India’s Ministry of Electronics and Information Technology (MeitY) has demanded detailed explanations from home services platforms regarding their collection of first-person video and sensor data from gig workers. The ministry is investigating whether this data, used to train physical artificial intelligence models, violates worker rights, consumer privacy, and national data security protocols.
S Krishnan, the MeitY secretary, led a meeting with senior executives from firms including Pronto, Snabbit, and Urban Company’s InstaHelp. The ministry requested documentation on the standard operating procedures used for gathering, processing, and storing this data. Officials specifically questioned if these companies are transferring or selling collected recordings to foreign AI developers.
Privacy and Security Concerns
The government’s inquiry focuses on whether service providers obtain proper consent from workers and protect the privacy of individuals caught in recordings within private homes. Regulators expressed apprehension that India is becoming a low-cost source of training data for international AI companies. During the meeting, some executives suggested the nation should prioritize developing domestic physical AI capabilities instead of supplying raw data to overseas entities.
Pronto is currently under scrutiny for a pilot program where service professionals wore cameras to record household chores. The startup stated that the feature was opt-in, limited to less than 0.01% of its users, and that raw footage was deleted after work completion. It maintained that anonymized, encrypted recordings were accessible only to customers for 48 hours before being used for AI training.
Industry Responses
Other companies have moved to distance themselves from the controversy. Urban Company founder Abhiraj Singh Bhal stated the firm does not record inside customer homes and has no plans to do so. Snabbit clarified that while it conducted a limited assessment of such technology in a controlled training environment, it ultimately decided against implementing the practice.