Training in supervision of autonomous vehicles should always be required for humans to do the supervision.

No, it is not currently true as a legal requirement. There is currently no standard state DMV license class (such as a "Class AV") dedicated to autonomous vehicle supervision or safety monitoring. Here is how the regulatory and licensing landscape currently works: 1. Current Legal Requirements Standard Driver's License: Human safety drivers, test operators, and supervisors operating autonomous vehicles (AVs) on public roads are generally required to hold a standard driver's license for the vehicle's size—typically a Class C license for passenger cars or a Class A/B Commercial Driver's License (CDL) for autonomous trucks. State Testing Programs: Certain states with heavy AV development (such as California and Arizona) require companies to ensure their test drivers meet strict criteria (e.g., specific age limits, clean driving records, and completion of company training programs), but this is tracked through employer certification and manufacturer permits rather than a distinct class printed on a driver's license. Fully Driverless AVs: For fully autonomous (Level 4/5) commercial vehicles operating without any human inside, states require company-level operating permits and compliance with safety frameworks, rather than individual driver licensing. 2. The Policy & Academic Concept While a dedicated "Class AV" license does not exist in law, it is a recognized policy proposal frequently discussed by transportation safety experts, legislators, and tech researchers. Proponents argue that as semi-autonomous (Level 2/3) and fully autonomous systems proliferate, a specialized license class or endorsement could ensure drivers understand: System limitations and handoff protocols (when and how human intervention is required). Edge-case supervision and emergency override techniques. Legal liability and distraction laws specific to automated driving. PER GEMINI

But what about robot taxis

I agree with the accusation. But the questions is whether the owner of the vehicle or the manufacturer is liable for the license.

Any machine can fail for any number of reasons, and humans must take responsibility for any damage caused by machines they own and/or operate, so they must have fundamental understanding of their machine and the know-how to step in and avert accidents.

Training in supervision of autonomous vehicles should always be required for humans to do the supervision.

Autonomous vehicles introduce a genuinely different relationship between the human occupant and the vehicle. A specialised competency requirement could make sense, particularly where the human is expected to supervise or intervene.

Whether there "should" be a dedicated license class for Autonomous Vehicle (AV) supervision isn't a factual matter with a simple "true" or "false" answer—it is an ongoing debate involving technology, safety ethics, and state regulation. Calling it the "whole truth" implies it is an absolute necessity or an accepted fact, when in reality, there are compelling arguments on both sides.

What is the license actually for? To know how to drive?

Need more info before from Bob.

A licence addresses the human’s competence, but it doesn’t solve vehicle safety, software failures, cybersecurity, manufacturer responsibility, infrastructure problems or liability.

o say it is "nothing but the truth" would imply that this is an unassailable, objective fact carved in stone—and it simply isn't. Whether there should be a dedicated driver's license class for Autonomous Vehicle (AV) supervision is not a statement of fact; it is a value judgment and a regulatory debate. In legal terms, it's a normative claim (an argument about how the world ought to be), not an empirical fact (a statement about how the world actually is). If we put this claim "on trial," here is why calling it "nothing but the truth" falls short: 1. "Truth" Requires Consensus—And the Experts Are Divided For a policy proposal to be considered an undeniable truth, there would need to be overwhelming agreement that it is the single best solution. In reality, the transportation and tech sectors are deeply split: The "Yes" Position: Proponents argue that supervising an AI system requires a totally different skill set than driving a traditional car—specifically, managing automation fatigue, understanding system boundaries (Operational Design Domains), and executing emergency handoffs. To them, a new license class is common sense safety. The "No" Position: Opponents argue that creating a DMV-level "Class AV" license is a clumsy solution. Software updates change AV behavior faster than state governments can update driving tests. Furthermore, for commercial testing, strict internal employer training is far more effective than a generic state exam, while for consumer cars, the goal is to reduce human burden, not add new bureaucratic layers.

In the fsd sutuation fewer people will learn to drive. And therefore have no skills to take over if and when FSD fails. If everyone still has to have a driving license, then something about the FSD scheme seems superfluous.

The plaintiff risks implying that introducing a new licence is inherently the solution. It might help, but there is no guarantee that another licence will actually make autonomous vehicles safer.

There is no deceit.

There is no deceit.

No deceit intended.

The deceit is that the lie is misleading.

1. The Category Error (A "Fiat Lie") The Trick: Presenting an opinion or policy proposal as if it were an established, objective fact. Why it Deceives: The word "should" inherently expresses a preference, value judgment, or ideal state of affairs. Passing off a normative goal (what ought to be) as an undeniable truth (what is) attempts to bypass critical debate. It tricks the listener into accepting a political or regulatory preference as a settled reality. 2. False Dichotomy & Omission of Alternatives The Trick: Implying that a specialized state DMV license class is the only valid or effective way to ensure autonomous vehicle (AV) safety. Why it Deceives: It hides viable, competing safety paradigms, such as: Employer-Level Certification: Rigorous, proprietary internal training by AV operators (like Waymo or Cruise) tailored to specific vehicle software, which is far more detailed than a generic DMV exam. System-Level Software Safety: Engineering the AI to handle its own fail-safes and handoffs, reducing human error altogether rather than shifting the burden back onto a human supervisor. Federal Vehicle Standards: Regulating the hardware/software manufacturers directly at the NHTSA level rather than creating individual state driver licensing schemes. 3. The Illusion of Regulatory Control The Trick: Suggesting that placing a "Class AV" stamp on a driver's license actually solves the hazard of human inattention during automated driving. Why it Deceives: Decades of human-factors engineering show that humans are inherently poor at passively monitoring automated systems for long periods without losing focus (a concept known as vigilance decrement). Promising that a state driving test fixes this fundamental psychological limitation creates a false sense of security—pretending a bureaucratic solution solves a complex human-machine interaction problem.

