There has been a global trend in the usage of AI for safeguarding the safety of citizens through AI integrated technology and predictive analysis. The innovations have enhanced police’s capability to maintain vigilance, empowered them to respond to crimes in advance, and given them the ability to anticipate illegal activities. Once a system that was limited to responding or reacting to complaints, it has now evolved into a more dynamic and initiative driven process.
How does it work?
Crime scenes have behavioural patterns which are hard to notice and take considerable time for investigators to notice. However, data mining wherein machine learning and statistical techniques are used for investigation and evaluation, makes it easier and faster to uncover these patterns. This allows forces to predict times and places of high vulnerability and identify groups which are more predisposed to experiencing atrocities. The process eventually makes resource allocation more efficient and reasonable and paves the way for public safety to be much more efficient and widespread. However, advancements are not without challenges, such as algorithmic biases and privacy concerns, which must be addressed responsibly.
Why is AI Powered-Predictive Policing Needed?
Using AI in vigilance has several motivations that outweigh its demerits. Some of them are listed below: –
- Rising Complexity of Transnational Crimes
Cyber-attacks, smuggling and human trafficking often involve an international nexus of criminals who have leveraged advancements in communication and transportation technologies to increase the efficiency of their criminal and operate in secrecy while exploiting jurisdictional limitations. AI integrated technology can empower forces to predict such criminal activities and catch them in the act faster.
- Bridging Resource Gaps
Organisations such as the United Nations propose for efficient maintenance of safety standards that a nation must have a police force of 222 officers per 100,000 people. However, India falls significantly below the recommended ratio with only 155 police officers per 100,000 people. This huge gap demands rigorous efforts for optimal resource management to maximise public safety; predictive analysis becomes an essential tool for prioritising deployment of vigilant forces in high-crime areas and making the best of what is available.
What AI and Predictive Policing Involves
As stated earlier, predictive analysis is conducive for identifying crime hotspots which is known as hotspot analysis and comes under the broader term of geospatial intelligence. However, it has several other tools that together make it a powerful tool against criminals in a proactive system.
Link and Network Analysis: AI can analyse past criminal cases to learn about criminal behavioural patterns and use the knowledge to identify connections between seemingly unrelated criminal cases in the present.
Visual Analytics: Identification of crime suspects becomes smoother with AI integrated softwares as they are extremely capable of recognising faces though CCTV footage and other digital evidence.
Unifying Data: A criminal investigation involves a laborious procedure of processing forensic data, telecom records and financial trails besides social media data and personal history. AI has been playing a pivotal role in speeding up the process, giving police forces access to a consolidated dashboard.
Predictive Policing in Action
In countries like the US, property-based crimes experienced a colossal reduction of 20% with the help of AI integrated predictive systems and hotspot-policing. Predictive policing in action encapsulates enabling situational analysis at a larger scale and faster investigation besides ensuring the best use of limited manpower through AI and ML techniques like statistical modelling and data mining. Here’s how these complex algorithms are applied in the real-world setup.
- Situational Awareness at Scale
Artificial intelligence empowers police with tools of advanced threat analysis, allowing senior level officers to not just gain insights into what has been happening in their districts, but also identify emerging trends in crimes. This can include determining locations where pickpocketing has been rising or becoming alert when a certain neighbourhood suddenly becomes a criminal hotspot. While such patterns earlier took weeks to be noticed, AI significantly speeds up the process.
- Smarter Resource Deployment
Police patrolling is a major tool in use for deterrence against criminal activities. However, as stated earlier, human resources are scarce in many ways and sending a team to each location might be wasteful. Therefore, though AI led short term forecasting, police deploy a larger force in certain threatened neighbourhoods where patrolling is most needed to reduce crime.
- Swifter Justice
Justice delayed is justice denied and thus, to safeguard fundamental rights of citizens, police are required to act fast. AI often takes away the burden of time taking routine analysis and helps police save time and resources that would have gone in manual checking of records and data collection. The automation is a boon that enables advanced correlation analysis and lead generation at a much faster pace for the police to solve the case in time. This becomes especially useful in crimes that involve organised gang activities.
Early Adopters and Case Studies
Predictive policing has started to spread its roots in India, and several police teams are experimenting with its usage in their work. Here are a couple of examples.
- Ahmedabad’s Nirbhaya Safe City Project
The Ministry of Home Affairs is piloting the use of predictive analysis for identification of vulnerable areas and proactive criminal forecasting of crimes against women. The project named Nirbhaya Safe City Project has an objective of improving women’s safety in the city. Through data from CCTNS, records from helpline number 112 and information from city surveillance systems, police forces are working to intervene before the criminal act itself.
- Chandigarh’s CenCOPS
Chandigarh houses The Centre for Cyber Operations and Security (CenCOPS) which is India’s first integrated cybercrime response and investigative hub. Facial recognition, AI-driven data analysis and many other algorithmic tools, it works to strengthen cyber security defences and increase law enforcement at a local level.
AI led vigilance is only getting started, and if used with transparency and responsibility, it can revolutionize the internal working process of police forces to enable a new dawn of social justice in India. This will make police a much proactive and trustable institution, making redressal of grievances more accessible for masses.