After the September 11, 2001 attack, the US national government discovered the life-and-death importance of intelligence operations. Since then, more attention has been focused on restructuring and changing law enforcement intelligence operations. Oftentimes, individuals confuse intelligence with information and use the terms interchangeably, which have a different meaning. While information ideals with data collection, law intelligence is the integration and analysis of data collected to assist law enforcement executives with facts and alternatives to make informed critical decisions. Law enforcement intelligence is used to prevent crime and terrorism in various ways.
First, through data collection and processing, law enforcement intelligence use physical surveillance and undercover operations to prevent crime and terrorism. Since law intelligence requires a labor-intensive data collection, new technologies have been adopted to automate and validate data collection. After data collection, eliminating irrelevant, incorrect, or non-terrorism related information is sifted in collaboration with sophisticated databases with text-mining capabilities. Data collection and processing are vital in criminal justice since it is used in predictive policing. Law enforcers anticipate crime and intervene to prevent those crimes or terrorism from being realized. Secondly, data analysis and dissemination in law enforcement intelligence provide further leads in investigations. Data analysis and dissemination hypothesize who committed the criminal activity, how it was carried out, and predict the next occurrence of a similar event. It also assesses the level of threat posed in the criminal activity jurisdiction. Collectively, law enforcement intelligence justice gathers information, analyses data, and acts according to two dimensions – tactical intelligence and strategic intelligence. Tactical intelligence prevents crime and terrorism by leading a criminal investigation's direct success, while strategic intelligence deals with broader issues such as human resources allocation and planning.
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While identifying criminals and terrorists within a population, different tools and tactics are implemented depending on the investigation's nature. These tools may include video surveillance systems, electronic communications, keystroke monitoring, and global positioning system device (GPS).
After the invention of video cameras in early 1900, video surveillance systems have proliferated in the world market, making it easier for public conduct to be captured on video ( Soroka & Kurkova, 2019). Video surveillance cameras are used to identify criminals through license plate information capture on traffic camera's accurate revelation of events and criminals' presence in a specific area. Modification of video surveillance has extended to police departments with the introduction of body-worn cameras (BWC). They are used to promote officers' safety and increase transparency through the real-time conveyance of events while law enforcers are on duty.
Due to technological advancement, the scope of terrorism and criminal activities have shifted. Criminals use computers and other electronic devices to perform unlawful activities, and the use of keyloggers to monitor and record keyboard activities enables law enforcers to identify such criminals. Keystroke monitoring tools retrieve passwords and monitor online activities such as the individuals a user is communicating to, the type of data they are creating, and whether they transmit any sensitive, contraband, or proprietary information. With such capabilities, keystroke monitoring devices are tools that prove useful in the identification of criminals.
Finally, the Global Positioning System (GPS) uses receivers in conjunction with satellites to accurately identify the location of a vehicle, person, or any item containing a GPS receiver ( Rademacher, 2020) . The tool helps identify criminals since it can map crime scenes and describe a search warrant location. Other than accurate location, the GPS could be used in surveilling movement activities to reveal a criminal's historical information regarding their movement, speed, and stopping points.
While data collection is the most critical step in law enforcement intelligence, challenges faced during data collection and interpretation cannot be unnoticed. With the presence of advanced technologies, the amount of data collected during law enforcement intelligence can be overwhelming. Real-time data from body-worn cameras, videos from interviews, audio recordings, financial transactions, GPS location history, among other data, takes time to process and analyze into usable intelligence in law enforcement. Even though automated systems might be present, the accuracy level is limited to the type of data handled. Lack of enough skills to perform big data analytics in law enforcement agencies also contributes to huge data presented during investigations.
Analysis of data from multiple disjointed sources is also a challenge during data analysis in criminal intelligence. Data hosted from different systems are prone to inaccurate analysis. Manual combinations of data from crime scenes, video footage, and interviews could lead to wrong recommendations; therefore, the use of a centralized system is necessary. Even though law enforcers might opt for a centralized system, they will also be faced with the previous challenge of vast amounts of data to be analyzed.
Finally, poor quality data is another harmful challenge likely to face law enforcement intelligence during data collection. Human beings are prone to manual errors, and when law enforcers make such errors to critical data, it leads to inaccuracy of the information and the results and recommendations. The effect could have enormous devastating consequences if the data was high-level security information. Errors affect the traditional method of data collections such as manual imputation and big modern data due to the lack of skilled personnel that handles big data.
With so much data to be handled and faith in technology, intelligence agencies have risks of cyberattacks and information leaks from hackers and terrorists. For a decentralized data center, an infection from malicious software to that demands fees before restoring the system's servers is a huge loss. Large data handling also comes with huge responsibilities such as highly skilled cybersecurity professionals' employment to protect law enforcement data from leaks and other hacking attacks. Such leaks could also be caused by theft of employee data, which Raaijmakers (2019) found that top employees of an organization caused 58% of database breaches. Other risks of collecting law enforcement intelligence include management-initiated controls, physical and operational security. Facilities housing servers of high value, such as law enforcement intelligence, should be protected from unauthorized access at all times. Operational security involves quality control during data handling and the restriction levels of different centralized system data. Management initiated controls are fair use of data, information security management, and administrative policies regulating computer access.
Incorporating technology into law enforcement intelligence has increased the ability to predict future crime and mitigate the risks prior to its occurrence. Increased surveillance usage to target serial killers has significantly reduced property-related crimes, for example, by 24% for the past two years ( Wilson et al., 2020) . The existence of a pro-active and forward-looking approach to curb crime has diversified to other fields, such as businesses, to address sales issues. Efficiency output per employee has increased significantly, reducing crime rates in the United States.
References
Raaijmakers, S. (2019). Artificial intelligence for law enforcement: challenges and opportunities. IEEE Security & Privacy , 17 (5), 74-77.
Rademacher, T. (2020). Artificial intelligence and law enforcement. In Regulating artificial intelligence (pp. 225-254). Springer, Cham.
Soroka, L., & Kurkova, K. (2019). Artificial intelligence and space technologies: legal, ethical and technological issues. Advanced Space Law , 3 (1), 131-139.
Wilson, L. E., Kessler, M. P., Ellis‐Smith, J., & Robertson, J. (2020). A systems approach to integration of military operations and law enforcement investigations: Toward a unified forensic intelligence model. Wiley Interdisciplinary Reviews: Forensic Science , 2 (2), e1358.
