Roomba is watching
The images were not taken by a person, but by development versions of iRobot’s Roomba J7 series robot vacuum. They were then sent to Scale AI, a startup that contracts workers around the world to label audio, photo, and video data used to train artificial intelligence.
- Image captured by iRobot development devices, being annotated by data labelers.
The images were not taken by a person, but by development versions of iRobot’s Roomba J7 series robot vacuum. They were then sent to Scale AI, a startup that contracts workers around the world to label audio, photo, and video data used to train artificial intelligence.
- Image captured by iRobot development devices, being annotated by data labelers.
Computer vision depends on high-definition cameras, and by our count, around a dozen companies have incorporated front-facing cameras into their robot vacuums for navigation and object recognition—as well as, increasingly, home monitoring. This includes the top three robot vacuum makers by market share: iRobot, which has 30% of the market and has sold over 40 million devices since 2002; Ecovacs, with about 15%; and Roborock, which has about another 15%, according to the market intelligence firm Strategy Analytics. It also includes familiar household appliance makers like Samsung, LG, and Dyson, among others. In all, some 23.4 million robot vacuums were sold in Europe and the Americas in 2021 alone, according to Strategy Analytics.
- Image captured by iRobot development devices, being annotated by data labelers.
Additionally, “lawmakers and enforcers in privacy would view biometrics, including faces, as sensitive information,” says Jessica Rich, a privacy lawyer who served as director of the FTC’s Bureau of Consumer Protection between 2013 and 2017. This is especially the case if any minors are captured on camera, she adds: “Getting consent from the employee [or testers] isn’t the same as getting consent from the child. The employee doesn’t have the capacity to consent to data collection about other individuals—let alone the children that appear to be implicated.” Rich says she wasn’t referring to any specific company in these comments.
- MATTHIEU BOUREL
In the end, the real problem is arguably not that the data labelers shared the images on social media. Rather, it’s that this type of AI training set—specifically, one depicting faces—is far more common than most people understand, notes Milagros Miceli, a sociologist and computer scientist who has been interviewing distributed workers contracted by data annotation companies for years. Miceli was part of a research team that has spoken to multiple labelers who have seen similar images, taken from the same low vantage points and sometimes showing people in various stages of undress.
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