Artificial intelligence (AI) is everywhere today. While that’s an exciting prospect to some, it’s an uncomfortable thought for others. Applications like AI-powered traffic cameras are particularly controversial. As their name suggests, they analyze footage of vehicles on the road with machine vision.
They’re typically a law enforcement measure — police may use them to catch distracted drivers or other violations, like a car with no passengers using a carpool lane. However, they can also simply monitor traffic patterns to inform broader smart city operations. In all cases, though, they raise possibilities and questions about ethics in equal measure.
How Common Are AI Traffic Cameras Today?
While the idea of an AI-powered traffic camera is still relatively new, they’re already in use in several places. Nearly half of U.K. police forces have implemented them to enforce seatbelt and texting-while-driving regulations. U.S. law enforcement is starting to follow suit, with North Carolina catching nine times as many phone violations after installing AI cameras.
Fixed cameras aren’t the only use case in action today, either. Some transportation departments have begun experimenting with machine vision systems inside public vehicles like buses. At least four cities in the U.S. have implemented such a solution to detect cars illegally parked in bus lanes.
With so many local governments using this technology, it’s safe to say it will likely grow in the future. Machine learning will become increasingly reliable over time, and early tests could lead to further adoption if they show meaningful improvements.
Rising smart city investments could also drive further expansion. Governments across the globe are betting hard on this technology. China aims to build 500 smart cities, and India plans to test these technologies in at least 100 cities. As that happens, more drivers may encounter AI cameras on their daily commutes.
Benefits of Using AI in Traffic Cameras
AI traffic cameras are growing for a reason. The innovation offers a few critical advantages for public agencies and private citizens.
Safety Improvements
The most obvious upside to these cameras is they can make roads safer. Distracted driving is dangerous — it led to the deaths of 3,308 people in 2022 alone — but it’s hard to catch. Algorithms can recognize drivers on their phones more easily than highway patrol officers can, helping enforce laws prohibiting these reckless behaviors.
Early signs are promising. The U.K. and U.S. police forces that have started using such cameras have seen massive upticks in tickets given to distracted drivers or those not wearing seatbelts. As law enforcement cracks down on such actions, it’ll incentivize people to drive safer to avoid the penalties.
AI can also work faster than other methods, like red light cameras. Because it automates the analysis and ticketing process, it avoids lengthy manual workflows. As a result, the penalty arrives soon after the violation, which makes it a more effective deterrent than a delayed reaction. Automation also means areas with smaller police forces can still enjoy such benefits.
Streamlined Traffic
AI-powered traffic cameras can minimize congestion on busy roads. The areas using them to catch illegally parked cars are a prime example. Enforcing bus lane regulations ensures public vehicles can stop where they should, avoiding delays or disruptions to traffic in other lanes.
Automating tickets for seatbelt and distracted driving violations has a similar effect. Pulling someone over can disrupt other cars on the road, especially in a busy area. By taking a picture of license plates and sending the driver a bill instead, police departments can ensure safer streets without adding to the chaos of everyday traffic.
Non-law-enforcement cameras could take this advantage further. Machine vision systems throughout a city could recognize congestion and update map services accordingly, rerouting people around busy areas to prevent lengthy delays. Considering how the average U.S. driver spent 42 hours in traffic in 2023, any such improvement is a welcome change.
Downsides of AI Traffic Monitoring
While the benefits of AI traffic cameras are worth noting, they’re not a perfect solution. The technology also carries some substantial potential downsides.
False Positives and Errors
The correctness of AI may raise some concerns. While it tends to be more accurate than people in repetitive, data-heavy tasks, it can still make mistakes. Consequently, removing human oversight from the equation could lead to innocent people receiving fines.
A software bug could cause machine vision algorithms to misidentify images. Cybercriminals could make such instances more likely through data poisoning attacks. While people could likely dispute their tickets and clear their name, it would take a long, difficult process to do so, counteracting some of the technology’s efficiency benefits.
False positives are a related concern. Algorithms can produce high false positive rates, leading to more charges against innocent people, which carries racial implications in many contexts. Because data biases can remain hidden until it’s too late, AI in government applications can exacerbate problems with racial or gender discrimination in the legal system.
Privacy Issues
The biggest controversy around AI-powered traffic cameras is a familiar one — privacy. As more cities install these systems, they record pictures of a larger number of drivers. So much data in one place raises big questions about surveillance and the security of sensitive details like license plate numbers and drivers’ faces.
Many AI camera solutions don’t save images unless they determine it’s an instance of a violation. Even so, their operation would mean the solutions could store hundreds — if not thousands — of images of people on the road. Concerns about government surveillance aside, all that information is a tempting target for cybercriminals.
U.S. government agencies suffered 32,211 cybersecurity incidents in 2023 alone. Cybercriminals are already targeting public organizations and critical infrastructure, so it’s understandable why some people may be concerned that such groups would gather even more data on citizens. A data breach in a single AI camera system could affect many who wouldn’t have otherwise consented to giving away their data.
What the Future Could Hold
Given the controversy, it may take a while for automated traffic cameras to become a global standard. Stories of false positives and concerns over cybersecurity issues may delay some projects. Ultimately, though, that’s a good thing — attention to these challenges will lead to necessary development and regulation to ensure the rollout does more good than harm.
Strict data access policies and cybersecurity monitoring will be crucial to justify widespread adoption. Similarly, government organizations using these tools should verify the development of their machine-learning models to check for and prevent problems like bias. Regulations like the recent EU Artificial Intelligence Act have already provided a legislative precedent for such qualifications.
AI Traffic Cameras Bring Both Promise and Controversy
AI-powered traffic cameras may still be new, but they deserve attention. Both the promises and pitfalls of the technology need greater attention as more governments seek to implement them. Higher awareness of the possibilities and challenges surrounding this innovation can foster safer development for a secure and efficient road network in the future.
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