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Law Enforcement Eyes AI for Investigations and Analysis
With AI, police have access to a powerful new tool. Here's a look at its uses -- and potential misuses.
5 Min Read
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AI has an almost endless array of potential applications, yet none may be more important or higher priority than its use as a law enforcement investigatory and analysis technology.
AI has a tremendous and very exciting potential to streamline various aspects of law enforcement, making processes more efficient and effective, says David Rome, an attorney with Los Angeles criminal defense law firm Gomez, Radford, & Rome, in an email interview.
Marcus Claycomb, a retired member of the Melbourne, Fla., police department and current business development manager at IT professional services firm Panasonic Connect, agrees. "AI will likely see slow and steady adoption across the law enforcement sector," he states via email.
Multiple Applications
AI will soon supplement crime analysis, Claycomb predicts. "By streamlining data collection and interpretation, crime analysis teams will have more time to be proactive and develop new strategies in response to data findings," he explains. "With so many police departments facing staffing shortages, technologies that support proactivity, instead of reactivity, will be crucial to boosting efficiency and ensuring the most effective response."
Rome believes that evidence analysis will emerge as another important AI-enabled law enforcement tool. "Sifting through vast amounts of digital evidence, such as social media logs or financial statements, to identify relevant information is currently an extremely tedious and repetitive task that consumes an inordinate amount of time," he explains. AI promises to streamline the process by highlighting key information that police and prosecutors can use during their investigation. These individuals could then focus on making creative and human decisions rather than wasting time on boring drudgery.
Another AI-enabled technology -- facial recognition -- using private surveillance or public cameras, can help law enforcement identify suspects or missing persons. Meanwhile, AI fraud detection technology can identify patterns in documents indicative of unlawful activities, accurately highlighting and detecting patterns for law enforcement flagging, Rome says.
By automating the analysis of large datasets, AI can supplement traditional investigative techniques, freeing human resources to tackle more complex tasks, Rome says. "AI can also replace outdated manual processes, such as sorting through paper records, with more efficient digital solutions," he adds.
Claycomb notes that studying crime analytics is currently a time-consuming process. "With limited time, staff must review all handwritten and digital reports, along with third-party information, before they can begin to analyze it," he says. "Using AI to synthesize the data will help crime analytics teams spend less time on tedious work and more time on the findings and improving future strategies."
For all of its potential benefits, AI is also vulnerable to misuse. Weak oversight, for instance, can lead to biases in predictive policing or errors in evidence analysis. "It's crucial to implement checks and balances to ensure that AI is used ethically and accurately," Rome says. Meanwhile, many law enforcement organizations are reluctant to embrace technology due to budget constraints, a lack of technical expertise, and an overall resistance to change.
Concerns about privacy and civil liberties are also hindering adoption. In particular, there's the possibility of AI bias, which can lead to inaccurate conclusions when discriminatory data and algorithms are baked into AI models.
Looking Forward
Despite the challenges, the long-term outlook is promising, Rome says. "As technology advances and law enforcement agencies become more familiar with AI's potential, its adoption is likely to increase," he predicts. Claycomb agrees, but notes that adopters will need to implement workflows that take full advantage of other technology tools, including deploying powerful and connected mobile device fleets.
Claycomb believes that AI can also help law enforcement agencies cope with persistent staff shortages. In recent years, most agencies have witnessed a significant team shortfall with more officers retiring than entering the field. "The only way to perform more work with less resources is to adopt more efficient tech-driven workflows," he says. "That’s where we’ll see more law enforcement departments turn to AI platforms."
Last Thoughts
It's important to note that while AI can greatly assist law enforcement, it should never be considered as a replacement for human judgment, especially when someone's freedom is potentially on the line, Rome says. "AI should be seen as a tool to enhance the capabilities of law enforcement officers, not to replace them." He feels that continuous monitoring and evaluation will be necessary to ensure accuracy and fairness. "Although I'm optimistic about AI's future in law enforcement, its implementation must be approached with caution, ensuring that it's used ethically and responsibly."
This is an exciting time, Claycomb says. "Having worked in the law enforcement industry for more than two decades, I've witnessed the introduction of various technologies to transform workflows," he states. "When implemented well, in accordance with government regulations for use and security, AI will be game-changing."
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