HOW AI IS CHANGING THE WAY POLICE FIGHT CRIME
In recent years, AI is being used in all possible fields to simplify tasks and increase efficiency. While AI has been employed in sectors like transportation, finance, energy, and healthcare for some time, its adoption in policing is relatively recent. Artificial intelligence (AI) has the potential to revolutionize the criminal justice system, from the way police investigate crimes to the way courts sentence offenders. It has the capability to address various types of crime, making it a powerful tool for law enforcement. Law enforcement agencies around the world are leveraging AI technology to enhance the effectiveness of their officers. The objective is not only to prevent crime but also to solve it.
Current Applications of AI by Police
AI is still new to the law enforcement community, so its applications have not yet been fully realized. Nonetheless, it’s already making an impact in key areas like surveillance, crime prevention, and crime-solving. With enhanced imaging technologies and object and facial recognition, AI reduces the need for labor-intensive tasks, freeing officers to handle more complex activities. It also may capture criminals that would otherwise go free, and solve crimes that would otherwise go undetected.
Some of the key areas where AI is already being used are:
Facial Recognition
AI-powered facial recognition technology helps police departments identify criminals and missing persons using image data. It offers greater accuracy than humans and saves time for officers by analyzing images and matching faces more effectively. Advanced systems can even identify a single face in a crowd, aiding in the capture of criminals. Close-circuit cameras with facial recognition capabilities are deployed in public areas to identify and apprehend troublemakers. It is also used for surveillance in sensitive locations such as airports and train stations. The positive results achieved through AI in policing have contributed to its increasing adoption.
Surveillance Cameras
AI is being applied to surveillance camera footage to not only recognize faces but also identify objects and activities like car accidents. This helps police monitor large events and detect potential threats. AI can also analyze street footage to identify vehicles based on set characteristics, aiding vehicle-related investigations. Drone cameras equipped with AI capabilities further assist in search-and-rescue efforts.
AI cameras and video technology play a significant role in assisting law enforcement at crime scenes. In cases where the crime scene covers a large area that is inaccessible by foot, AI can provide insights and assist in finding clues.
Predictive Policing
Predictive policing involves using data and statistical models to predict where crimes are likely to occur, who might commit them, and who could be potential victims. It shifts the focus from responding to crimes to preventing them by allocating resources strategically. It helps police target high-crime areas for additional patrolling and surveillance. AI analysis of historical patterns also assists in identifying individuals at risk of committing crimes or re-offending. Predictive policing has been successfully implemented in several countries, leading to lower violent crime rates.
AI tools help law enforcement agencies identify patterns and predict criminal activities that may go unnoticed by humans. Artificial Neural Networks are used to make calculations based on extensive databases, including social media posts, Wi-Fi networks, and IP addresses. AI in policing also aids in detecting crimes related to money laundering and fraud.
Robots
While replacing the entire police force with robots is not imminent, robots are being used for various tasks. Law enforcement agencies employ physical robots powered by AI to perform tasks that are considered unsafe for humans. They can handle mundane tasks and enter dangerous locations to identify potential threats, improving officer safety. Some robots are equipped to detonate bombs, enhancing public safety.
Discovering Non-violent Crimes
AI is effective in spotting anomalies in patterns, making it valuable for discovering non-violent crimes like fraud and money laundering. Banks and law enforcement collaborate to utilize AI in detecting counterfeit goods and bills.
Pre-trial Release & Parole
AI systems aid the criminal justice system in assessing the risk of flight and determining the terms of parole for offenders. These systems analyze complex data sets and assist in efficient decision-making, considering crime data and personal information.
Other organizations using AI to Detect Crime and Report it
For example, delivery companies can use AI to identify prohibited goods in parcels and report them to the authorities. Medicine and retail stores can employ AI solutions to identify suspicious customers, such as those purchasing large quantities of chemicals or substances. Shipping companies can utilize AI to combat human trafficking by identifying containers used for illegal transportation.
Social media monitoring and analysis
AI is being used to constantly monitor social media messages to detect threatening behavior and ensure the safety of users on social media.
Practical Applications of AI Tools being used in Law Enforcement
AI is being used in policing in a variety of ways, including:
- Crime-prevention software in the New York City Police Department is called PredPol. It has been credited with reducing crime in the city by up to 10%. This software uses historical crime data to identify patterns and predict where and when crimes are likely to occur. This information can then be used to deploy officers more effectively and prevent crimes from happening.
- Facial recognition technology in the United Kingdom is used to identify suspects and track their movements. It can also be used to prevent crime by deterring criminals from committing crimes in the first place. Facial recognition technology is already being used by police departments in over 60 countries.
