
A Telangana labourer was unable to mark his attendance under the MGNREGA scheme after a facial recognition app failed to identify him because he had shaved his head, leading to an unusual fix involving a fellow coworker's hair. The Mahabubabad area, where the government recently implemented a facial recognition-based attendance system for workers hired under the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), is where the event was discovered. As part of a religious rite, Srinivas, a worker from Komatipalli village in Inugurthi mandal, recently went to the Kondagattu Anjaneya Swamy Temple and gave his hair.
When Srinivas returned to work on Thursday with a shaved head, an unexpected problem emerged. The system frequently failed to recognise the worksite supervisor when he tried to use the face recognition software to record his attendance. The technology was unable to match his new look with his prior profile following the drastic change in haircut, leaving the site workers perplexed.
The situation then took an amusing turn when a woman labourer at the worksite stepped in with an improvised solution. She covered Srinivas's shaved head with her hair as the supervisor tried another scan using the attendance app, according to reports of the event. This time, he was successfully recognised and his visit was noted by the face recognition system.
ఉపాధి హామీ సాఫ్ట్వేర్లో బయటపడ్డ లోపాలు
గుండుతో ఉన్న కార్మికుడిని గుర్తించని యాప్
గుండుపై మహిళ జుట్టు కప్పి అటెండెన్స్ వేసుకున్న కార్మికుడు
మహబూబాబాద్ జిల్లా ఇనుగుర్తి మండలం కోమటిపల్లి గ్రామంలో ఇటీవల కొండగట్టు అంజన్నకు తలనీలాలు సమర్పించిన శ్రీనివాస్ అనే ఉపాధి హామీ కార్మికుడు… pic.twitter.com/PUKifkdN4R— Telugu Scribe (@TeluguScribe) May 29, 2026
The unconventional solution attracted notice right away, and although many found comedy in the scenario, it also raised more general concerns about the dependability of face recognition systems in circumstances involving appearance alterations.
The incident also highlighted potential flaws in the technology being employed, especially in situations where physical changes—even transient ones—may obstruct precise identification.
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