Tesla workers shared sensitive images

The article reports on how groups of Tesla employees, between 2019 and 2022, privately shared videos and images recorded by customers’ car cameras via an internal messaging system. Tesla workers shared sensitive images recorded by customer.

• The incidents shared include crashes and road rage, and some recordings were made when the cars were parked and turned off.

• Some former employees stated that they could see inside people’s garages and private properties through the recordings.
• Former employees said the computer program they used at work could show the location of recordings, potentially revealing the owner’s location.
• Tesla’s online “Customer Privacy Notice” states that camera recordings remain anonymous and are not linked to the owner or vehicle.
• sensitive images

The report published by Reuters on April 6, 2023, highlights that artificial intelligence systems require human beings to help train machines to learn automated tasks such as driving.

• Tesla has employed hundreds of people in Africa and later the United States to label images to help its cars learn how to recognize pedestrians, street signs, construction vehicles, garage doors, and other objects encountered on the road or at customers’ houses.

The article discusses how Tesla’s use of cameras to collect data for its Autopilot system has resulted in sensitive and embarrassing personal moments being captured and shared by employees.

• Tesla’s Autopilot system has evolved over time, with early versions of the system relying on sonar sensors, radar, and a single front-facing camera.
• Later versions included eight cameras that collected more data and offered more capabilities.

In July 2021, the Dutch data protection authority investigated Tesla’s use of cameras in its vehicles after reports that personal data, including recordings of drivers and passengers, was being collected and shared by employees.

• The DPA ultimately determined that it was the responsibility of the vehicle owners, rather than Tesla, to ensure that their data was being used appropriately.
• However, the DPA emphasized that personal data must be protected and used for a specific purpose.

Tesla’s Autopilot system has faced criticism, with some experts questioning whether the system is safe enough to be used in fully autonomous vehicles.

• In February 2022, Tesla recalled over 362,000 U.S. vehicles to update their Full Self-Driving software after the National Highway Traffic Safety Administration said it could allow vehicles to exceed speed limits and potentially cause crashes at intersections.
• Tesla workers shared sensitive images recorded by customer.

The article highlights the challenges and potential risks involved in developing and deploying autonomous driving systems, as well as the importance of protecting personal data and ensuring that it is being used appropriately.

The article indicates that while Tesla’s online “Customer Privacy Notice” states that camera recordings remain anonymous and are not linked to the owner or vehicle, former employees said the computer program they used at work could show the location of recordings, potentially revealing the owner’s location. Some employees also stated that some recordings appeared to have been made when cars were parked and turned off, and that they could see inside people’s garages and their private properties. The article notes that some former employees were not bothered by the sharing of images, as customers had given their consent or had given up any reasonable expectation of keeping personal data private.

However, others were troubled by the breach of privacy, as the people who buy the car did not know that their privacy was not respected. The article highlights one of the less-noted features of artificial intelligence systems, as they often require armies of human beings to help train machines to learn automated tasks such as driving, and that since about 2016, Tesla has employed hundreds of people in Africa and later the United States to label images to help its cars learn how to recognize pedestrians, street signs, construction vehicles, garage doors, and other objects encountered on the road or at customers’ houses.

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