The Indian workers filming their work to train AI

But recently the 22-year old has been strapping a camera to his head to record his work.

"The routine is simple, but you have to be disciplined about how you move. The operations team taught me that my hands always have to stay cleanly inside the frame, the lighting has to be sharp, and I can't tilt my head too abruptly while working."

"It's good money, but honestly, the feeling of doing something this futuristic is what keeps me excited. I never imagined my razor techniques would be useful to a global tech company," says Ashim.

Ashim's footage is collected by a local company, which might have hundreds of people filming their work.

That video is then sold on to technology companies and research organisations who use it to train artificial intelligence - in particular so-called physical AI, a type of artificial intelligence that can control robots in the real world.

"Every robotics company, every frontier AI lab, has a specific kind of data they want: industrial tasks, agriculture, household chores, small business work like pottery, garment-making, embroidery, candle-making. We go wherever the task is," says co-founder and CEO Shahil Baig.

"For a lot of these people, that's meaningful," Baig says.

"We record hands, not faces, and where multi-camera rigs do capture more of the body or environment, we blur faces out. No names, no contact details, nothing that identifies them personally goes into what we hand off."

"Now clients are asking for four to six cameras rigged around a person's head to cover the entire scene, not just the hands.

"Getting someone to agree to one small camera is one conversation. Getting them to agree to wearing what's effectively a five-camera headset is a completely different, and harder, one. We pay more for that tier of data collection because of what we're asking of people."

If you want robots to navigate the real world, they can't just be trained inside computer simulations, argues Manish Agarwal, the founder of Humyn Labs, which collects and processes human-generated data.

"Physical tasks require high-quality signals involving limb movements, fingers, wrists, elbows, shoulders and dynamic force application. For example: applying the correct grip force so a plastic bottle doesn't crumble versus a steel glass," he says.

"There is no existing internet archive of embodied human activity - no dataset of a kitchen being cleaned, or a car being assembled by hands that know exactly how much force to apply. That data has to be captured from scratch, in the real world, across diverse environments," says Agarwal, whose company has bases in Bangalore and San Francisco.

Humyn Labs filters the thousands of hours of video supplied by those collectors, selecting the most useful content. It's then labelled so the AI knows what it is looking at and packaged in a format that can be used by clients.

"You need to source across a variety of factories, a variety of tasks, in different geographies because if you want to build deployment for US factories or US houses, you'd want environments that are a proxy for that. Residential houses in India may not be the right context for building a robotics use case for the US."

At the moment it's too early to tell says Bino Paul, senior professor at the School of Management and Labour Studies at the Tata Institute of Social Sciences (TISS) in Mumbai.

The problem is that, if machines do start to take over, there will be little workers can do about.

Like many others, he wants governments to regulate AI.

"AI cannot be viewed merely as a technical system. We need to develop a socio-technical system in which ethics is upheld through human agency, ensuring that AI delivers beneficence rather than maleficence."

Some of that trickles down to workers in India, where there is no shortage of workers prepared to wear a camera for a few dollars a day.

"Garments stitching and cutting. I know this work so well I could probably do it with my eyes closed. Cloth, thread, needle, machine after 10 years, your hands just know what to do before your mind even tells them," he says.

"For me, it's simple. This is survival. I have a family back home in Bihar, and every rupee I send back matters. If someone offers me extra money to wear a camera while I do the exact same work I've been doing for 10 years, I'm not going to say no.

"It doesn't cost me anything. I'm already doing the stitching, already doing the cutting. Now I just get paid a little more for it," he says.

"India's current role in this industry is largely as a supplier of raw material - people strap on cameras, record themselves doing ordinary tasks, and that footage gets shipped off to labs abroad," Agarwal says.

"India can't afford to stay a footage supplier. It needs to move up the value chain: from recording raw video to owning the pipeline that turns that video into something usable - cleaning it, structuring it, validating it, and ultimately setting the standards for what counts as high-quality training data," he says.

Science teacher Jolly Arifur was looking for work she could do from home that would fit around her young son.

"For the past seven months, I strapped a rig-mounted camera on my head while doing my routine domestic work scrubbing, cooking, sweeping tile floors, and folding laundry."

"I get paid two to three dollars per hour. If I record three to five hours a day, that's a good amount in hand it's become an extra source of income for me, on top of teaching. I'm managing both honestly, fantastically."