Rush to Judgment: Before We Blame AI, Let’s Look at What It’s Actually Doing
Artificial intelligence is changing the way communities identify and respond to property conditions, and that is something local governments should be paying attention to.
Innovative, game-changing technology is giving cities the ability to identify conditions across entire communities that previously might have gone unnoticed until a resident complained or a code officer happened to drive by.
That doesn’t mean the technology should be adopted without questions.
Privacy, accuracy, transparency and appropriate safeguards are legitimate concerns. But before we decide that AI itself is the problem, we should take a closer look at how the technology is actually being used.
Dallas provides a good example.
The Dallas Story
A recent NBC 5 Investigates report (click here) examined Dallas’ use of City Detect‘s AI-powered cameras mounted on trash trucks to identify potential code violations. Since the program began, the cameras have identified tens of thousands of potential property conditions, with more than 21,000 properties receiving what the city calls a “blight score.”
The reaction has been mixed.
Some residents have raised concerns about privacy and the potential impact of increased code enforcement on lower-income neighborhoods. But one reaction reported by NBC 5, an effort by Councilmember Chad West to strip funding from the program, is premature.
Why?
Because the camera isn’t issuing citations.
The AI isn’t determining that a property has violated the code.
And the system isn’t deciding who gets fined.
The technology identifies potential conditions and puts the images in front of Code Compliance staff. Human reviewers examine the detection before the city takes enforcement action. Dallas has said that AI-generated detections are reviewed and validated by city staff before enforcement.
And the initial communication is a courtesy notice.
The purpose is to give the property owner an opportunity to correct the condition voluntarily. According to Dallas officials, the city has seen substantial voluntary compliance following notices. A recent analysis in Governing reported that approximately 80% of recipients comply after receiving a letter.
That makes the characterization of the program as simply a “money grab” difficult to reconcile with the actual process.
There Is More to the Dallas Story
There is another part of the Dallas story that shouldn’t be overlooked.
Dallas has Code Cares, a program designed to help elderly and disabled residents who may not have the financial resources to address property violations.
The city’s Code Compliance department also conducts community outreach, provides training and resources, organizes neighborhood cleanups and supports volunteer programs.
That presents a very different picture from an automated machine simply driving around looking for opportunities to issue fines.
The technology is a tool.
What matters is how the city uses it.
And No, This Isn’t Flock
Another comparison that deserves some clarification is the suggestion that these systems are essentially the same as Flock cameras.
They’re not.
The Dallas system is designed to identify property conditions from the public right-of-way. According to City Detect, faces and license plates are blurred, the system is not connected to federal databases, and a city employee must review a detection before action is taken.
That doesn’t mean there should be no oversight.
There absolutely should be.
Cities should establish clear rules regarding what is captured, how information is stored, who can access it, how long it is retained and how residents can challenge an erroneous determination.
Those are reasonable questions.
But reasonable questions are very different from calling for the elimination of the technology before evaluating whether it is actually producing better outcomes.
A Different Perspective From Cleveland
And this is where another recent article deserves attention.
Writing in Governing, Stephen Goldsmith examined how Cleveland and Dallas are using AI-powered vision technology to identify neighborhood conditions. His conclusion was notably different from the narrative that AI-powered cameras are inherently punitive.
Cleveland’s partnership with City Detect, for example, has been used to survey properties, identify emerging issues and even help validate whether conditions have been corrected after a notice is sent. The technology has allowed the city to survey roughly 158,000 parcels, work that Governing says would previously have required approximately 40 officers over six months.
That’s a significant distinction.
The technology isn’t replacing code officers.
It is helping them see more.
And perhaps even more importantly, it can allow them to spend less time driving around looking for problems and more time actually addressing them.
As Goldsmith put it, the measure of success should be the property condition that gets corrected, not the number of tickets written.
That’s a perspective worth considering.
Another Rush to Judgment?
The Dallas debate isn’t happening in isolation.
Just days later, House Oversight Committee Chairman James Comer raised concerns about Washington, D.C.’s plans to use panoramic cameras and AI to identify vacant properties and external property maintenance violations. His concerns included the potential for fines, tax debt and foreclosure.
Again, those are issues worth examining.
But there is a danger in moving from “How will this technology be used?” to “This technology shouldn’t be used.”
Those aren’t the same question.
In fact, the Dallas and Cleveland experiences suggest that the more productive question may be:
Can this technology help communities identify problems earlier, communicate with property owners sooner and use limited code enforcement resources more effectively?
That’s a question that can actually be answered.
The Conversation We Should Be Having
AI shouldn’t get a free pass.
Neither should government.
Cities need safeguards. They need transparency. They need human oversight. And they need to demonstrate that technology is being used to improve neighborhoods, not simply to increase enforcement activity.
But eliminating an innovative tool simply because it can be misused would mean ignoring its potential benefits.
For communities struggling with limited code enforcement staff, thousands of properties and growing demands on municipal services, the ability to identify emerging property conditions across an entire city could be transformative.
The goal shouldn’t be more citations.
It should be better neighborhoods, earlier intervention and better communication with property owners.
Before we throw the technology out, let’s determine whether it is working, whether it is being used responsibly and whether it is helping communities address problems sooner.
That’s the conversation worth having.
And with that additional context, the Dallas story, and the broader debate over AI in code enforcement, looks a lot different.