Artificial Intelligence (AI) will soon be a significant part of the lives of people in law enforcement and the rest of the justice system.
AI has the potential to remake law enforcement and the entire justice system.
This article is available as a video podcast on YouTube.
Author
Leonard Adam Sipes, Jr.
Former Senior Specialist for Crime Prevention and Statistics for the Department of Justice’s clearinghouse. Former Director of Information Services, National Crime Prevention Council. Former Adjunct Associate Professor of Criminology and Public Affairs-University of Maryland, University College. Former police officer. Retired federal senior spokesperson.
Former advisor to presidential and gubernatorial campaigns. Former advisor to the “McGruff-Take a Bite Out of Crime” national media campaign. Produced successful state anti-crime media campaigns.
Thirty-five years of directing award-winning (50+) public relations for national and state criminal justice agencies. Interviewed thousands of times by every national news outlet, often with a focus on crime statistics and research. Created the first state and federal podcasting series. Produced a unique and emulated style of government proactive public relations.
Certificate of Advanced Study-The Johns Hopkins University.
Author of ”Success With The Media: Everything You Need To Survive Reporters and Your Organization” available at Amazon and additional booksellers.
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Article
I’m sure this topic scares a lot of people. Artificial Intelligence is new and there are many unknowns.
AI will soon be a significant part of the lives of people in law enforcement and the rest of the justice system. AI is exploding in the technical, health, and legal fields. It will integrate into every aspect of our society so we might as well start the process of exploration within the justice system.
Quite frankly, we within the justice system are taking a bit of a beating. We lost over 25,000 local police personnel. Arrests have plummeted to record lows. Crimes solved are flat after years of decreases. There are endless conversations (and disagreements) as to what works.
Our ability to create predictions of the future dangerousness of criminal offenders is floundering over the lack of a race-neutral risk instrument; it was supposed to revolutionize sentencing and parole and probation operations. Rape kits go untested. DNA goes unprocessed. Violent crime is at record levels per the Bureau of Justice Statistics yet the FBI states that there are reductions.
Yes, I understand this will be an evolution as AI in the justice system gets judicial review but everything we do is subject to challenges. Drones in law enforcement were controversial but today, they are commonplace. Creating lists of dangerous offenders offends the ACLU. It will be the same for AI. Every paper record we have needs to be in a digital format.
Potential Examples
But think of the possibilities for criminal investigation. So a woman is sexually assaulted by a stranger. The victim reports a tattoo of a heart and dagger on his left shoulder. He is a white male approximately 6-3 in weight and weighs 220 pounds. He spoke with a Southern accent. He broke into her home through an unlocked window. He threatened to use force and had a knife. There are no fingerprints or DNA.
The data indicates that sexual assaults with strangers have a very low probability of being solved. But imagine if similar cases were digitized and examined by Artificial Intelligence and shared with area police and parole and probation agencies. Suddenly, you have several hits with one living in the area of the assault. Yes, the case needs to be developed but you have an instant suspect where there would be none previously.
Questions
Can AI create lists of dangerous offenders in your community based on criteria no one could dispute?
Can AL contact parole and probation agents daily with case information looking for possible suspects?
Can AI write your reports with your review?
Can AI create a list of offenders recently released from prison with their previous mode of operations and additional characteristics?
Can AI analyze crime data and predict where crimes will happen down to the block level?
Can AI analyze new drug patterns in your community and link them to potential offenders?
Can AI reduce violent and property crime?
Can AI greatly improve citizen satisfaction through surveys and analysis?
Can AI greatly improve services to crime victims and update them on the status of their victimization?
Can AI help in the development of real-time police command and intelligence centers?
Can AL assist with license plate readers across all states?
Can AI analyze an offender’s social media and summarize data? There are endless photos or videos of criminal offenders boasting about gun use and drugs or violence. Can this be of use in parole and probation or criminal investigations? Can video analysis predict future criminality based on an offender’s own words?
Can AI analyze and explain the discrepancies between the Bureau of Justice Statistics National Crime Victimization Survey (currently the largest increase in violent crime in the nation’s history) and FBI crime data (reductions in the majority of crime categories based on crimes reported to law enforcement)? Can AI give us a definitive answer as to the status of national crime statistics? Can AI analyze national, state, and local crime data and provide guidance?
Is there a possibility of AI overwhelming the justice system with too much data? If AI analyzed the social media of violent offenders on parole and probation and discovered violations, can the courts or parole commission or corrections handle the influx?
What Are the Possibilities?
Artificial intelligence (AI) is increasingly being integrated into various facets of the criminal justice system, offering innovative solutions to longstanding challenges. While the adoption of AI is still in its early stages, several applications have demonstrated the potential to enhance efficiency, accuracy, and fairness within the system.