- AI for smart prison systems in Hong Kong and China is used to monitor prisoners and prevent escapes. It can also be used to provide prisoners with rehabilitation services and help them reintegrate into society after their release.
CASE STUDY — I: Trinetra
Problem: The UP Police faced challenges in solving criminal cases rapidly and efficiently due to the high crime rate in Uttar Pradesh. They sought to enhance their efficiency by leveraging technology, including AI.
Solution: In December 2018, the UP Police launched an AI-powered mobile application called ‘Trinetra.’ Developed by Staqu, the application contains a database of 5 lakh criminals, including their pictures, addresses, and criminal histories. It utilizes facial recognition, visual search, machine learning, and deep learning technologies.
Functionality: Trinetra enables police officers to easily register and search for criminals using simple biometric features such as images or videos. It connects to databases of prisons, District Crime Records Bureaus (DCRBs), State Crime Records Bureaus (SCRBs), and the Crime and Criminal Tracking Network and Systems (CCTNS). The application provides real-time access to non-repetitive and non-ambiguous data on criminals active in the state.
Impact: Trinetra has already assisted the police in apprehending a high-profile criminal involved in a shoot-out in Lucknow. The application is set to expand its coverage to 75 districts, 6 Government Railway Police (GRP) units, Anti-Terrorist Squads (ATS), and Special Task Forces (STF). It will be used by over 1,500 police officials, including station house officers, GRP inspectors, and senior police officials.
Future Development: The UP Police plans to introduce additional features in Trinetra, such as vehicle search technology, voice sample search using AI-powered speaker identification, fingerprint-based identification, and active geo-fencing of police personnel. These enhancements aim to further improve the application’s capabilities in criminal identification and investigation.
CASE STUDY — II: Clearview AI
Clearview AI: Clearview AI is a facial recognition firm that has conducted nearly a million searches for US police. The company has amassed a database of 30 billion images scraped from platforms like Facebook without users’ permission. The software is reportedly used by hundreds of police forces across the US. However, many cities have banned its use, including Portland, San Francisco, and Seattle.
Controversial Privacy Practices: Clearview AI has faced multiple privacy breaches and has been fined millions of dollars in Europe and Australia. Critics argue that the use of Clearview’s technology by the police infringes on privacy rights and creates a “perpetual police line-up” by comparing suspect photos to people’s faces without their consent.
Functionality: Clearview’s system allows law enforcement to upload a photo of a face and search for matches in its database of billions of collected images. The software provides links to where matching images appear online, and it is considered one of the most powerful and accurate facial recognition companies globally.
Lack of Regulation: Facial recognition by the police operates with few laws or regulations. The true extent of mistaken identities resulting from facial recognition is unclear due to limited data and transparency. Civil rights advocates call for police to openly disclose the use of Clearview and subject its accuracy to independent testing and scrutiny in court.
Accuracy and Concerns: Clearview claims high accuracy rates, but critics question the reliability of the technology, especially when using images from public sources like CCTV.
Testimony and Legal Use: The CEO stated that Clearview does not want to testify in court regarding the accuracy of its algorithm, as investigators use other methods to verify results. However, Clearview has been used in specific cases, such as finding crucial witnesses and helping in defense efforts. Defense lawyers argue that both prosecutors and defenders should have access to the same technology.
CASE STUDY — III: Revolutionizing school safety with AI technology
License plate recognition (LPR) technology can be integrated into existing security cameras to identify unauthorized vehicles on school premises, potentially preventing dangerous situations.
Facial recognition technology can be used to identify individuals who are not authorized to be on campus, enhancing security measures.
AI-powered virtual assistants can provide real-time emergency information and guidance to students and staff, improving emergency preparedness and response.
Data analytics can help schools identify patterns and trends that indicate safety threats, such as bullying or violence, enabling timely interventions.
AI can assist in monitoring and tracking potential threats, including cyberbullying and online hazards.
Opportunities for AI in Law Enforcement
While artificial intelligence (AI) is not yet being used to its full potential in policing, there are a number of ways that researchers are exploring how AI can be used to improve law enforcement.
Here are some specific examples of how AI is being researched for use in policing:
Biometric identification
AI-powered biometric technology can be used to identify suspects and match them to criminal databases accurately and swiftly.
Body cameras and wearable technology
Integrating wearable technologies with body cameras can enhance threat detection and emergency response capabilities.
Drones and autonomous vehicles
AI-powered sensors and cameras on drones and autonomous vehicles can improve surveillance of public areas.
Natural language processing (NLP)
AI-powered NLP systems can facilitate communication with non-English-speaking communities, reducing language barriers in law enforcement interactions.
Enhance Prison Management
AI can improve prison security, and help in the treatment of inmates with addiction issues. It can also aid in the selection of the best combination of inmates to result in the least amount of conflict.
