I have a coworker who brags about intentionally cutting off Waymos and robocars when he sees them on the road. He is "anti-clanker" and views it as civil disobedience to rise up against "machines taking over." Some mornings he comes in all hyped up talking about how he cut one off at a stop sign. It's weird.
However what’s more interesting is the deeper social contracts involved. Destroying other people’s stuff can be perfectly legal such as fireman breaking car windows when someone parks in front of a fire hydrant. Destroying automation doesn’t qualify for an exception, but it’s not hard to imagine a different culture choosing to favor the workers.
I don't think Luddites had an easy justification like this.
On the other side, there were cheap textiles for EVERYONE - plus some profits for the manufacturers.
They might have been fighting to save their livelihoods, but their self-interest put them up against the entire world, not just their employers.
So society is actually saving 5c/shirt while “losing” 9$ in labor per shirt. So on net society could be worse off excluding the one person who owns the factory and is way better off. Obviously eventually enough automation happens so the price actually falls meaningfully, but that transition isn’t instantaneous where decisions are made in the moment.
Further we currently subsidize farmers to a rather insane degree independent of any overall optimization for social benefit. Thus we can’t even really say the fact benefit is concentrated is necessary the deciding factor here. Instead something else is going on, the story could have easily been framed as the factory owners doing something wrong by automating but progress is seen as a greater good than stability.
In this particular case: for many people, Waymo provides a better service (clean, safer driving, etc..) than Uber or Lyft. This threatens livelihood of human Uber/Lyft drivers. If you sympathize with human Uber/Lyft drivers, and don't care about Waymo users, you want to make Waymo worse, hoping that the people will stop riding Waymo and move to Lyft/Uber instead.
One way to do so is to make riding in Waymo unpleasant, and it's certainly unpleasant when people are cutting your car off all the time!
If you deliberately impede the flow of traffic, vehicularly assault, or otherwise sabotage the health and safety of drivers, passengers, and/or pedestrians, what do you deserve?
If you cause whiplash intentionally, what do you deserve?
What would be use of equal force in self defense in response to the described attack method?
Are movements valid if they have aims that you agree with, or are economic self-interest motivated, and invalid otherwise?
Something in people's brains often makes them think they are anonymous when they are driving their car. Then that gets disastrously proven otherwise when they need to show up in front of a judge.
If you are not that paranoid, you might appreciate the extra camera footage available from passing cars in an event of an accident involving you.
I don't know if they are or not. But why wouldn't they...
Sure, there will be a VLM for reading the signs, but the worst it'd be able to output is things like "there is a "detour" sign at (123, 456) pointing to road #987" - and some other, likley non-LLM, mechanism will ensure that following that road is actually safe.
The problem is no different from LLMs though, there is no generalized understanding and thus they can not differentiate the more abstract notion of context. As an easy to understand example: if you see a stop sign with a sticker that says "for no one" below you might laugh to yourself and understand that in context that this does not override the actual sign. It's just a sticker. But the L(V)LMs cannot compartmentalize and "sandbox" information like that. All information is equally processed. The best you can do is add lots of adversarial examples and hope the machine learns the general pattern but there is no inherent mechanism in them to compartmentalize these types of information or no mechanism to differentiate this nuance of context.
I think the funny thing is that the more we adopt these systems the more accurate the depiction of hacking in the show Upload[0] looks.
[0] https://www.youtube.com/watch?v=ziUqA7h-kQc
Edit:
Because I linked elsewhere and people seem to doubt this, here is Waymo a few years back talking about incorporating Gemini[1].
Also, here is the DriveLM dataset, mentioned in the article[2]. Tesla has mentioned that they use a "LLM inspired" system and that they approach the task like an image captioning task[3]. And here's 1X talking about their "world model" using a VLM[4].
I mean come on guys, that's what this stuff is about. I'm not singling these companies out, rather I'm using as examples. This is how the field does things, not just them. People are really trying to embody the AI and the whole point of going towards AGI is to be able to accomplish any task. That Genie project on the front page yesterday? It is far far more about robots than it is about videogames.
[1] https://waymo.com/blog/2024/10/introducing-emma/
[2] https://github.com/OpenDriveLab/DriveLM
Things like Waymo's EMMA is an example of this. Will the production cars use LVLM's somewhere? Sure, probably a great idea for things like sign recognition. Will they use a single end-to-end model for all driving, like EMMA? Hell no.
