Comment by brainwad
12 hours ago
This is like saying cars don't kill people, because if nobody drives them faster than 3mph there's no problem. The _whole_ promise of cars is that they can go fast, just like the whole promise of AI is offloading thinking to a computer. If AIs are unsafe without close human supervision and checking every interaction with the real world, they are unsafe full stop.
The analogy would be more fitting if you had said "cars don't kill people if every drivers has proven skills, never drives impaired, keeps the speed in line with weather and road conditions and stays on actual roadways". You know, like everyone should, regardless of whether they're driving a high performance sports car.
To keep with the analogy: cars have seatbelts, airbags, ABS, ESP, lights, horns, crumple zones, emergency braking systems, roads have speed limits, there are traffic stops, insurance, regular inspections (not in all countries), etc. etc.
So what's unsafe here? The car or roads without speed limits, complete lack of safety measures (both active and passive), absence of any supervision and no insurance? That's the problem. It's not the models themselves - they can spit out tokens by the billions, there's no risk there.
You wouldn't give full access to your phone, your computers, your house keys and your credit cards to any stranger on the street now, would you? How is it then, that people act all surprised when a non-deterministic machine that's optimised to achieve goals while taking all the shortcuts it can, suddenly uses the tools handed to it in unexpected ways? That's a failure on the operator's side, not an inherent danger within of the model.
The cars are still unsafe at speed. All those mitigations reduce the risks but do not eliminate the inherent danger. Sandboxing agentic LLMs is similar, there is no way to mitigate the inherent safety problem entirely while preserving the power of the thing (an LLM without a harness is safe in the way an engine without a chassis is - safe and useless).
But safety is just one thing people optimise for; if it's convenient enough people will accept imperfect safety (as with cars). It's unrealistic to just heap blame on end-users who use mostly very safe tools in the common way, even though in aggregate they are meaningfully dangerous. They don't think they are strapping a weed whacker to a dog; they think they are driving a car.
And therein lies the problem. I listed all the things that differentiate cars from current AI models: cars require a license to drive, they are subject to heavy regulation (insurance, registration, inspections, etc.), there's road signs, police, incident statistics, recalls in case of defects etc. etc. NONE of that is currently in place for AI models and the systems surrounding them. So the analogy is flawed on every level. I don't buy the convenience is just too appealing narrative when your own analogy clearly demonstrates what is required in order to roll out dangerous technology to the masses, while NONE of that is in place in the context of AI models.
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What did your momma tell you about running into the street?
Cars are inherently dangerous. They’ll still be dangerous when computers are driving them all.
I'm sick of this strawman nonsense. You are attacking a false analogy. Discuss the actual meat of the argument instead.
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