June 25, 2026, (Inside AI) — Lieutenant Governor Taranjit Singh Sandhu directed Delhi Police on Wednesday to integrate artificial intelligence, drones, and facial recognition into crime prevention during his first visit to the force’s headquarters since taking office.
He chaired a two-hour review with Police Commissioner Satish Golcha and senior officers, laying out a roadmap for technology-driven, people-centric policing in the capital.
The meeting, attended by all Special Commissioners, Joint Commissioners, and Deputy Commissioners, focused on public safety, traffic management, and community engagement. Sandhu stressed a policing model that is humane, visible, and preventive, asserting that trust hinges on fairness and transparency.
He declared the safety of women, children, and senior citizens non-negotiable, ordering officers to identify crime-prone areas and boost security for girl students. The LG’s push for AI mirrors a global trend where cities like London and New York deploy predictive policing, though critics warn of bias and privacy risks absent strict oversight.
Sandhu instructed the force to aggressively use AI, social media monitoring, and drones for intelligence gathering. He highlighted continuous training in cybercrime and POCSO cases, signaling a shift toward data-driven law enforcement.
On traffic, he demanded stringent enforcement against wrong-side driving, triple-riding, and helmet violations, with visible personnel at congestion points. Community policing gained emphasis through integration of Resident Welfare Associations, market groups, and street vendors into grassroots intelligence networks.
Sandhu also pushed for transparent transfers, timely promotions, and more women in the force, alongside exploring CSR support for martyr welfare. He directed police colonies to become zero-waste complexes, replicating the Navjeevan Vihar model with the Municipal Corporation of Delhi.
Reminding officers that outcomes define institutional trust, he urged visible improvements in safety and service, promising full support for the force’s renewed commitment.
Sofia spent years studying how machines parse human language before pivoting to cover the systems now rewriting it. She reads technical papers the way others read news and looking for what the numbers are actually saying beneath the headlines.
