Streamlining Society: The Case for AI at the DMV, TSA, and Taxis
When people talk about automation and artificial intelligence, the conversation often drifts toward extreme scenarios. Some worry about robots taking over every job, while others dream about a fully automated world where everything just works. In reality, we are still far from that point and are just building the stepping stones. If I had to pick the first areas where AI and automation could make a major positive impact, I would choose the TSA, the DMV, and ride-hailing services.
Why Start with These Jobs?
These sectors are famous for inefficiency, slow service, and widespread public frustration. Ask almost anyone about their least favorite experiences in day-to-day life, and there’s a good chance a story about the DMV, TSA, or a bad taxi ride will come up. The common thread across these jobs is a combination of bureaucracy, bad customer service, and outdated systems.
TSA: Streamlining Security Without Sacrificing Safety
The airport security process is often the first real test of patience for any traveler. Long lines, inconsistent screening procedures, and sometimes indifferent or even rude staff are regular complaints. While security is obviously important, the current system is labor-intensive and not always effective at catching real threats. Since the early 2000s, we’ve seen that the changes made to TSA have been unnecessary in stopping threats.
I think AI-based scanners, facial recognition, and automated baggage checks could make the TSA process much more efficient. In most cases, the process could be completely automated, with just a few human supervisors present to intervene in unusual cases or handle issues that machines cannot address. This would cut down wait times, reduce staffing costs, and potentially increase security by removing human error and bias.
DMV: No More Endless Lines
If you want to hear people complain about inefficiency, just mention the DMV. Most people have lost hours of their lives sitting in a dingy waiting room, staring at a number screen, and wondering why the process is so slow. When I visit the DMV, I notice simple improvements that could make the process quicker. The DMV is essentially a paperwork-processing center, and there is little reason why most tasks such as renewing licenses, transferring titles, or registering vehicles should require a person behind a desk.
Most DMV functions can be handled through digital portals with AI verification for identity, document authenticity, and eligibility. The system could automatically flag exceptions for review by the small number of staff still needed onsite. Not only would this make things faster, but it would also reduce costs for state governments and free up employees for more complex roles that truly require human judgment. With AI handling the routine, people would only need to visit a main office for rare cases, such as complicated legal issues or system failures. A facility with a window system could serve many people each day, requiring only a few workers for exceptional cases.
Taxis and Ride-Hailing: Toward a Smoother Ride
Taxis and ride-hailing services like Uber and Lyft are already partly automated, with apps that match drivers to passengers and process payments. The next step is self-driving cars. The technology is still being refined, but there are already clear benefits to moving in this direction. Most complaints about taxi services revolve around driver behavior, inconsistent pricing, and concerns about safety. Waymo and Tesla’s Robotaxi are demonstrating early success, and both the technology and public acceptance are steadily improving.
By automating the driving itself, AI-powered vehicles could provide reliable, consistent service at lower costs. Machines will not take longer routes to increase the fare, and there will be no language barriers when giving instructions. Automated taxis can be available 24/7 and can be dispatched efficiently according to real-time demand. As with the other examples, some human oversight will still be needed for technical support or handling incidents a machine cannot address.
Common Objections and the Role of Humans
Some people worry that automating these jobs means eliminating all human interaction. That is an overreaction. Automation should improve service, not remove humans entirely. In the examples I’ve mentioned, there is still a need for people: supervisors at TSA checkpoints, experts handling DMV edge cases, or remote operators available to take control of a self-driving car if needed. The point is to let machines handle routine, repetitive, or unpleasant tasks so that people can focus on roles that require empathy, expertise, or creativity. The future of work does not have to be dystopian. It can be practical, efficient, and a lot less aggravating than the systems we have now.