Why India must use AI to save what it already grows
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Ms Rubal Chib
Contd from previous issue
What this experience has underscored is that AI’s effectiveness depends fundamentally on context. Models trained on foreign datasets or standardised supply chains struggle in India’s heterogeneous conditions, where crop varieties, climates, storage practices and market structures vary sharply across regions. In food systems especially, accuracy cannot be separated from locality.
AI that does not understand Indian produce, Indian logistics and Indian behavioural norms risks being irrelevant at best, and misleading at worst.
(To be contd)
Contd from previous issue
What this experience has underscored is that AI’s effectiveness depends fundamentally on context. Models trained on foreign datasets or standardised supply chains struggle in India’s heterogeneous conditions, where crop varieties, climates, storage practices and market structures vary sharply across regions. In food systems especially, accuracy cannot be separated from locality.
AI that does not understand Indian produce, Indian logistics and Indian behavioural norms risks being irrelevant at best, and misleading at worst.
(To be contd)