A new class of gig-workers in India are teaching robots to do the dishes

**Rachel Varghese** (0:00)
So, before we start today, we have been thinking a lot lately about this show, about what it is, what it could be and about you, the people who show up for it every single morning. And we realized, we don't actually know that much about you.
So, we have made this survey. It takes about three minutes, and we are genuinely asking what's working, what isn't and what you want more of. The link is in the show notes, and we promise to read every single response.
Okay, let's get into it.
Ranjan is a 20-something employee at Deloitte. But unlike most of his co-workers, his workday doesn't end at 5 p.m. Instead, when he gets home at 6.30, he showers, drinks coffee, and then gets down to business. He straps a camera to his forehead and starts recording as he goes about his daily chores, washing and folding laundry, cooking, doing the dishes. Once he begins, though, he moves slower than usual. His movements are deliberate. His hands never leave the frame. He can't record faces, idle for longer than 3 seconds, or shoot in slow motion. These are the conditions of Ranjan's new gig. He is a physical AI trainer and for every task he does, he makes about 250 to 300 rupees. On good evenings, he even makes 1,000. He is part of a new class of gig workers who freelance for data collection companies like MicroOne, EgoData, Human Labs and more to help train robots in human behaviour.
You may remember Pronto, the Bangalore-based home services start-up that made headlines in May for allegedly sending workers equipped with cameras into customers' homes so that they could record similar footage for physical AI training. Of course, Pronto's competitors like Urban Company and Snabbit rushed to reassure their own customers that they would not be doing the same. But backlash aside, it's important to note that Pronto did not create this market. It was already there. In fact, companies like Tesla, Figure AI and Nvidia, all building humanoid robots by the way, had been purchasing footage made by workers like Ranjan long before the Pronto controversy ever made the news. The thing is, this kind of labor supply pattern is not new to India. We saw it first with IT services, then with the BPO or business process outsourcing model. Each wave has brought the country employment and the opportunity to integrate into the global technology stack. Each wave has left India supplying the labor, while others captured the intellectual property. To look at this wave more closely, I have with me in the studio, my colleague Sakshi Sadashiv. She has spent days reporting on the story, speaking to recruiters and workers across the country, studying listings sprinkled across sites like Indeed and nocty.com. What she found suggests that this market is only picking up steam. Which means, this is the question. Is physical AI training just the latest version of that same old Faustian bargain?
Hi, Sakshi, thank you so much for joining us in the studio today. I know this is your first Daybreak episode with us, so before we get into the questions, would you give us a brief introduction about you?

**Sakshi Sadashiv** (4:05)
Of course, thank you for having me. My name is Sakshi, I am a reporter with The Ken. I have been here for close to three months, and I work from Delhi.

**Rachel Varghese** (4:16)
Great, thank you so much for that. So I wanted to start the story with, where you start the story actually, where you talk about Ranjan, who is this physical AI trainer, and for whom this is a side gig, like he has a day job at Deloitte. So could you describe what his day looks like when he's doing the training?

**Sakshi Sadashiv** (4:36)
Of course. So Ranjan works full-time at one of the big fours, and does this after work. He straps an iPhone or any body camera basically, to his chest and opens a task list. This task list has a set of instructions, which means that your phone has to be angled at a certain... which I'll get into a bit later.
The phone has to be angled in a certain way. Your hands, which are the most important thing in this process, have to be visible at all times.
You cannot slow yourself. You cannot like fasten your speed at any point. And he sort of records himself...

**Rachel Varghese** (5:21)
Speed has to be like consistent throughout.

**Sakshi Sadashiv** (5:23)
Like you can't slow down or speed up. So you have to have like a consistent amount of speed.
And they will sometimes have like certain tasks that they would want you to do a little bit more fast or a little bit more slow. Which I'll get into why variation is important.