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Study finds that police are employing AI tools without a comprehensive understanding of their functionality
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Study reveals law enforcement's lack of understanding of AI technologies and the need for ethical considerations
A recent study highlights the revolutionary impact of artificial intelligence (AI) in law enforcement, with predictive policing, facial recognition, and gunshot detection systems already integrated into investigations. However, the study raises concerns about the detrimental consequences of AI and emphasizes the moral obligation to mitigate risks associated with its use.
Crowd of business people tracked with technology walking on busy urban city streets. CCTV AI facial recognition big data analysis interface scanning, showing animated information. (Getty Images)
Conducted by North Carolina State University, the study interviewed law enforcement professionals in North Carolina and examined the effects of AI on community-police relationships. The findings revealed that participants lacked familiarity with AI technologies and their limitations, even though they expressed support for their value in law enforcement.While AI is believed to enhance public safety, there are concerns that it may erode trust between police and civilians. This issue arises at a time when American cities are grappling with the challenge of reducing crime while rebuilding public trust following high-profile incidents like the murder of George Floyd.
Law enforcement officials recognize the potential benefits of AI in investigations but acknowledge the accompanying risks. Criminals gaining access to the same technology could impede police efforts. The study suggests that policymaking should promote accountability through responsible AI design in policing and aim to provide societal benefits while mitigating harm.
One of the study's key findings is the general lack of knowledge among police officers regarding AI capabilities and operations. This knowledge gap hinders their understanding of limitations and ethical risks, creating challenges for both law enforcement and the public. Facial recognition technology, for example, experienced significant adoption after the January 6, 2021 Capitol riot.
The study highlights the importance of well-regulated and carefully implemented AI technologies to increase community confidence in policing and the criminal justice system. However, concerns remain regarding algorithmic bias, empathy replication, privacy, trust, fairness, accountability, transparency, and explainability.
Now-retired Boston Police Commissioner Edward Davis III testifying on Capitol Hill in Washington, on July 10, 2013, before the Senate Homeland Security and Governmental Affairs Committee hearing to review the lessons learned from the Boston Marathon bombings.
According to the study, AI has the potential to bridge or deepen the divide between police and the public. To ensure responsible AI decision-making, law enforcement leaders must be actively involved in discussions about the framework for technology use. Guidelines derived from the study can inform AI implementation and foster understanding of AI's limitations among law enforcement officials.The study underscores the need for a transparent culture of accountability that demonstrates how AI technologies are used in police investigations. Instances of wrongful arrests resulting from flawed facial recognition algorithms highlight the dangers of adopting technologies without sufficient understanding. It is crucial for law enforcement professionals to receive ethical training related to AI technologies.
The study concludes that AI policing technologies should be explainable to some extent, and law enforcement professionals should have a broad understanding of the AI technologies utilized in their jurisdictions. Procedural training should be provided to police officers who utilize AI technology. The study's scope was limited to North Carolina and serves as a preliminary analysis, highlighting the necessity for further research and education for law enforcement professionals in this emerging field.
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