The unsettling sight of AI in Bengaluru’s local markets

Trisha Majumder
A grocery run on a Sunday morning is one of life’s simple pleasures. The energy of local markets feels almost therapeutic — handpicking fruits and vegetables, asking vendors about the freshest produce, participating in familiar bargaining rituals, and listening to conversations about prices and politics unfolding in the background. It is one of the few everyday experiences that still feels deeply human. Unfortunately, that may not remain unchanged for long.

Recently, vegetable vendors in Bengaluru were spotted wearing AI-enabled headsets while sorting greens, selling tomatoes, and interacting with customers. Training Artificial Intelligence models is no longer confined to futuristic corporate offices or research labs; it has now reached local markets. These devices reportedly record video, audio, and spatial information to help train AI systems using ordinary human tasks and interactions. We already associate malls and self-checkout systems with a certain loss of human connection. If AI gradually enters traditional market spaces, it could not only reduce everyday social interaction but also threaten thousands of livelihoods built around these ecosystems.

According to reports, some vendors claim that tech companies are paying them to upload footage captured through these devices, with earnings allegedly reaching up to Rs 1 lakh a month. While these claims remain unverified, the promise of easy supplemental income has already triggered widespread discussion on social media. Similar visuals have emerged from factories in India, where garment workers were reportedly seen wearing these devices while stitching clothes. Globally, smart glasses equipped with high-resolution cameras are already commercially available, while companies like Apple are reportedly exploring camera-enabled earphones. Many social media users believe that the data collected through such wearable devices could eventually be used to train AI models — a cheaper and more scalable alternative to traditional data collection methods.

At a time when concerns about privacy, surveillance, and data theft by large tech companies are growing, the image of marginalised workers helping train AI systems feels especially ironic. And, in an economy shaped by inflation, unstable incomes, and limited job opportunities, participation in such initiatives may stem less from enthusiasm for technology and more from necessity. In many ways, people may be unknowingly contributing to systems that could eventually reduce the need for their own labour.
It may not be realistic — or even desirable — to reject technological progress altogether. But as AI becomes increasingly embedded in everyday life, humans must remain at the centre of that evolution: as workers with dignity, agency, and fair compensation, not merely as sources of data.



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