MEET THE INDIAN EXPERTS TRAINING AI MODELS

These doctors and engineers are educating global AI models. It's not a job for the fainthearted

- Shadma Shaikh

The difference between catching a foetal anomaly in time and missing it can be life-changing for the foetus and the expecting mother. These days, Kochi based Raji Chandran, a medical professional who is well aware of this difference, is using her knowledge and expertise well beyond clinical practice to educate artificial intelligence models.

Week after week, she opens foetal ultrasound scans on her computer and carefully annotates them to outline organs, measure growth and flag anomalies. Her work is helping train Al systems being developed for hospitals in the US and other western countries. So, when a woman in Dallas undergoes a pregnancy scan, the algorithm guiding the diagnosis may, in part, be shaped by Chandran's judgment in Kochi.

Chandran is part of a new workforce emerging in India. Once seen as low-cost projects done by anonymous workers labelling cats or stop signs, AI training today has moved to a higher level requiring domain expertise and accountability. Doctors, dentists, linguists and engineers are becoming the 'human in the loop' for algorithms, where the penalty for error can be catastrophic.

At the centre of this shift are data annotation firms, which have evolved from volume-driven labelling to expert-led AI training. Globally, companies such as Scale AI and Turing are building human-in-the-loop systems that rely on domain specialists rather than anonymous crowdworkers. iMerit, headquartered in San Jose with major hubs in Kolkata, Bengaluru and Coimbatore, is also embedding doctors, engineers and linguists into critical AI workflows.

Other companies offering expert AI data training include Cogito Tech and Pixel Annotation which have their roots and a large presence in India, reflecting how the country has become a global base for expert-in-the-loop talent powering the AI systems used in hospitals, cars and financial institutions worldwide.