India's ambitious push to digitize welfare delivery has hit a devastating humanitarian crisis: an AI-powered facial recognition system meant to prevent fraud is denying food rations to pregnant women whose faces have changed during pregnancy.
The Integrated Child Development Services (ICDS) program—the world's largest maternal and child nutrition initiative serving 47.3 million beneficiaries—mandated AI facial recognition through its Poshan Tracker app in July 2025. By year's end, nearly half of eligible recipients had not received rations due to authentication failures, according to a Boom Live investigation.
The system's failure is grimly simple: pregnant women's faces often don't match identity photographs taken years earlier. The Poshan Tracker app uses Google's ML Kit for facial detection paired with an undisclosed matching algorithm. Community health workers report repeated authentication failures. "The community health worker lifts her smartphone toward the woman's face and waits. The screen flashes: 'Face not matched,'" the investigation documented.
In India, as across the subcontinent, scale and diversity make simple narratives impossible—and fascinating. This is Digital India's dark paradox: a country celebrated globally for its technology prowess and startup ecosystem is deploying AI systems without adequate testing on vulnerable populations, harming the very people these programs are designed to help.
The accountability gap is striking. Google clarified that ML Kit "does not have facial recognition capabilities" and the company has no visibility into how developers deploy it. Yet the Indian government has refused to disclose who built the system, whether it was tested for accuracy on pregnant women, or what safeguards exist when the technology fails.
The Ministry of Women and Child Development allocated Rs 21.37 crore ($2.5 million) for the Poshan Tracker app's first year but has provided no data on fraud prevention outcomes—the stated justification for the facial recognition requirement.




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