Author
Leonard Adam Sipes, Jr.
Former senior specialist for crime prevention and statistics for the Clearinghouse of the Ministry of Justice. Former director of Information Services, National Crime Prevention Council. Former deputy university teacher Criminology and Public Affairs University of Maryland, University College. Former police officer. Retired federal senior spokesperson.
Former adviser of presidential and gubernatorial campaigns. Former adviser of the national media campaign “McGruff-Take a Bite of Crime”. Produced successful media campaigns against crimes.
Thirty -five years of directing award -winning (50+) public relations for national and national criminal agencies. Thousands of times interviewed by every national news exit, often with a focus on crime statistics and investigation. Created the first State and Federal Podcasting series. Produced a unique and emulated style of proactive public relations from the government.
Certificate of advanced study-de Johns Hopkins University.
Author of “Good luck with the media: everything you need to survive reporters and your organization“Available at Amazon and extra booksellers.
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Article
I am sure this subject scares many people. Artificial intelligence is new and there are many strangers.
AI will soon be an important part of the lives of people in law enforcement and the rest of the legal system. AI explodes in the technical, health and legal areas. It will integrate into every aspect of our society, so that we can just as well start the process of exploration within the legal system.
To be honest, we take a bit of a beating within the legal system. We have lost more than 25,000 local police personnel. Arrests have plummeted to record lows. Resolved crimes are just after years of decreases. There are endless conversations (and disagreements) about what works.
Our ability to create predictions of the future danger of criminal perpetrators has escaped the lack of a racing-neutral risk instrument; It was supposed to bring about a revolution in the conviction and conditional release and probation activities. Rape kits do not go out. DNA becomes unprocessed. Violent crime is at record levels according to the Bureau of Justice Statistics, but the FBI states that there are reductions.
Yes, I understand that this will be an evolution, because AI receives a judicial assessment in the legal system, but everything we do is subject to challenges. Drones in law enforcement were controversial, but nowadays they are commonplace. Making lists with dangerous offenders insults the ACLU. It will be the same for AI. Every paper record we have must be in a digital format.
Possible examples
But think of the possibilities for criminal investigation. So a woman is sexually abused by a stranger. The victim reports a tattoo of a heart and dagger on his left shoulder. He is a white man of about 6-3 in weight and weighs 220 pounds. He spoke with a southern accent. He broke in her house through an unlocked window. He threatened to use violence and had a knife. There are no fingerprints or DNA.
The data indicates that sexual attacks with strangers have a very low chance of being resolved. But imagine that similar cases were digitized and investigated by artificial intelligence and shared with area police and conditional and probation agencies. Suddenly you have different hits with one who lives in the area of the attack. Yes, the case must be developed, but you have a direct suspect where there would be none before.
To ask
Can AI make lists of dangerous perpetrators in your community based on criteria that nobody can dispute?
Can you already contact conditional release and probation information with Case information Looking for possible suspects?
Can AI write your reports with your review?
Can AI make a list of offenders who have recently released from prison with their earlier operating method and extra characteristics?
Can AI crime data analyze and predict where crimes will take place until the block level?
Can AI analyze new drug patterns in your community and link them to potential perpetrators?
Can AI reduce violent and property crime?
Can AI significantly improve the satisfaction of the citizens through surveys and analysis?
Can AI significantly improve the services for victims of crimes and update on the status of their victimization?
Can AI help with the development of real-time police command and intelligence centers?
Can already help with license plate readers in all states?
Can AI analyze the social media of a perpetrator and summarize data? There are endless photos or videos of criminal perpetrators that brag about the use of weapons and drugs or violence. Can this be of use in conditional release and probation or criminal investigations? Can video -analysis predict future crime based on the own words of a perpetrator?
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 history of the nation) and FBI crime data (reductions in the majority of crime categories) reported on crimes? Can AI give us a definitive answer about the status of national crime statistics? Can AI analyze and provide national crime data and provide guidance?
Is there a possibility that AI overwhelms the legal system with too much data? If AI analyzed the social media of violent perpetrators on conditional release and probation and discovered violations, can the courts or conditional committee or corrections deal with the influx?
What are the possibilities?
Artificial intelligence (AI) is increasingly being integrated into various facets of the criminal justice system and offers innovative solutions for long -term challenges. Although the approval of AI is still in the early stages, various applications have shown that it is potential to improve efficiency, accuracy and fairness within the system.
1. Risk assessment and perpetrator management
AI tools are being developed to more accurately assess the potential risk of perpetrators. By analyzing enormous data sets, these systems are intended to predict the probability of recidivism, so that decisions and resources allocation are informed by pretrial, corrections and conditional and probation agencies. However, implementing such tools has led to a debate about their transparency and potential prejudices. For example, the use of own AI algorithms in the conviction has expressed concern about the right process and the right to a fair trial. A remarkable case was an AI tool called Cybercheck, which was used to condemn a person based on the analysis. Subsequent studies doubted the reliability of the tool and the credibility of the developer, which led to broader discussions about the role of AI in judicial decisions, Businessinsider.com.
2. Improving writing the police report
AI-driven applications, such as Chatgpt, are being investigated to help law enforcement officers prepare reports. These tools can process audio recordings of body cameras and generate initial concepts of incident reports, reducing administrative burdens and officers can concentrate more on community involvement. Certain AI systems can, for example, analyze body camera images and produce a draft report within a few seconds, so that the documentation process is streamlined, AssociatedPress.
3. Predictive police and allocation of resources
AI’s ability to analyze crime data enables law enforcement agencies to identify patterns and to predict potential criminal activities. This predictive police approach makes it possible to take strategic use of resources in areas with a greater chance of a crime. However, it is crucial to ensure that these AI systems are designed to prevent the strengthening of existing prejudices, which could lead to disproportionate targeting of certain communities, PoliceChiefmagazine.org.
Another predictive police forces
AI algorithms analyze historical crime data to predict where crimes are likely to take place, making the strategic use of police sources possible. This method is intended to prevent crime by increasing the presence of the police in areas that are identified as a high risk. However, it is essential to approach predictive police work with caution to prevent possible prejudices and to guarantee ethical application, Councilonccj.org.
4. Crime analysis and pattern recognition
AI excels in searching extensive data sets to discover connections that human analysts can miss. In the context of criminal investigations, AI can analyze data from multiple location offenses to identify agreements in methods, to link cases and to identify suspects more efficiently. AI can, for example, process data from different incidents to detect patterns that indicate serial offenses, which helps it in faster case resolutions, Police1.com.
Another example of a crime pattern analysis example
AI systems can analyze huge data sets to identify crime patterns and predict potential criminal activities. For example, the Bedfordshire police in the UK has implemented AI tools developed by Palantir to analyze data from multiple sources. This integration has considerably reduced research times and improved the identification of risky individuals, improving the efforts for crime prevention, Thetimes.co.uk.
5. Legal research and case management
The legal field also benefits from AI through tools that help with legal research and case management. AI can quickly analyze legal documents, precedents and articles of association and provide lawyers and judges with relevant information to inform their decisions. This capacity not only speeds up the research process, but also improves the thoroughness of legal analyzes, Techuk.org.
6. National Crime Pattern Recognition Database