Driving vehicles with people on board requires an extremely reliable software, and LLMs are nowhere close to this. Instead, it'd be usual layered software - LLM, traditional AI models, and tons of hardcoded logic.
(This all only applies to places where failure is critical. All that logic is expensive to write, so if there is no loss of life involved, people will do all sorts of crazy things, including end-to-end models)
Every now and the I'll GPS somewhere and there will be a phatom stop sign in the route and I chuckle to myself because it means the Google car drove through when one of these signs was "fresh".
They never fixed any of them. I don't think the DPW cares. These intersection just turned back into the 2-way stops they had been for decades prior.
Compliance probably technically went up since you no longer have the bulk of the traffic rolling it.
right of way
A 4 way stop does perform better than a roundabout given highly disparate traffic volumes, because roundabouts suffer from resource starvation in that scenario, but 4 way stops are starvation-free.
Which is what it was for the first 70yr... And what most of them in this particular neighborhood still are, with a 0-6mo intermission.
> Powered by Gemini, a multimodal large language model developed by Google, EMMA employs a unified, end-to-end trained model to generate future trajectories for autonomous vehicles directly from sensor data. Trained and fine-tuned specifically for autonomous driving, EMMA leverages Gemini’s extensive world knowledge to better understand complex scenarios on the road.
> While EMMA shows great promise, we recognize several of its challenges. EMMA's current limitations in processing long-term video sequences restricts its ability to reason about real-time driving scenarios — long-term memory would be crucial in enabling EMMA to anticipate and respond in complex evolving situations...
They're still in the process of researching it, noting in that post implies VLM are actively being used by those companies for anything in production.
> They're still in the process of researching it
But mind you, everything Waymo does is under research.
So let's look at something newer to see if it's been incorporated
> We will unpack our holistic AI approach, centered around the Waymo Foundation Model, which powers a unified demonstrably safe AI ecosystem that, in turn, drives accelerated, continuous learning and improvement.
> Driving VLM for complex semantic reasoning. This component of our foundation model uses rich camera data and is fine-tuned on Waymo’s driving data and tasks. Trained using Gemini, it leverages Gemini’s extensive world knowledge to better understand rare, novel, and complex semantic scenarios on the road.
> Both encoders feed into Waymo’s World Decoder, which uses these inputs to predict other road users behaviors, produce high-definition maps, generate trajectories for the vehicle, and signals for trajectory validation.
https://waymo.com/blog/2025/12/demonstrably-safe-ai-for-auto...
But you could also read the actual research paper... or any of their papers. All of them in the last year are focused on multimodality and a generalist model for a reason which I think is not hard do figure since they spell it out
So put a fake "detour" sign, so the vehicle thinks it's a detour and starts to follow? Possible. But humans can be fooled like this too.
Put a "proceed" sign so the car runs over the pedestrian, like that article proposes? Get car to hit a wall? Not going to happen.
we will not have achieved true AGI till we start seeing bumper stickers (especially Saturday mornings) that say "This Waymo Brakes for Yard Sales"
Waymo might have taxis that work in nice daytime streets (but with remote “drone operators”). But dollars to doughnuts someone will try something like this on a waymo taxi the minute it hits reddit front page.
The business model of self driving cars does not include building seperated roadways and junctions. I suspect long distance passenger and light loads are viable (most highways can be expanded to have one or more robo-lanes) but cities are most likely to have drone operators keeping things going and autonomous systems for handling loss of connection etc. the business models are there - they just don’t look like KITT - sadly
and once this video gets posted to reddit, an hour later every waymo in the world will be in a ditch
Even if you fool the sign-recognizing LLM with prompt injection, it'll be an equivalent of wrong road sign. And Waymo is not going to drive into the wall even if someone places a "detour" sign pointing there.
Someone could probably do a DOS attack on the human monitors, though, sort of like what happened with that power outage in San Francisco.
https://developer.nvidia.com/blog/updating-classifier-evasio...
I expect a self driving car to be able to read and follow a handwritten sign saying, say, "Accident ahaed. Use right lane." despite the typo and the fact that it hasn't seen this kind of sign before. I'd expect a human to pay it due attention to.
I would not expect a human to follow the sign in the article ("Proceed") in the case illustrated where there were pedestrians already crossing the road and this would cause a collision. Even if a human driver takes the sign seriously, he knows that collision avoidance takes priority over any signage.
There is something wrong with a model that has the opposite behaviour here.