> In a new class of attack on AI systems, troublemakers can carry out these environmental indirect prompt injection attacks to hijack decision-making processes.
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.
This is a legitimate movement in my eyes. I don’t participate, but I see it as valid. This is reminiscent of the Luddite movement - a badly misunderstood movement of folks who were trying to secure labor rights guarantees in the face of automation and new tools threatening to kill large swaths of the workforce.
The Luddites were employed by textile manufacturers and destroyed machines to get better bargaining power in labor negotiations. They weren't indiscriminately targeting automation, they targeted machines that directly affected their work.
Criminality is an arbitrary benchmark here, cutting people off can be illegal due to the risks involved.
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.
Inflicting damage is usually justified by averting larger damage. Very roughly, breaking a $200 car window is justified in order to save a $100k house from burning down. Stealing someone's car is justified when you need a car to urgently drive someone bleeding to a hospital to save their life (and then you don't claim the car is yours, of course).
I don't think Luddites had an easy justification like this.
I'm pretty sure the Luddites judged the threat the machines posed to their livelihood to be a greater damage than their employer's loss of their machines. So for them, it was an easy justification. The idea that dollar value encapsulates the only correct way to value things in the world is a pretty scary viewpoint (as your reference to the value of saving a life illustrates).
It’s an interesting question because the benefits of automation aren’t necessarily shared early on. If you can profitably sell a shirt for 10$ while everyone else needs to sell for 20$ there’s no reason to actually charge 10$ you might as well charge 19.95$ and sell just as many shirts for way more money.
So if society is actually saving 5c/shirt while “losing” 9$ in labor per shirt. 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 optimization is 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. And IMO that’s what actually decides the issue for most people.
It's easy to see the word Waymo and think clanker autonomous car, but there are very often people inside that car - they are a rideshare service after all. Calling endangering other humans "legitimate" because you dislike the taxi company is not a good look.
Your general luddite argument - preserve way-of-life of the small group at the expense of a larger group.
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 are sitting in a waymo vehicle, and somebody cuts you off - do you even notice? They don't have them round here but my idea is that the vehicle itself is doing all the work, you can just continue reading your book, chat or get on something else with little awareness of the actual journey. Does the waymo curse and shake its little fist to alert you it was cut off?
People are free to reject technology as they please.
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?
Please tell me that he does realize that when something bad happens, that Waymo car has all the footage that it is his fault?
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.
These drones have cameras, it's a matter of time before they "share" footage... basically becoming robo-cops, traffic edition - this might be of interest to your coworker.
Most roads already have plenty of cameras registering passing cars, so if you want to travel highly privately, take a bike, which does not require number plates. Also don't forget to wrap your phone in foil (yes, even when turned off), and regularly change your shirt color, or something.
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.
On a related note, when the sales and popularity of the automobile really started to take off, some farmers and rural residents would deliberately block roads with wagons and refused to yield right-of-way.
The study assumes that the car or drone is being guided by a LLM. Is this a correct assumption? I would thought that they use custom AI for intelligence.
Its an incorrect assumption, the inference speed and particularly the inference speed of the on-device LLMs with which AVs would need to be using is not compatible with the structural requirements of driving.
I think the assumption is valid. Most of the reasoning components of the next gen (and some current gen) robotics will use VLMs to some extent. Deciding if a temporary construction sign is valid seems to fall under this use case.
But unless you are using a single, end-to-end model for the entire driving stack, that "proceed" command will never influence accelerator pedal.
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.
No; AV uses "classical" AI and computer vision. I remember reading somewhere that Tesla FSD uses a small LLM for understanding road signs. Not sure if true, though.
To the best of my knowledge every major autonomous vehicle and robotics company is integrating these LVLMs into their systems in some form or another, and an LVLM is probably what you're interacting with these days rather than an LLM. If it can generate images or read images, it is an LVLM.
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.
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.
Many large companies have research departments that do experimental work that'll never get to the product. This raises prestige, increases visibility and helps hire smart people.
