The idea of artificial intelligence (AI) in law enforcement may evoke images of dystopian futures like those in the movie Minority Report, where authorities arrest suspects before any crime occurs. Others might imagine a surveillance state with residents identified and tracked through facial recognition technology, networked cameras, and automated license plate readers. However, while some local leaders acknowledge the risks of imperfect algorithms and potential biases, many believe AI’s benefits make it worth exploring.
AI’s Role in Crime Prevention
In a recent speech at the International City and County Manager Association’s conference in Palm Springs, California, Corona’s Chief Innovation Officer, Chris McMasters, discussed the city’s approach to integrating AI in law enforcement. According to McMasters, Corona is using AI-driven data analysis to map crime hotspots and direct policing resources more effectively. By identifying crime patterns, the technology aims to locate drug stash houses and other criminal activities, although human oversight remains essential to prevent errors.
“We don’t want to tie everyone down to where we can’t be innovative,” McMasters stated. “Yet we want to make sure that people are safe and that we are doing it responsibly.” Corona also plans to launch a real-time crime center with AI-integrated cameras to spot incidents as they occur.
Navigating Risks and Benefits
McMasters emphasized the need to balance innovation with responsibility, especially considering the historical discrimination faced by certain communities. He mentioned that the police chief is working to “get ahead” of officers’ desire to use AI in report filing by outlining clear guidelines for its use.
While AI’s applications in other government sectors, such as translating communications and managing traffic signals, are relatively low-risk, its use in law enforcement carries higher stakes. “Anytime you’re looking at criminal-type things, there’s a hefty weight to that,” McMasters said. He highlighted the existing laws governing law enforcement practices and the importance of balancing risk and reward.
Skepticism and Oversight
External groups remain skeptical of AI in policing. The NAACP, in a policy brief, warned that predictive policing and AI could “increase racial biases” despite their goal of improving “efficiency and objectivity.” The organization calls for rigorous oversight, transparency, community engagement, and legal frameworks, and advocates banning the use of historical crime data known to contain racial biases.
Lawmakers share these concerns. In a January letter to U.S. Attorney General Merrick Garland, seven members of Congress urged the Department of Justice to halt all grants for predictive policing systems until assurances can be made that they won’t be used in discriminatory ways.
Learning from Other Cities
Insights from other cities can help inform AI’s role in law enforcement. During a panel discussion at the Smart City Expo USA in New York City, New Orleans CIO Kimberly LaGrue described AI as a “force multiplier” that can enhance officers’ effectiveness. For instance, AI can help identify individuals violating temporary restraining orders by frequenting banned areas.
Despite potential controversy and backlash, McMasters urged local leaders not to shy away from new technology in public safety. “My worry is that we’re so risk-averse sometimes that we’re not willing to try,” he said.
AI in law enforcement presents both significant risks and promising opportunities. While the technology could revolutionize crime prevention and resource allocation, it also requires careful oversight to avoid perpetuating biases and infringing on civil liberties. As cities like Corona and New Orleans explore AI’s potential, finding the right balance between innovation and responsibility will be crucial.
