Investors are pouring money feverishly into solving this challenge, spending over $6 billion on humanoid robots in 2025. And at-home data recording is becoming a booming gig economy all over the world. Data corporations like Scale AI and Encord are recruiting their very own armies of information recorders, while DoorDash pays delivery drivers to film themselves doing chores. And in China, employees in dozens of state-owned robot training centers wear virtual-reality headsets and exoskeletons to show humanoid robots tips on how to open a microwave and wipe down the table.
“There’s numerous demand, and it’s increasing really fast,” says Ali Ansari, CEO of Micro1. He estimates that robotics corporations at the moment are spending greater than $100 million annually to purchase real-world data from his company and others prefer it.
A day within the life
Staff at Micro1 are vetted by an AI agent named Zara that conducts interviews and reviews samples of chore videos. Every week, they submit videos of themselves doing chores around their homes, following a listing of instructions about things like keeping their hands visible and moving at natural speed. The videos are reviewed by each AI and a human and are either accepted or rejected. They’re then annotated by AI and a team of lots of of humans who label the actions within the footage.
“There’s numerous demand, and it’s increasing really fast.”
Ali Ansari, CEO of Micro1
Because this approach to training robots is in its infancy, it’s not clear yet what makes good training data. Still, “it’s essential to give lots and a number of variations for the robot to generalize well for basic navigation and manipulation of the world,” says Ansari.
But many employees say that creating quite a lot of “chore content” of their tiny homes is a challenge. Zeus, a scrappy student living in a humble studio, struggles to record anything beyond ironing his clothes day-after-day. Arjun, a tutor in Delhi, India, takes an hour to make a 15-minute video because he spends a lot time brainstorming recent chores.
“How much content [can be made] in the house? How much content?” he says.
There’s also the sticky query of privacy. Micro1 asks employees not to point out their faces to the camera or reveal personal information equivalent to names, phone numbers, and birth dates. Then it uses AI and human reviewers to remove anything that slips through.
But even without faces, the videos capture an intimate slice of employees’ lives: the interiors of their homes, their possessions, their routines. And understanding what kind of non-public information they is likely to be recording while they’re busy doing chores on camera could be tricky. Reviews of such footage won’t filter out sensitive information beyond probably the most obvious identifiers.
