Synopsis
The concerns gained urgency after controversy around startup Pronto’s in-home recording pilot sparked wider questions over how “physical AI” systems may learn from people’s routines, conversations, movement patterns and behaviour inside private spaces.Listen to this article in summarized format
The concerns gained urgency after controversy around startup Pronto’s in-home recording pilot sparked wider questions over how “physical AI” systems may learn from people’s routines, conversations, movement patterns and behaviour inside private spaces.
While India’s privacy laws are largely built around conventional personal data processing, lawyers said the new regulatory challenge goes beyond collection or deletion of recordings because AI memory may retain behavioural intelligence, predictive insights and model improvements derived from such interactions.
“The concern is not merely surveillance in the traditional sense, but the gradual creation of highly sophisticated behavioural ecosystems capable of mapping routines, habits, preferences, conversations and emotional patterns,” said Hardeep Sachdeva, partner at AZB & Partners.
Unlike traditional AI models trained largely on internet data, physical AI systems learn from real-world human activity and interactions. As companies increasingly look for such behavioural data to train AI models, lawyers point to legal grey areas around surveillance, profiling, consent and AI memory.
“The real legal complexity lies in the fact that even if raw recordings are deleted, the AI system may continue to retain behavioural patterns, spatial intelligence, predictive insights and model improvements extracted from that data,” Sachdeva said. “Current law does not clearly distinguish between deletion of raw data and retention of intelligence derived from it.”
Supratim Chakraborty, partner at Khaitan & Co, said while India does not yet have a standalone law specifically governing AI systems, existing legal frameworks could still apply through consent, purpose limitation and consumer protection principles.
“Concerns are likely to intensify where in-home AI systems engage in persistent monitoring, create long-term behavioural profiles or repurpose interaction data for downstream AI training without sufficiently clear disclosures and user awareness,” he said.
Unlike digital platforms, home-based AI systems may operate in a “persistent and context-aware” manner inside highly private spaces, while also incidentally collecting information relating to family members, children, guests or domestic workers present in the household, Chakraborty said.
At present, such systems are governed through a combination of the Information Technology Act, the IT Rules on sensitive personal data, consumer protection provisions and the Digital Personal Data Protection (DPDP) Act, which are largely designed around identifiable personal data and conventional data processing models, experts said.
Some of them called for safeguards specifically for AI systems operating inside homes, including limits on continuous recording and clearer controls to allow users to switch off listening or monitoring features when needed.
They pointed to a growing legal grey area around AI-generated inferences and learnings that may not always qualify as personally identifiable data under current laws.
“To the extent that inferences or improvements are not personally identifiable, their continued retention or processing may be permissible from a privacy standpoint,” said Arun Prabhu, partner at Cyril Amarchand Mangaldas. “That said, other issues like benefit sharing, ownership and potential harms will need to be addressed with greater clarity.”
Prabhu drew a distinction between anonymised service improvement and deeper behavioural profiling inside homes. “Profiling, or processing of interpersonal interactions, with a view to deriving insights or monetisation may be difficult to justify,” he said.
As AI companies increasingly seek real-world behavioural data beyond internet content, homes and other private spaces could gradually become large-scale AI training grounds if regulations fail to keep pace with the technology, experts warned.
