He would allow the preproduction test version of iRobot’s Roomba J series device to roam around his house, let it collect all sorts of data to help improve its artificial intelligence, and provide feedback to iRobot about his user experience.“The whole idea is that you get to learn about something new, and hopefully be involved in shaping the product, whether it’s making a better-quality release or actually defining features and functionality.” But what Greg didn’t know—and does not believe he consented to—was that iRobot would share test users’ data in a sprawling, global data supply chain, where everything (and every person) captured by the devices’ front-facing cameras could be seen, and perhaps annotated, by low-paid contractors outside the United States who could screenshot and share images at their will.Nearly a dozen people who participated in iRobot’s data collection efforts between 2019 and 2022 have come forward in the weeks since MIT Technology Review published an investigation into how the company uses images captured from inside real homes to train its artificial intelligence.We found that in one 2020 project, gig workers in Venezuela were asked to label objects in a series of images of home interiors, some of which included individuals—their faces visible to the data annotators.We know about these particular images because the screenshots were subsequently shared with us, but our interviews with data annotators and researchers who study data annotation suggest they are unlikely to be the only ones that made their way online; it’s not uncommon for sensitive images, videos, and audio to be shared with labelers."