The Agonising Wait
Traditionally, the search for a missing person is a gruelling, manual process. It involves police and volunteers physically searching areas, putting up posters, and interviewing witnesses. Investigators spend hours, sometimes days, sifting through enormous
amounts of data, such as CCTV footage from multiple locations or social media activity. This painstaking work is not only slow but also resource-intensive, often constrained by limited manpower. The problem isn’t a lack of evidence, but an overwhelming amount of it. For families awaiting news, this delay prolongs the uncertainty and anguish, while the window for a safe return potentially closes.
Enter the Digital Detective
Artificial intelligence is changing this landscape by acting as a force multiplier for law enforcement. At its core, AI can process and analyse vast datasets at a speed impossible for humans. One of the most significant applications is facial recognition. Modern systems can scan thousands of hours of video from CCTV networks at airports, railway stations, and public squares, looking for a match. Beyond simple matching, AI can analyse social media for a person's last known activity, location tags, or signs of distress in their posts. It can also perform predictive analysis, using data on the person's habits, the last known location, and even weather conditions to suggest high-probability search areas.
From Theory to the Field
This is not science fiction; it is already being deployed in India with promising results. In a trial, Delhi Police used facial recognition software to scan photos of 45,000 children in institutional homes against a database of missing children. In just four days, the system identified nearly 3,000 matches. Manually comparing these photos would have been a near-impossible task for any human team. Similarly, police in Telangana have used an AI-powered facial recognition app called 'Operation Smile' to successfully identify and reunite thousands of missing children with their families. More recently, generative AI is being used to restore and enhance old, faded photographs of missing children, giving investigators a clearer image to work with.
AI's Advantage: Speed and Scale
The primary advantage AI offers is the compression of time. An investigation that might take days or weeks can be accelerated, with leads generated in minutes or hours. AI systems can integrate fragmented data from different sources—police reports from one district, hospital admission records from another, and railway surveillance footage—and connect the dots. For instance, if a person is found and admitted to a hospital in an adjacent state, an integrated AI platform could automatically flag the match against a missing person report, a connection that might otherwise be missed. This ability to rapidly correlate information across jurisdictions and systems provides investigators with actionable intelligence when it matters most.
A Tool, Not a Replacement
Despite its power, experts are quick to point out that AI is a tool to augment human capabilities, not replace them. The final decision-making and the crucial on-the-ground investigation still rely on human judgment and empathy. Furthermore, the use of AI in policing raises important ethical questions about privacy, consent, and potential bias in algorithms. Using facial recognition on a mass scale requires a robust legal and ethical framework to prevent misuse and protect citizens' rights. Ensuring transparency and accountability is key to building public trust in these powerful new technologies. The goal is to leverage AI's efficiency while keeping human oversight at the centre of the process.
