How Countries Are Using AI to Predict Crime

Countries aren’t only using AI to organize quick responses to crime — they’re also using it to predict crime. The United States and South Africa have AI crime prediction tools in development, while Japan, Argentina, and South Korea have already introduced this technology into their policing. Here’s what it looks like.

SwissCognitive Guest Blogger: Zachary Amos – “How Countries Are Using AI to Predict Crime”

A world where police departments can predict when, where and how crimes will occur seems like something from a science fiction novel. Thanks to artificial intelligence, it has become a reality. Already, countries are using this technology to forecast misconduct.

How Do AI-Powered Crime Prediction Systems Work?

Unlike regular prediction systems — which typically use hot spots to determine where and when future misconduct will be committed — AI can analyze information in real time. It may even be able to complete supplementary tasks like summarizing a 911 call, assigning a severity level to a crime in progress or using surveillance systems to tell where wanted criminals will be.

A machine learning model evolves as it processes new information. Initially, it might train to find hidden patterns in arrest records, police reports, criminal complaints or 911 calls. It may analyze the perpetrator’s demographic data or factor in the weather. The goal is to identify any common variable that humans are overlooking.

Whether the algorithm monitors surveillance camera footage or pours through arrest records, it compares historical and current data to make forecasts. For example, it may consider a person suspicious if they cover their face and wear baggy clothes on a warm night in a dark neighborhood because previous arrests match that profile.

Countries Are Developing AI Tools to Predict Crime

While these countries don’t currently have official AI prediction tools, various research groups and private police forces are developing solutions.

United States

Violent and property crimes are huge issues in the United States. For reference, a burglary occurs every 13 seconds — almost five times per minute — causing an average of $2,200 in losses. Various state and local governments are experimenting with AI to minimize events like these.

One such machine learning model developed by data scientists from the University of Chicago uses publicly available information to produce output. It can forecast crime with approximately 90% accuracy up to one week in advance.

While the data came from eight major U.S. cities, it centered around Chicago. Unlike similar tools, this AI model didn’t depict misdemeanors and felonies as hot spots on a flat map. Instead, it considered cities’ complex layouts and social environments, including bus lines, street lights and walkways. It found hidden patterns using these previously overlooked factors.

South Africa

Human trafficking is a massive problem in South Africa. For a time, one anti-human trafficking non-governmental organization was operating at one of the country’s busiest airports. After the group uncovered widespread corruption, their security clearance was revoked.

At this point, the group needed to lower its costs from $300 per intercept to $50 to align with funding and continue their efforts. Its members believed adopting AI would allow them to do that. With the right data, they could save more victims while keeping costs down.

Some Are Already Using AI Tools to Predict Crime

Governments have much more power, funding and data than nongovernmental organizations or research groups, so their solutions are more comprehensive.

Japan

Japan has an AI-powered app called Crime Nabi. The tool — created by the startup Singular Perturbations Inc. — is at least 50% more effective than conventional methods. Local governments will use it for preventive patrols.

Once a police officer enters their destination in the app, it provides an efficient route that takes them through high-crime areas nearby. The system can update if they get directed elsewhere by emergency dispatch. By increasing their presence in dangerous neighborhoods, police officers actively discourage wrongdoing. Each patrol’s data is saved to improve future predictions.

Despite using massive amounts of demographic, location, weather and arrest data — which would normally be expensive and incredibly time-consuming — Crime Nabi processes faster than conventional computers at a lower cost.

Argentina

Argentina’s Ministry of Security recently announced the Artificial Intelligence Applied to Security Unit, which will use a machine learning model to make forecasts. It will analyze historical data, scan social media, deploy facial recognition technology and process surveillance footage.

This AI-powered unit aims to catch wanted persons and identify suspicious activity. It will help streamline prevention and detection to accelerate investigation and prosecution. The Ministry of Security seeks to enable a faster and more precise police response.

South Korea

A Korean research team from the Electronics and Telecommunications Research Institute developed an AI they call Dejaview. It analyzes closed-circuit television (CCTV) footage in real time and assesses statistics to detect signs of potential offenses.

Dejaview was designed for surveillance — algorithms can process enormous amounts of data extremely quickly, so this is a common use case. Now, its main job is to measure risk factors to forecast illegal activity.

The researchers will work with Korean police forces and local governments to tailor Dejaview for specific use cases or affected areas. It will mainly be integrated into CCTV systems to detect suspicious activity.

Is Using AI to Stop Crime Before It Occurs a Good Idea

So-called predictive policing has its challenges. Critics like the National Association for the Advancement of Colored People argue it could increase racial biases in law enforcement, disproportionately affecting Black communities.

That said, using AI to uncover hidden patterns in arrest and police response records could reveal bias. Policy-makers could use these insights to address the root cause of systemic prejudice, ensuring fairness in the future.

Either way, there are still significant, unaddressed concerns about privacy. Various activists and human rights organizations say having a government-funded AI scan social media and monitor security cameras infringes on freedom.

What happens if this technology falls into the wrong hands? Will a corrupt leader use it to go after their political rivals or journalists who write unfavorable articles about them? Could a hacker sell petabytes of confidential crime data on the dark web?

Will More Countries Adopt These Predictive Solutions?

More countries will likely soon develop AI-powered prediction tools. The cat is out of the bag, so to speak. Whether they create apps exclusively for police officers or integrate a machine learning model into surveillance systems, this technology is here to stay and will likely continue to evolve.

About the Author:

Zachary Amos is the Features Editor at ReHack, where he writes about artificial intelligence, cybersecurity and other technology-related topics.