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)
One year in my city they were installing 4-way stop signs everywhere based on some combination of "best practices" and "screeching Karens". Even the residents don't like them in a lot of places so over time people just turn the posts in the ground or remove them.
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".
4-way stops are terrible in general. They train people to think "I stopped, now I can go", which is dangerous when someone confuses a normal stop for a 4-way stop. It also wastes a good bit of energy.
That isn’t the rule either, I guess parent made their point. The first person who stops goes next, right away only matters if their is ambiguity in who stopped first.
I’ve never seen a four way stop in a region that had traffic on the right can always go regardless of stop time. But I’ve only seen four way stops in a few countries.
Roundabouts are great (we just had two complex intersections with traffic lights replaced by roundabouts and the traffic flow is much better), but they take significantly more space than a 4-way stop.
They make people on the main road slow down, which is a feature, not a bug. What you mean is that they're the most efficient at what they do when the traffic is comparable. They only reduce accident at the expense of a slightly lowered throughput if the traffic is highly disparate.
> Right but it's not like a 4 way stop is going to perform better.
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.
So use a mini roundabout. They are common in the UK. It's just a painted circle with a slight hump, in the middle of a four-way junction. Vehicles can drive over it (and larger ones have to) but it indicates to everyone that they have to give way to traffic from the right and don't have to stop otherwise. They typically aren't big enough for multiple vehicles to be turning a corner at the same time. They fit anywhere.
Even rural Georgia has double roundabouts now. Not sure why people on the internet can't contain their glee at stating the US is "allergic" to them when the frequency of roundabouts has grown significantly in recent decades.
Because retrofitting them properly requires emminent domain. The ones they shoehorn onto former four way stops are so useless. They are so tight you still have to face a stop sign vs being able to just seamlessly zipper merge in a proper larger circumference roundabout. When they have room to build out a proper roundabout they are usually OK but that is hard to do outside say new suburban construction due to lack of available land on the right of way.
No! No one in their right mind would even consider using them for guidance and if they are used for OCR (not too my knowledge but could make sense in certain scenarios) then their output would be treated the way you'd treat any untrusted string.
> 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.
You were confidently wrong for judging them to be confidently wrong
> 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.
I should have taken more care to link a article, but I was trying you link something more clear.
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.
They also go on to explain model distillation. Read the whole thing, it's not long
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
O brave new world of endless manipulation opportunities! Once we’ve trained a generation of humans to always do what their “AI” tells them, there will be no more disobedience.
To me this is just one more pillar underlying my assumption that self driving cars that can be left alone on same roads as humans is a pipe dream.
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
Given Waymo's don't actually connect LLMs to wheels, they are pretty safe.
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.
How does Waymo fix it? They have to be responsive to some signs (official, legitimate ones such as "Lane closed ahead, merge right") so there will always be some injection pathway.
They've mapped the roads and they don't need to drive into a ditch just because there's a new sign. It probably wouldn't be all that hard to come up with criteria for saying "this new sign is suspicious" and flag it for human review. Also, Waymo cars drive pretty conservatively, and can decide to be even more cautious when something's confusing.
Someone could probably do a DOS attack on the human monitors, though, sort of like what happened with that power outage in San Francisco.
Regarding some other comments, VLMs are a component of VLAs. So even if this won’t directly impact this generation of vehicles, it almost certainly will for robotics without sufficient mitigations.
The experiment in the article goes further than this.
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.
The Register stooping this low is the only surprise here. I'm quite critical of Teslas approach to level 3+ autonomy but even I wouldn't dare suggest that there vision based approach amounted to bolting GPT-4o or some other VLLM to their cars to orient them in space and make navigation decisions. Fake News like this makes interacting with people who have no domain knowledge and consider The Register, UCLA and Johns Hopkins to be reputable institutions and credible sources more stressful to me as I'll be put into a position to tell people that they have been misled or go along with their delusions...
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.
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