1. Risk Assessment and Offender Management
AI tools are being developed to assess the potential risk posed by offenders more accurately. By analyzing vast datasets, these systems aim to predict the likelihood of reoffending, thereby informing decisions and resource allocation by pretrial, corrections, and parole and probation agencies. However, implementing such tools has sparked debate regarding their transparency and potential biases. For instance, the use of proprietary AI algorithms in sentencing has raised concerns about due process and the right to a fair trial. A notable case involved an AI tool called Cybercheck, which was used to convict an individual based on its analysis. Subsequent investigations questioned the tool’s reliability and the credibility of its developer, leading to broader discussions about the role of AI in judicial decisions, BusinessInsider.com.
2. Enhancing Police Report Writing
AI-powered applications, such as ChatGPT, are being explored to assist law enforcement officers in drafting reports. These tools can process audio recordings from body cameras and generate initial drafts of incident reports, thereby reducing administrative burdens and allowing officers to focus more on community engagement. For example, certain AI systems can analyze body camera footage and produce a draft report within seconds, streamlining the documentation process, AssociatedPress.
3. Predictive Policing and Resource Allocation
AI’s capability to analyze crime data enables law enforcement agencies to identify patterns and predict potential criminal activity. This predictive policing approach allows for the strategic deployment of resources to areas with a higher likelihood of crime occurrence. However, it’s crucial to ensure that these AI systems are designed to prevent the reinforcement of existing biases, which could lead to disproportionate targeting of certain communities, PoliceChiefMagazine.org.
Another Predictive Policing Example
AI algorithms analyze historical crime data to forecast where crimes are likely to occur, allowing for the strategic deployment of police resources. This method aims to prevent crime by increasing police presence in areas identified as high-risk. However, it is essential to approach predictive policing with caution to avoid potential biases and ensure ethical application, CounciloncCJ.org.
4. Crime Analysis and Pattern Recognition
AI excels at sifting through extensive datasets to uncover connections that might elude human analysts. In the context of criminal investigations, AI can analyze data from multiple crime scenes to identify similarities in methods, potentially linking cases and identifying suspects more efficiently. For instance, AI can process data from various incidents to detect patterns indicative of serial offenses, thereby aiding in faster case resolutions, Police1.com.
Another Crime Pattern Analysis Example
AI systems can analyze vast datasets to identify crime patterns and predict potential criminal activity. The Bedfordshire Police in the UK, for example, have implemented AI tools developed by Palantir to analyze data from multiple sources. This integration has significantly reduced investigation times and improved the identification of at-risk individuals, thereby enhancing crime prevention efforts, TheTimes.co.uk.
5. Legal Research and Case Management
The legal field is also benefiting from AI through tools that assist in legal research and case management. AI can quickly analyze legal documents, precedents, and statutes, providing attorneys and judges with relevant information to inform their decisions. This capability not only accelerates the research process but also enhances the thoroughness of legal analyses, Techuk.org.
6. National Crime Pattern Recognition Database
Imagine an AI-powered system that continuously scans police reports, arrest records, forensic data, and witness statements from jurisdictions across the country. It could flag patterns that suggest a single offender operating in multiple locations, something that human analysts might miss due to jurisdictional silos, OJP.Gov.
7. Automated Criminal Profiling
AI could assist in profiling offenders by analyzing previous crimes and generating behavioral predictions. By studying case histories, forensic psychology data, and known offender behavior, AI could generate insights into a suspect’s likely next move, ResearchGate.
8. AI-Powered Digital Evidence Analysis
Modern crimes generate vast amounts of digital evidence—social media posts, online transactions, phone records, and surveillance footage. AI could analyze these data sources at a speed no human detective could match, OJP.Gov.
9. Cold Case Resolution & DNA Matching
AI could be a game-changer in solving cold cases by re-analyzing old forensic evidence and crime scene data. With improved AI-based DNA matching and facial recognition, cases that have remained unsolved for decades could finally see justice, OJP.Gov.
10. AI in Fraud & Financial Crimes
Financial crimes leave digital trails that AI could analyze far more efficiently than human investigators. AI can detect suspicious transaction patterns, fake identities, and money laundering schemes in real time, OJP.Gov.
11. AI-Powered Witness & Suspect Identification
Imagine an AI system that compiles descriptions from multiple eyewitness accounts and uses facial recognition to generate possible matches from criminal databases. AI could also match scars, tattoos, voiceprints, or even gait patterns caught on security cameras, OJP.Gov.
12. AI-Driven Social Media & Dark Web Monitoring
Criminals frequently communicate on the dark web or encrypted messaging platforms. AI can monitor these spaces for criminal activity, tracking illegal gun sales, drug trafficking, or even preempting violent attacks, OJP.Gov.
13. Facial Recognition Technology
AI-driven facial recognition systems assist in identifying suspects by analyzing surveillance footage and matching faces against criminal databases. For instance, the New York Police Department (NYPD) employs AI-powered facial recognition software to track down suspects in high-profile cases, such as the assassination of United Healthcare CEO Brian Thompson. This technology enables the rapid analysis of extensive surveillance footage, aiding in suspect identification and apprehension, NYPost.com.
