Yes, after saying it was about what they need “to do not to cause accidents” and that “any accidents which could occur will be attributable to other cars actions,” which I then added caveats to regarding pedestrians, I said “will only have accidents” when I should have said “will only cause accidents.” I have fixed that with another edit. But I think you’re confused about what I’m trying to show .
Principally, I think you are wrong about what needs to be shown here for safety in the sense I outlined, or are trying to say that the sense I outlined doesn’t lead to something I don’t claim. If what is needed in order for a system to be safe is that no damage will be caused in situations which involve the system, you’re heading in the direction of a claim that the only safe AI is a universal dictator that has sufficient power to control all outcomes. My claim, on the other hand, is that in sociotechnological systems, the way that safety is achieved is by creating guarantees that each actor—human or AI—behaves according to rules that minimizes foreseeable dangers. That would include safeguards for stupid, malicious, or dangerous human actions, much like human systems have laws about dangerous actions. However, in a domain like driving, in the same way that it’s impossible for human drivers to both get where they are going, and never hit pedestrians who act erratically and jump out from behind obstacles into the road with an oncoming car, a safe autonomous vehicle wouldn’t be expected to solve every possible case of human misbehavior—just to drive responsibly.
More specifically, you make the claim that “as far as I can tell it would totally be compatible with a car driving extremely recklessly in a pedestrian environment due to making assumptions about pedestrian behavior that are not accurate.” The paper, on the other hand, says “For example, in a typical residential street, a pedestrian has the priority over the vehicles, and it follows that vehicles must yield and be cautious with respect to pedestrians,” and formalizes this with statements like “a vehicle must be in a kinematic state such that if it will apply a proper response (acceleration for ρ seconds and when braking) it will remain outside of a ball of radius 50cm around the pedestrian.”
I also think that it formalizes reasonable behavior for pedestrians, but I agree that it won’t cover every case—pedestrians oblivious to cars that are driving in ways that are otherwise safe, who rapidly change their path to jump in front of cars, are sometimes able to be hit by those cars—but I think fault is pretty clear here. (And the paper is clear that even in those cases, the car would need to both drive safely in residential areas, and attempt to brake or avoid the pedestrian in order to avoid crashes even in cases with irresponsible and erratic humans!)
But again, as I said initially, this isn’t solving the general case of AI safety, it’s solving a much narrower problem. And if you wanted to make the case that this isn’t enough for similar scenarios that we care about, I will strongly agree that for more capable systems, the set of situations it would need to avoid are correspondingly larger, and the set of necessary guarantees are far stronger. But as I said at the beginning, I’m not making that argument—just the much simpler one that proveability can work in physical systems, and can be applied in sociotechnological systems in ways that make sense.
The crux of these types of arguments seems to be conflating the provable safety of an agent in a system with the expectation of absolute safety. In my experience, this is the norm, not the exception, and needs to be explicitly addressed.
In agreement with what you posted above, I think it is formally trivial to construct a scenario in which a pedestrian jumps in front of a car, making it provably impossible for a vehicle to stop in time to avoid a collision using high school physics.
Likewise, I have the intuition that AI safety, in general, should have various “no-go theorems” about unprovability outside a reasonable problem scope or that finding such proofs would be np-hard or worse. If you know of any specific results( outside of general computability theory) , could you please share them? It would be nice if the community could avoid falling into the trap of trying to prove too much.
(Sorry if this isn’t the correct location for this post.)
On the absolute safety, I very much like the way you put it, and will likely use that framing in the future, so thanks!
On impossibility results, there are some, andI definitely think that this is a good question, but also agree this isn’t quite the right place to ask. I’d suggest talking to some of the agents foundations people for suggestions
Yes, after saying it was about what they need “to do not to cause accidents” and that “any accidents which could occur will be attributable to other cars actions,” which I then added caveats to regarding pedestrians, I said “will only have accidents” when I should have said “will only cause accidents.” I have fixed that with another edit. But I think you’re confused about what I’m trying to show .
Principally, I think you are wrong about what needs to be shown here for safety in the sense I outlined, or are trying to say that the sense I outlined doesn’t lead to something I don’t claim. If what is needed in order for a system to be safe is that no damage will be caused in situations which involve the system, you’re heading in the direction of a claim that the only safe AI is a universal dictator that has sufficient power to control all outcomes. My claim, on the other hand, is that in sociotechnological systems, the way that safety is achieved is by creating guarantees that each actor—human or AI—behaves according to rules that minimizes foreseeable dangers. That would include safeguards for stupid, malicious, or dangerous human actions, much like human systems have laws about dangerous actions. However, in a domain like driving, in the same way that it’s impossible for human drivers to both get where they are going, and never hit pedestrians who act erratically and jump out from behind obstacles into the road with an oncoming car, a safe autonomous vehicle wouldn’t be expected to solve every possible case of human misbehavior—just to drive responsibly.
More specifically, you make the claim that “as far as I can tell it would totally be compatible with a car driving extremely recklessly in a pedestrian environment due to making assumptions about pedestrian behavior that are not accurate.” The paper, on the other hand, says “For example, in a typical residential street, a pedestrian has the priority over the vehicles, and it follows that vehicles must yield and be cautious with respect to pedestrians,” and formalizes this with statements like “a vehicle must be in a kinematic state such that if it will apply a proper response (acceleration for ρ seconds and when braking) it will remain outside of a ball of radius 50cm around the pedestrian.”
I also think that it formalizes reasonable behavior for pedestrians, but I agree that it won’t cover every case—pedestrians oblivious to cars that are driving in ways that are otherwise safe, who rapidly change their path to jump in front of cars, are sometimes able to be hit by those cars—but I think fault is pretty clear here. (And the paper is clear that even in those cases, the car would need to both drive safely in residential areas, and attempt to brake or avoid the pedestrian in order to avoid crashes even in cases with irresponsible and erratic humans!)
But again, as I said initially, this isn’t solving the general case of AI safety, it’s solving a much narrower problem. And if you wanted to make the case that this isn’t enough for similar scenarios that we care about, I will strongly agree that for more capable systems, the set of situations it would need to avoid are correspondingly larger, and the set of necessary guarantees are far stronger. But as I said at the beginning, I’m not making that argument—just the much simpler one that proveability can work in physical systems, and can be applied in sociotechnological systems in ways that make sense.
The crux of these types of arguments seems to be conflating the provable safety of an agent in a system with the expectation of absolute safety. In my experience, this is the norm, not the exception, and needs to be explicitly addressed.
In agreement with what you posted above, I think it is formally trivial to construct a scenario in which a pedestrian jumps in front of a car, making it provably impossible for a vehicle to stop in time to avoid a collision using high school physics.
Likewise, I have the intuition that AI safety, in general, should have various “no-go theorems” about unprovability outside a reasonable problem scope or that finding such proofs would be np-hard or worse. If you know of any specific results( outside of general computability theory) , could you please share them? It would be nice if the community could avoid falling into the trap of trying to prove too much.
(Sorry if this isn’t the correct location for this post.)
On the absolute safety, I very much like the way you put it, and will likely use that framing in the future, so thanks!
On impossibility results, there are some, andI definitely think that this is a good question, but also agree this isn’t quite the right place to ask. I’d suggest talking to some of the agents foundations people for suggestions