Introduction
Artificial Intelligence, or AI, has been referred to as the development of computers that think like human beings. Artificial intelligence is the computer’s ability to perform activities that mimic human activity. Artificial intelligence is not confined to a supercomputer in a laboratory; instead, it is a growing technology that has invaded society with many positive aspects (Velasco, 2022).
In recent years, artificial intelligence has led to new developments in robotics (creating machines capable of intelligent and independent behavior), expert systems (automated reasoning and problem-solving programs for support), and other fields. The defense and aerospace industries are now among the most significant users of artificial intelligence technologies. This article makes the case that, given the growing use of artificial intelligence by criminals, criminal justice should consider the effects of this technology on the legal system. The AIs have influenced criminal justice by improving investigations, enhancing assessment processes, enabling crime predictions, providing surveillance capabilities, reducing the chances of skipping bail, and reducing cybercrimes.
Investigations
The use of AI in criminal justice has helped improve investigations. Though AI is a new technology, research has shown that it can be applied to solve problems encountered in criminal investigations (Rigano, 2019). AI can quickly analyze and interpret large volumes of data and provide broader perspectives on perpetrator behavior in a given situation.
For example, computer search histories can help better detect possible perpetrators (Rigano, 2019). Computerized algorithms and programs can quickly collect vast amounts of information from electronic documents. The computers also correlate this data with crime details from police reports, which are difficult to store or retrieve accurately, especially for long periods.
Additionally, deep learning networks, a branch of AI, can spot patterns in large data sets. Natural language processing (NLP) analyzes texts of all kinds, from social media posts and comments to news articles and court transcripts (Završnik, 2020, March). The US State Department used NLP to help process visa applications for several years. It has also been used in fraud detection and anti-money laundering applications. NLP is increasingly being implemented by police forces worldwide, including the London Metropolitan Police Service, New York Police Department, Orlando Police Department, and Texas Department of Public Safety.
Assessment Process
AI has facilitated this department by enhancing or improving the assessment process. Assessment evaluates a defendant and determines whether he or she is responsible for the crime. To do this, two experts must discuss the evidence gathered from witnesses and other sources (Sushina & Sobenin, 2020, May). AI has aided the assessment process by helping to identify patterns in the data that were not apparent to people unfamiliar with AI science.
For example, AI can extract information from millions of cases to look for patterns and rate the probability that a suspect is guilty (Sushina & Sobenin, 2020, May). This means that instead of relying on the opinion of individual people who are not very familiar with the investigation, the objective probabilities of an AI machine can be used. Furthermore, due to the exponential growth in technology, AI can now look at more information than before. The use of AI has also helped to improve predictions in this field.
Crime Prediction
AI has aided this department by enabling the prediction of various crimes. Since computers use sophisticated algorithms and models to make predictions, they have the potential to provide more accurate answers. Law enforcement agencies have invested in artificial intelligence systems that can predict where crimes will happen before they take place (Hayward & Maas, 2021).
These systems use various data, including past crime statistics and profiles of offenders. For example, the Chicago Police Department has developed an “early warning system” to reduce repeat gun violence in Chicago neighborhoods. This is done by using data from 911 calls made by residents to track reported crimes such as shootings and robberies (Hayward & Maas, 2021). This has helped prevent murders and gun violence in certain streets where crimes are reported.
Surveillance Capabilities
AI has facilitated this department by providing surveillance capabilities that were not well-known before the adoption of AI. For example, computers can now monitor and record CCTV cameras to find suspicious activities (Velasco, 2022). This helps detect criminals and make arrests more efficiently.
CCTV has helped reduce the crime rate, and AI can also help reduce the number of sexual crimes against children. In this area, computers make it possible to store information that is impossible to keep on paper or in computer records. Thus, this has also helped to enhance security at various police stations across the United States.
Chances of Suspects Skipping Bail
The use of AI has helped reduce the chances of suspects skipping bail. For example, AI systems can be used to discover bail bondsmen’s trustworthiness by identifying their historical patterns. Police can then check the bail bond agents’ records and even call them. The system can also check an individual’s criminal record to know whether he has previously skipped bail (Rigano, 2019).
Nonetheless, the AI can detect if an individual uses their cards to pay for air and train tickets or hotel rooms. This helps in improving public safety through the reduction of criminal activity. This monitoring helps increase productivity because the time and money spent on undertaking investigations by police officers can be reduced.
On average, a bond dealer must sign 500 bonds monthly as part of their required monthly bonding submission to the court (Rigano, 2019). It is faster for AI to go through all these records for a particular bail bondsman than to manually go through them. Besides speeding up the process and reducing human error, it also eliminates bias towards specific individuals, especially those of low socio-economic status or without power or influence.
Cybercrime and Criminal Activity
The use of AI has also aided in reducing cybercrimes and criminal activity. For example, a computer program can alert police when there is evidence of online stalking or harassment by reviewing what messages are sent over social media platforms like Twitter, Instagram, and Facebook. It also detects real-time threats over live video streams (Završnik, 2020, March).
AI has helped improve the efficiency of the processes and procedures within police stations to identify suspects. It can also suggest helpful information to detectives doing a lot of paperwork. Furthermore, AI has been used to reduce the backlog of cases that have gone unprocessed for years. This means that many cases that never get to court will now be investigated by computers instead.
Conclusion
In conclusion, AI has assisted in reducing crime rates by making it possible to survey various areas through CCTV cameras. This has enabled the police to monitor streets and control crimes such as drug peddling, harassment, and other offenses. Furthermore, AI has also assisted in raising the efficiency of police investigations by improving the assessment of large data sets.
Initially, suspects could easily skip bail by traveling out of the country; however, with the invention of AI, monitoring them has become easier since their credit cards can be tracked to obtain their live locations. AI has proved helpful in the criminal justice system by helping address some of the significant challenges police stations have faced, such as improving investigations. Therefore, AI has contributed to a safer society and enhanced efficiency in the justice system.
References
Hayward, K. J., & Maas, M. M. (2021). Artificial intelligence and crime: A primer for criminologists. Crime, Media, Culture, 17(2), 209-233. Web.
Rigano, C. (2019). Using artificial intelligence to address criminal justice needs. National Institute of Justice Journal, 280, 1-10. Web.
Sushina, T., & Sobenin, A. (2020). Artificial Intelligence in the Criminal Justice System: Leading Trends and Possibilities. In 6th International Conference on Social, Economic, and Academic Leadership (ICSEAL-6-2019) (pp. 432-437). Atlantis Press.
Velasco, C. (2022). Cybercrime and artificial intelligence. An overview of the work of international organizations on criminal justice and the international applicable instruments. ERA Forum, 23(1), 109–126. Web.
Završnik, A. (2020). Criminal justice, artificial intelligence systems, and human rights. In ERA Forum, 20(4), 567-583. Springer Berlin Heidelberg.