Karnataka plans AI facial recognition system for school attendance tracking
Karnataka's education department plans to implement an AI facial recognition system in schools to track student attendance and government welfare beneficiaries starting in 2025-2026. A coalition of 31 experts and civil society groups has urged the government to abandon the system, warning it could expose children to data theft, exploitation by criminals, and deepfake-based sexual abuse.
What happened
The Department of School Education and Literacy in Karnataka announced plans to implement a mobile-based AI facial recognition system to mark student attendance in the Students Achievement Tracking System (SATS) and track beneficiaries of government welfare schemes such as midday meals.
The system is set to be implemented in the 2025-2026 academic year and will capture student images, encrypt them, and convert them into unique identification codes.
Reported impact
A coalition of 31 experts, educationists, teachers' unions, parents' groups, and civil society organisations warned the initiative could expose children to risks of data misuse, exploitation, and abuse.
Experts cautioned that if facial data is leaked or stolen, it could have 'unimaginable consequences, including falling into the hands of child traffickers and criminals.' They also expressed concerns over possible sexual exploitation given the rise in deepfake tools.
Index analysis
The coalition pointed out that facial recognition systems have been banned in many jurisdictions due to dangers of data misuse. They cited risks from leaky data environments and noted that student data collected by the education department has previously been shared with commercial institutions.
Experts warned that image morphing could convert photos of children into 'crime-enabling items' and that classrooms are protected spaces, not public spaces, where routine photo capture could cause significant vulnerabilities.
Governance controls
Officials stated the system would encrypt captured images and convert them into unique identification codes that cannot be reverse-engineered to ensure privacy and data security.
The coalition recommended strengthening existing School Development and Monitoring Committees in schools as an alternative to surveillance tools for ensuring accountability.
Classification
Sources and evidence
Sources not yet published
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