AI Tools Are Being Employed By Cops Who 'Do Not Comprehend How These Technologies Work': Research

Law enforcement has already begun to use artificial intelligence in its investigations, but “society has a moral obligation to mitigate the detrimental consequences,” according to a recent research.

According to a North Carolina State University paper published in February, AI is still in its infancy, but law enforcement organizations are already incorporating predictive policing, facial recognition, and gunshot detection technology into their investigations.

The paper is based on 20 semi-structured interviews with North Carolina law enforcement officials about how AI affects interactions between communities and police agencies.

“We discovered that study participants were unfamiliar with AI or its limitations,” stated Jim Brunet, co-author of the paper and head of NC State’s Public Safety Leadership Initiative.

“This included artificial intelligence (AI) technologies that participants had used on the job, such as facial recognition and gunshot detection technologies,” he explained. “However, study participants expressed support for these tools, which they felt were valuable for law enforcement.”

According to the survey, law enforcement officers believe AI will increase public safety but may destroy confidence between police and civilians.

This comes at a time when American communities are grappling with the politically charged issue of reducing crime while restoring public faith in the aftermath of George Floyd’s death at the hands of discredited police officers.

Ed Davis, the police commissioner at the time of the 2013 Boston Marathon bombing, said Fox News Digital AI “will ultimately improve investigations and allow many dangerous criminals to be brought to justice.”

However, there are hazards and drawbacks, according to Davis, and criminals will have access to the same technology, which could jeopardize police investigations.

The findings of the investigation support up the well-respected commissioner’s views.

“Policymaking guided by public consensus and collaborative discussion with law enforcement professionals must aim to promote accountability through the application of responsible AI design in policing, with the end state of providing societal benefits and mitigating harm to the populace,” the study concludes.

“There is a moral obligation on society to mitigate the negative consequences of fully integrating AI technologies into law enforcement.”

According to Ronald Dempsey, the study’s primary author and a former graduate student at NC State, part of the problem is police officers’ overall lack of awareness about AI’s capabilities and how they work.

This “makes it difficult or impossible for them to appreciate the limitations and ethical risks,” according to Dempsey. “This can cause significant issues for both law enforcement and the general public.”

The use of facial recognition by law police increased dramatically during the Capitol incident on January 6, 2021.

In 2021, twenty of 42 federal agencies examined by the Government Accountability Office reported using face recognition in criminal investigations.

If upcoming AI technologies “are well-regulated and carefully implemented,” a public safety benefit “can potentially increase community confidence in policing and the criminal justice system,” according to the report.

“However, study participants expressed concerns about the risks of algorithm bias (diversity and representativeness issues), the difficulty of replicating the human factor of empathy, and privacy and trust concerns.”

“In addition, challenges to fairness, accountability, transparency, and explainability remain as presented in the broader academic debate,” the report concludes.

According to the report, AI has the potential to bridge or exacerbate the divide between police and the public, and it is critical that law enforcement leaders have a place at the table for all discussions on the framework for how police might use the technology.

The criteria, according to Veljko Dubljevi, corresponding author of the paper and associate professor at North Carolina State University, can be used to inform AI decision-making.

“It’s also important to understand that AI tools are not foolproof,” Dubljevi stated. “AI is not without limitations.” And if law enforcement personnel are unaware of these restrictions, they may place more importance on AI than is appropriate, which can pose ethical difficulties in and of itself.”

Using face recognition, police have already made mistakes that resulted in unjust arrests.

According to a 2019 study by the National Institute of Standards and Technology, AI systems misidentified African American and Asian faces 10 to 100 times more than White faces.

“There are always dangers when law enforcement adopts technologies that were not developed with law enforcement in mind,” Brunet added.

“This is absolutely true with AI technology like facial recognition. As a result, training in the ethical dimensions of the employment of new AI technology is vital for law enforcement authorities.”

“There are always dangers when law enforcement adopts technologies that were not developed with law enforcement in mind,” Brunet added.

“As a final point, AI policing technologies must be explainable, at least generally, in how decisions are reached,” according to the NC State study.

“At a minimum, law enforcement professionals should have a broad understanding of the AI technologies used in their jurisdictions as well as the criminal justice system as a whole.” “Procedural training for police officers who use artificial intelligence.”

The study was limited to North Carolina and is meant to be a “snapshot” of a developing trend that necessitates additional research and education for law enforcement officers.

AI Tools Are Being Employed By Cops Who ‘Do Not Comprehend How These Technologies Work’: Research

Law enforcement has already begun to use artificial intelligence in its investigations, but “society has a moral obligation to mitigate the detrimental consequences,” according to a recent research.

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