14. DNA Analysis and Genetic Genealogy
AI enhances DNA analysis by processing complex genetic information to identify suspects, especially in cold cases. Law enforcement agencies have utilized AI algorithms in conjunction with public genealogy databases to solve cases like the Golden State Killer, where traditional investigative methods had been unsuccessful. This approach involves matching crime scene DNA with potential relatives, leading to the identification of suspects through familial connections, TheScottishSun.co.uk.
15. Gunshot Detection Systems
AI-powered gunshot detection systems, such as ShotSpotter, identify and locate gunfire incidents in real time. These systems analyze acoustic data to distinguish gunshots from other noises, enabling rapid law enforcement response to shooting events. This technology has been instrumental in reducing response times and improving the accuracy of gunfire incident reporting, OJP.gov.
16. AI in Criminal Investigations
AI assists in processing and analyzing digital evidence, such as social media activity, to identify suspects and uncover criminal networks. For example, AI can recognize patterns in online behavior that may indicate criminal activity, aiding investigators in tracking and apprehending offenders, AMU.apus.edu
17. What Works
At the moment, we have endless disputes as to what works and how to judge current and past research projects. We have a system where opinion dominates rather than a hard appraisal of criminal justice data. That may end through AI.
18. Congressional Research Service Appraisal of AI In Law Enforcement
See the Congressional Research Service Appraisal of AI, CRS.
19. Facial Recognition And Drone Technology
Washington’s 2020 S 6280 and Colorado’s 2022 S 113 require an accountability report, data management, security protocols, training procedures and testing, for government entities to use facial recognition technology. Additionally, entities must obtain a warrant or court order to use the technology to conduct ongoing surveillance, real-time identification or tracking. Utah enacted a law that prohibits government entities from using facial recognition on an image database except for law enforcement agencies. Agencies must submit a request and adhere to notice, data protection and disclosure requirements.
20. Border Enforcement
Advanced tech like AI, machine learning, and remote sensing can help our Border Patrol agents track and stop smugglers before they ever get a chance to traffic drugs, crime, and people into our country, NewsNation.
21. INTERPOL
The AI Toolkit was developed by INTERPOL, together with its longstanding partner, the United Nations Interregional Crime and Justice Research Institute (UNICRI), with financial support from the European Union, based on the needs expressed by member countries, to fill gaps in terms of guidance on the development, procurement and use of responsible AI in law enforcement agencies.
The development process was characterized by a highly inclusive, consultative, and iterative process, specifically designed with a view towards ensuring the AI Toolkit is technically and practically sound, promoting close interdisciplinary coordination with industry, academia, criminal justice practitioners, civil society organizations and the public, and fostering a sense of transparency and broader acceptance of law enforcement’s use of AI, INTERPOL.
22. Artificial Intelligence and Criminal Justice Final Report
The policy and technology choices that law enforcement agencies, pretrial and probation services, prison systems, and other criminal justice stakeholders make in the near term will affect millions of Americans. These choices will also set the trajectory for rapid expansion in the scope and scale of AI use throughout the criminal justice system. A comprehensive analysis, US Department of Justice.
Conclusions
We within the justice system have been searching for technology to greatly improve our ability to reduce crime and make communities safer. Thus far, our metrics do not look that good. We thought that fingerprint analysis systems would greatly reduce crime. The same applies to DNA.
To some, what I list above is very concerning conjuring thoughts of an invasive “big brother” society controlled by computers and over-aggressive law enforcement or government. I and others who share civil liberties concerns understand your apprehensions.
However, there will be endless legal challenges and court rulings as to what the justice system can and cannot do with AI. None of this will be created in a vacuum. The justice system will have to be exceptionally transparent as to what it’s doing and why.
Implementing AI in crime-solving faces legal and ethical roadblocks. Privacy laws prevent unrestricted access to personal data, and concerns about AI bias, false positives, and misuse must be addressed. But with proper oversight, transparency, and ethical AI use, these tools could drastically improve law enforcement’s ability to solve crimes and promote safety.
Crime has a way of destroying our cities and our collective peace of mind. What parents need to do with children to warn them of actions they need to take for their safety is tragic. Urban areas lack jobs and economic prosperity because no one wants to invest in areas deemed unsafe. Crime greatly hampers the ability of children to prosper in schools.
While AI offers promising advancements in criminal justice, it is crucial to address ethical considerations, including privacy concerns, potential biases in AI algorithms, and the need for human oversight in AI-assisted decision-making processes. Balancing technological innovation with civil liberties ensures that AI serves as a tool for justice without compromising individual rights.
Note
This article is based on original writing and responses created by Chat GPT and Google searches. Chat GPT sources were reviewed for relevancy. Chat GPT responses were examined and edited when necessary.
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