come up to you and say, 'Oh, I saw what you posted. That was funny,'" said this former labeler. "People who got promoted to lead positions shared a lot of these funny items and gained notoriety for being funny."

According to two former employees, one benefit of working as a data labeler for Tesla in San Mateo was the chance to earn a prize: the use of a corporate car for a day or two.

However, several of the fortunate winners developed paranoia while operating the electric vehicles.

According to an ex-employee, "Knowing how much data those vehicles are capable of collecting definitely made folks nervous."

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