The deceit is that the lie is factually true.

It’s not clear why a driver class still has to be licensed for FSD cars. If something goes wrong then even that eventuality can be managed by the software.

There is no deceit.

This is partially true.

I don't agree with one part here: that people who do not know how to drive could get a license that only enables them to operate an AI vehicle. How do they take over in an emergency if they don't know how to drive?

There is no deceit.

The potential deceit is shifting the responsibility for autonomous technology onto the human supervisor.

If a vehicle is genuinely autonomous, we need to be careful about making the human legally responsible for decisions they didn’t actually make and systems they cannot directly control.

The truth is intended.

Truth intended. Autonomous vehicles need supervision by a human.

When evaluating whether truth or deceit is intended behind the claim "There should be a Driver's License Class for Autonomous Vehicle Supervision," the answer depends on who is making the claim and what operational or political outcome they are trying to achieve. Under strict frameworks of truth-testing (like those modeled in digital truth courts), the statement carries mixed intent—it is rarely a malicious lie, but it frequently functions as a strategic deception. Dimension Assessment Is it a Direct Lie? No. It is a normative statement (an opinion about what should be), so it cannot be factually false in a literal sense. Is Deceit Present? Yes. Deceit is present whenever the claim is used to hide corporate liability, present a bureaucratic test as a complete safety solution, or disguise a complex policy debate as settled fact. Primary Intent: Usually well-meaning in policy discussions, but deceptive when asserted as an absolute truth or sole regulatory solution.

FSD is not like other machinery. Constant monitoring is not required.

The truth is intended.

The truth is intended.

The truth is intended.

I don’t think the plaintiff is necessarily trying to deceive. The proposal comes from a legitimate concern about safety. But the argument needs to address whether the licence would genuinely improve safety or simply create another layer of responsibility.

The motivation is to be informative

The motivation is to be informative

When analyzing the motivation behind asserting either the TRUTH or the LIE regarding a specialized "Class AV" license, we move into the realm of incentives—who gains, who loses, and what drives the narrative.

Summary of Core Motivations Objective Primary Motivating Force Operational Driver Speaking the TRUTH Scientific & Legal Accuracy A desire to solve human-machine friction through real engineering and precise regulation. Promoting the LIE / DECEIT Liability Protection & Political Cover A desire to shift legal risk onto drivers, calm public fears, and create performative safety structures.

I'm not sure what the motivation is.

The idea that anyone can get in a car and have it take the. Where they want to go without licensing is surely the goal.

The motivation is to be informative

The motivation is to encourage people to get legislation passed requiring people to get a license to operate a self-driving car.

The motivation is to be informative

Public safety and regulatory preparedness

The motivation is understandable: autonomous vehicles are developing faster than traditional driving laws, so governments need a way to regulate human interaction with them.

This is important. The exact form of the test to achieve this driver/supervisor right is to be determined preferably by the National Institute of Standards or the appropriate ISO body in the United Nations The example of such a test given has some serious flaws.

Summary of Social Dynamics Stakeholder Group Perception of the Claim Primary Social Driver General Public High Acceptance ("Truth") Desires familiar, state-enforced safety measures to feel comfortable on public roads. Tech & Auto Industry Low Acceptance ("Deceit") Views paper licenses as ineffective at solving human attention limits and slow to adapt to tech updates. Lawmakers & Regulators Split / Mixed Torn between reassuring anxious voters with new rules and avoiding over-regulation that stalls innovation.

There is confusion in the plaintiff’s ase. He claims AI thinks better than HUmans and yet he demands that HUmans must continue to dominate them with Human control.

The licenses must be designed and issued by independent bodies, not by self-driven car manufacturers, who would make it too easy, and probably encourage the use of these vehicles by children, dementia patients, drunks, etc.

This is important. The exact form of the test to achieve this driver/supervisor right is to be determined preferably by the National Institute of Standards or the appropriate ISO body in the United Nations The example of such a test given has some serious flaws.

People can reasonably accept additional training for a technology that changes the nature of driving. But it becomes socially problematic if ordinary citizens are forced to carry responsibility for failures caused by manufacturers or autonomous systems.

No label needed

Safety first!

SEE SUPPORTING TEXT

Comparative Acceptability Impact Proposed Label Perception by Tech Industry Perception by General Public Primary Psychological Benefit Driver's License Class AV Low (Seen as rigid DMV overreach) Medium (Familiar, but sounds complex) Administrative clarity AV Safety Specialist Certification High (Aligns with existing industry titles) High (Conveys professional expertise) Builds public trust & authority Autonomous Systems Endorsement High (Integrates into existing DMV laws) High (Easy to understand like HazMat/Motorcycle) Regulatory efficiency

This is true, but misleading.

Either driving experience is required to drive a FSD car or it is not. I agree that a simple addendum to a driving license may well be required, as described namely check the state of the sensors, and basic equipment, software check list, charging stops required and so on. This could be done in a short time and maybe in addition to a log book of drives done with FSD.

No label needed

No label needed

No label needed

“Autonomous Vehicle Operator Certification.”

I actually prefer this to “autonomous driver’s licence” because it recognises that the person’s role may no longer be traditional driving.