Artificial intelligence ( AI ) has increasingly become a topic of concern for public safety . While AI has the potential to streamline processes , improve efficiency , and aid decision making , it is essential that we address the dangers and complexities associated with its implementation , especially in a police environment . This article digs into the potential risks posed by AI in police operations and discipline matters , explores the need for high-level scrutiny of technology , and discusses ethical considerations that must be closely monitored .
As AI-enabled technologies rapidly emerge , they are quickly outpacing the development of policies that regulate their use . In police discipline matters , AI being implemented in this fashion can cause massive problems that are not being considered or discussed .
AI companies promote that their AI systems have the ability to analyze vast amounts of data to find patterns and generate insights that support disciplinary actions , which is a benefit to all . I am here to tell you there are more downsides and dangers than benefits to the use of AI .
One of the primary concerns surrounding AI in police discipline matters is the reliance on potentially biased or incomplete data . If AI systems are trained on datasets that reflect existing disparities or prejudices , there is a risk of perpetuating these biases in disciplinary actions . This could lead to unfair treatment or , even worse , incorrect investigatory outcomes for officers .
Another significant concern lies in the lack of transparency and accountability of AI systems . The decisionmaking process of AI algorithms can be complex and difficult to understand , making it challenging to hold these systems accountable for their actions . Companies also keep certain parts of their algorithms concealed as company secrets . This will also lead to untrustworthiness of the system amongst officers .
Despite the advantages and capabilities of AI , its imperfections are well-known to users of AIpowered tools like ChatGPT .
THESE TOOLS , WHILE ADVANCED , ARE PRONE TO INACCURACIES , MISINFORMATION , AND HONEST ERRORS .
However , within the context of law enforcement , such shortcomings carry grave implications . You can read about AI systems outcomes resulting in wrongful arrests , misallocation of resources , or even unwarranted uses of force . So , take that information and think about what could happen to an officer who is under investigation conducted by AI systems .
The PLEA Executive Board , after attending a couple of seminars , determined that we needed to address this early on and negotiated a starting point within our contract . Currently , as of the publishing of this article , we are the only association in the nation to our knowledge that has contract language that reflects officers ’ rights and the limitations of use of AI by a department . We will continue to attempt to improve this section of the contract .
While AI can process vast amounts of data , it often lacks the ability to understand nuanced human behavior and context . Disciplinary investigations require a deep understanding of the complexities involved , such as the emotional state of individuals involved , their intentions , and the overall context of the situation . No two investigations are the same , nor should they be treated as such . Relying solely on AI-generated recommendations may overlook critical factors , potentially leading to unjust outcomes and taking away trust from the officers who are being judged by a piece of tech rather than by a human .
The concern of AI systems has even been discussed during Senate hearings to talk about its application for police work . Those hearings focused on the use for daily police operations , but the concerns can also be viewed on the discipline side of the job .
Agencies are already learning that implementation of the systems requires in-depth policy work . These polices should mandate additional evidence beyond AI-based information , underscoring the technology ’ s role as an assistant rather than a definitive arbiter in investigations .
Regulation and oversight are paramount in addressing the challenges AI introduces to policing . The push for independent accuracy verification and national training standards highlights an urgent need for strict guidelines to govern AI ’ s use , aiming to mitigate risks like bias and privacy breaches .
As AI continues to evolve , its integration into police discipline needs to be completed with extreme caution , acknowledging and mitigating the risks associated with biased data , lack of transparency , and the limitations of AI systems . Is there a place for AI in police work ? There might be in certain avenues , but in discipline matters , we still believe the old-fashioned way that has been around for decades does fine .
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