india

Updated: Sep 11, 2019 03:55 IST

The use of Artificial Intelligence in police paperwork, including charge sheets could remove flaws and prejudices from creeping into investigations, India’s Bureau of Police Research & Development (BPRD), a think-tank of the ministry of home affairs (MHA), believes.

BPRD’s futuristic vision for law enforcement , especially in smart cities, Prime Minister Narendra Modi’s ambitious project, is part of a concept note the body has drafted.

“A machine-learning algorithm can generate chargesheets specific to an incident with complete legal validity without any exclusions or non-conformity. This allows minimal manual intervention; hence the scope for malicious intent is not there in any way and the ability of the legal system to prosecute to the fullest extent of the law is always available. In the charge sheet, references from other judgements as well as other outcomes can also be included to make it more effective,” reads the note, a copy of which has been seen by HT.

Asserting that AI based systems have outperformed lawyers as well as judges in some cases, the BPRD note adds: “A neural network based system over a period of time can also create sensor based inputs in order to predictively allow for the analysis of outcome of cases as well, helping speed up the judicial process. The consequent burden on the policing system goes down”.

In a recent interview with The Economist, author Malcolm Gladwell, too discusses the importance of AI in the criminal justice system. Citing an example of judges taking bail decisions, Gladwell says, “..Defendants stand in front of the judge, the judge has to decide whether I released this person until the trial or I put the person in jail. Are they likely to commit another crime in the interim? That’s an extremely difficult decision to make. And when we look at how effective judges are in predicting the dangerousness of the defendant, they are not very good at it. But look how the machine learning algorithm tends to do better, actually much better than the judge. So there is an instance where we have clear evidence that a disembodied computer can be more accurate in making a prediction about the human being than a judge.”

Gladwell, however, also argues that there is a need to combine both the decision making of humans and AI, a view that many proponents of AI have also advocated.

According to BPRD, AI models coupled with crime mapping can be developed “to analyse crime patterns and identify hotspots which act as a useful tool for predictive and preventive policing”.

The police can also use AI based on algorithmic software at a crime scene for immediate recognition of perpetrator (s) based on modus operandi, pattern of crime/criminals in the area, biometric data, forensic data etc, the note claims. The BPRD note cites the example of San Francisco based Deep Science AI which has developed AI Surveillance (AIS) platform which uses deep learning to identify real people concealing their faces/firearms of intruders.

AI can also be used to manage traffic in smart cities, BPRD has suggested in its note.

To be sure, all this needs integrated data on video surveillance of public places, a wide CCTV camera network, sensors just about everywhere, databases of criminals, information on public transport, real-time tracking of events, and other such, the note admits. It also adds that privacy concerns need to be factored in while using such technologies.

When asked how AI can help police smart cities, Tarun Wig, co-founder of Innefu, a data analytics and cyber security company which provides predictive intelligence systems to various government institutions said: “The AI based system will read the text on a particular case which has to be charge sheeted and extract data on similar charges and relevant law provisions. It can read the type of crimes and tell police how to use its resources”.

BPRD and MHA officials did not respond to queries seeking comment on the concept note.