How law enforcement agencies use artificial intelligence to fight crime
Artificial intelligence (AI) has been on everyone’s lips lately, and for good reason. The technology is constantly finding new applications and has already transformed a number of industries, including healthcare, communications, automotive, and financial, with others set to follow in the near future. Given the stakes involved, it may not be particularly surprising that law enforcement has somewhat lagged behind other sectors when it comes to the adoption of artificial intelligence. However, that’s slowly starting to change, with law enforcement agencies around the world increasingly turning to AI to help them fight crime. A recent report published by MarketsandMarkets estimates that the global law enforcement software market will grow from $10 billion in 2017 to $18 billion by 2023.
Online chatrooms can be a dangerous place, especially for children. They’re often frequented by pedophiles, who will try to initiate a conversation with unsuspecting children or even get them to agree to meet with them in person, which can lead to sexual assault. To address this issue and help police officers catch sexual predators before they do any harm, a team of researchers from Purdue University, led by assistant professor Kathryn Seigfried-Spellar, developed an algorithm called the Chat Analysis Triage Tool (CATT), which can identify sex offenders most likely to arrange face-to-face meetings with potential victims by analysing their word usage and conversation patterns.
To develop the algorithm, the researchers first examined more than 4,300 messages from 107 online chat sessions that involved sex offenders, using a process called statistical discourse analysis to identify different trends in word usage. “We went through and tried to identify language-based differences and factors like self-disclosure,” explains Seigfried-Spellar. “If we can identify language differences, then the tool can identify these differences in the chats in order to give a risk assessment and a probability that this person is going to attempt face-to-face contact with the victim. That way, officers can begin to prioritize which cases they want to put resources toward to investigate more quickly.”
According to the International Labour Organization, 40.3 million people around the world were trapped in modern slavery in 2016, with one in four of them being children. More than half of them, 24.9 million, were trapped in forced labour, 4.8 million of which were in forced sexual exploitation. To address this issue and help the police find victims of human trafficking, a startup called Marinus Analytics developed Traffic Jam, a software suite that uses AI to comb the internet for escort ads and create a database of photos, phone numbers, and location data.
“Every day, tens and even hundreds of thousands of escort ads are posted online,” says Emily Kennedy, the founder and chief executive of Marinus Analytics. “We scrape the top escort sites and put them into Traffic Jam to make them searchable. The goal is to take all of the massive amount of data on the internet that’s relevant and turn it into actionable intelligence.” There are now more than 210 million ads in the Traffic Jam database. The websites are scraped every 20 minutes, which means that even ads that have since been deleted will be included in the database.
The company also recently added a new facial recognition feature called Facesearch. Based on Amazon’s Rekognition software, Facesearch allows police officers to upload a photo of a missing person and compare it against other photos in the database to find out whether they’ve been advertised before. According to Kennedy, Traffic Jam can significantly speed up police work, reducing investigation time by as much as 50 per cent. Widely used by law enforcement agencies across the United States, Canada, and the United Kingdom, Traffic Jam helped identify an estimated 3,000 victims of sex trafficking in 2018 alone.
