When my 12-year-old looked up the word autonomous, the definition was straightforward: self-governing, independent. That is exactly why the term breaks down when applied to robotaxis.
Calling them autonomous flatters the technology and hides who is responsible when something goes wrong. It shapes how the public and policymakers understand these systems. Autonomous suggests a machine that governs itself.
But the systems now being deployed on public roads, especially robotaxis, rely on human support, operational oversight, maintenance, and institutional coordination that the label obscures. Calling these vehicles autonomous does not just flatter the technology. It narrows accountability.
That matters because language shapes governance. If leaders believe they are regulating a self-sufficient machine, they may focus too narrowly on the vehicle itself: its sensors, software, and safety record. But if these systems are service networks with hidden human inputs and fragile dependencies, the policy questions become more urgent. The real question is whether policymakers are willing to regulate the whole system rather than the branding around it.
Military drones are often discussed as though they operate alone, even when they rely on remote operators, communications links, intelligence inputs and institutional rules of engagement. The machine may be distant, but the system remains deeply human.
The same is true on public roads. Robotaxis may remove the driver from the front seat, but they do not remove people from the system.
For years, the story around robotaxis was simple: cars that drive themselves, less human error, safer streets, cheaper rides.
The reality is more complicated. These systems do not run themselves. Someone answers rider questions. Someone cleans the sensors. Someone sits at a desk ready to step in when the car gets confused. There is maintenance, software updates, and mapping refinements. None of that is glamorous, but it is what keeps the service running.
This does not delegitimize the technology. If anything, it clarifies what makes it work. Redundancy and human backup may be exactly what makes these systems as safe as they are. But the public deserves a more honest accounting of what autonomous really means in practice. At that point, autonomous starts to look less like a technical description and more like a marketing choice that has stuck for too long.
Many local leaders are made to feel they are either pro-robotaxi or anti-innovation. That is a false choice.
The real question is whether officials understand what is being deployed on their streets and are willing to govern it, rather than simply get out of the way. Cities do not need to design the technology. But they do need to coordinate with firms to shape how the service operates in public space.
That means asking questions well beyond vehicle performance. Who provides remote assistance, and from where? What standards govern intervention? What happens when communication fails, or when flooded roads and other edge cases create uncertainty? Where do vehicles go when they are not on active rides? How should residents report unexpected or unsafe behavior? How are vehicles maintained, inspected, cleaned, and recalibrated? How do emergency responders interact with the vehicle and its remote support? How quickly can local officials obtain meaningful records after an incident?
California’s new regulations may begin to point the way, but cities and states cannot answer these questions on their own. They will need shared frameworks, coordination with technology providers and other stakeholders, and a broader view of what these systems involve. These issues are central to public safety and public trust and are too complex for individual localities to manage alone.
I remain skeptical that robotaxis will deliver the low-cost rides often promised. The layers of redundancy are expensive. That does not mean the business cannot succeed. It means profitability may be harder than many investors and innovators expect.
When profitability proves difficult, pressure to cut costs follows. Unless governance keeps pace, cost pressure will create incentives to weaken some of the support layers that currently make these systems publicly acceptable. Elected officials, not just corporate leaders, should be debating those tradeoffs.
The same logic extends beyond safety. Will these services lower transportation costs, or simply shift costs into less visible forms of labor and infrastructure? Will they complement public transportation, or erode transit ridership the way ridesharing did in many cities? Will they improve access to underserved communities? Will deadheading increase congestion? Will local communities bear the burdens on public space while companies retain most of the operational visibility?
If policymakers do not ask those questions up front, they will ask them after a crisis, when politics turn reactive, and trust is already eroding.
Senator Markey’s scrutiny of remote assistance and offshore support has helped surface what should have been clear all along: this is not just about vehicle safety. It is also about labor, national security, transparency, and control. California’s debates over infractions, remote operators, and emergency response point in the same direction. What is really at stake is how visible and governable the system must be before the public is asked to trust it.
Federal and local governments have different roles, but both must get this right. The federal government should take the lead on vehicle safety, cybersecurity, national security, technical reliability and whether critical remote assistance can be performed offshore. Local governments, by contrast, must manage the street-level realities of deployment: service requirements, curb access, ticketing, taxation, emergency interaction, and the conditions under which these systems enter civic life.
Cities cannot punt this to Washington. They will be left managing it on the ground.
Constructive governance does not mean blocking the technology. It means setting terms that reflect reality.
Leaders should stop treating robotaxis as if they are merely cars with better software. They are service systems that require oversight not only of the product but of the people, processes, and institutions that make it work.
That means more robust public data, not just on crashes but on exposure, interventions, operational limits, failures, and performance over time. It means clearer standards for remote support and emergency interaction. It means understanding where labor sits within the system and what happens when economic pressure makes that labor less visible. It means asking not just whether the vehicle can drive, but whether the larger system can scale without weakening safety, accountability or public confidence.
Better language leads to better questions. Call these systems what they are, highly automated and still human-dependent, and the governance questions become harder to ignore. Get that right, and long-term public trust is more likely to follow.
Robotaxis are likely to become part of the mobility landscape. The jurisdictions best positioned to benefit will not be the ones that echo the industry’s preferred vocabulary. They will be the ones willing to govern the system as it actually exists.
—Guest columnist Bryan Reimer is a research scientist at MIT and co-author of How to Make AI Useful. His work focuses on how artificial intelligence and automation shape real-world systems, and he advises industry and policymakers on their deployment. This piece is co-posted by Reimer on LinkedIn.