AI-based dispatch systems for emergency response
AI can automate the process of dispatching officers to emergencies, making the response quicker and more effective. By analyzing data from various sources, AI algorithms can determine the best course of action in real-time.
Traffic Management
AI can help manage traffic patterns and control traffic lights in real-time, enabling efficient routing during planned and unplanned situations. It can also facilitate the movement of emergency vehicles.
Police-Related Citizen Service Delivery
Policing-related services, such as the registration of FIRs (First Information Reports) and investigation of cases, can utilize an AI-based Intelligent Complaint Registration Application. This application could be hosted online or through smart interfaces and employ technologies like Natural Language Processing, speech recognition, and deep learning to streamline the process. By reducing the human factor in service delivery, such tools can help ensure standardized, truthful responses, equal access, and other benefits for citizens.
Risks & Considerations
Today, artificial intelligence is being used by law enforcement for facial recognition and even predictive policing. It can help solve and prevent crimes, but it’s not foolproof. That’s resulted in wrongful arrests and continued racial profiling in policing.
The development and implementation of AI technology have outpaced the creation of laws and regulations to govern its use. This has led to concerns about the impact of AI on human rights.
- Lack of understanding and digital literacy: People may not be able to question or challenge the results produced by AI systems. There is a need for a proper interpretation of AI-generated insights.
- Loss of privacy: AI has given states the power to create total surveillance states, where individuals can be constantly monitored. This raises concerns about the violation of privacy and other human rights.
- Discrimination and bias: AI algorithms can amplify existing social biases due to biased input data, leading to discrimination in predictive policing and criminal justice systems.
- Violation of the right to equality: When AI systems are biased, they can infringe on an individual’s right to be treated equally. Predictive tools and risk assessment algorithms may flag certain individuals as high risk based on biased historical data, undermining the principle of “innocent until proven guilty.”
- Lack of transparency and fairness: The “black-box” nature of AI algorithms and the reliance on big data sets that may not directly correlate with the crime accused can undermine transparency and fairness in decision-making, infringing on the right to a fair trial.
- Accountability: When AI systems are relied upon by police or courts, it raises questions about accountability. If these systems produce biased or unfair results, it becomes challenging to hold anyone accountable for the consequences.
- Vulnerability to hacking or manipulation: This high dependency on technology also introduces the additional issue of vulnerabilities to hacking or manipulation.
Key Takeaways
Usage of AI in Analytics:
We have seen how useful predictive policing using AI can be. This is done by using AI in analytics.
AI analytics combines artificial intelligence and machine learning with traditional analytics to generate insights, automate processes, deliver predictions, and drive actions for better business outcomes. It provides a comprehensive view of operations, customers, competitors, and the market, enabling organizations to understand what happened, why it happened, what’s likely to happen next, and the potential outcomes of different actions. AI analytics offers advanced capabilities that go beyond traditional analytics, enabling organizations to harness the power of data and make better-informed decisions for improved business outcomes.
The benefits of AI analytics include enhanced decision-making, improved efficiency and productivity, enhanced customer experiences, and freeing up data teams to focus on strategic initiatives.
Hence, it is important for people from different fields to understand how this technology might benefit them, and make informed changes to their business to incorporate this technology so that they can reap the most efficient outcome.
The top tools for AI-powered analytics that can be used for any business are:
- Adobe Analytics uses AI to analyze data from different online and offline sources, then visualize insights from your data.
- BlueConic is a customer data platform that turns customer data into person-level profiles.
- Crayon is a market and competitive intelligence tool that enables businesses to track, analyze, and act on everything happening in their market.
- Google Analytics uses machine learning to surface insights and answer your analytics questions.
- Google Cloud’s smart analytics solutions use machine learning to get insights into and make predictions.
- Helixa helps you produce detailed personas based on audience interests, demographics, and psychographics.
- Invoca is an AI-powered call-tracking and conversational analytics tool.
- IBM Watson + IBM Planning Analytics can make predictions across finance, operations, and sales.
AI-related Jobs in all kinds of Companies:
The demand for AI jobs is rapidly growing across various industries, and law enforcement is no exception. The use of AI in law enforcement has been highlighted as a significant improvement in the field. In policing, technology jobs encompass a wide range of roles such as electronic surveillance officers, digital forensic investigators, real-time crime analysts, social media researchers, and accident reconstructions, among others. Platforms like LinkedIn and Indeed display numerous job postings for technology positions in law enforcement, including data analysts, computer forensic instructors, intelligence analysts, research analysts, police business systems analysts, and more.
This emphasizes the importance of having dedicated AI and technology teams in every business venture to enhance operational efficiency.
