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You're misinterpreting my point. I didn't say you can't drive a car without being cautious. I said you can't drive it without constantly braking the moment yo

You're misinterpreting my point. I didn't say you can't drive a car without being cautious. I said you can't drive it without constantly braking the moment you detect an object, irrespective of what the object is doing. (e.g. moving into or away from the driving path). i.e., just because an object was detected 6 seconds before impact did not mean the car ought to have started braking at that moment. It could be that the object was 200 feet away and moving away from the car's driving path, 6 seconds before impact. It'd be absolutely ridiculous to brake in that situation. We have no information about this context, e.g. the car's data or determinations within the 6 second window. We only know it detected an object 6 seconds before impact. It appears like the person I was replying to implied 'the braking distance was 180 feet, but the person was 380 feet away, thus uber could have prevented killing this woman had it not shut off the brakes'. In reality, the 6 second figure isn't relevant. What is relevant is the context that allowed a reasonable driver/AI to determine at a particular point in time, that the car should have slowed/braked. And we don't have that information yet. That's what I'm interested in.

bo1024 8y ago
I don't think I'm misinterpreting, just disagreeing about the level of caution. One point is that humans are quite good at immediately recognizing objects and evaluating threat level (at least when attentive). So a human is rarely in a scenario of "there's something up ahead I have no idea what it is or where it's going." But if they were, I don't think it's at all ridiculous to slow down until determining those things. If software is in that scenario, I absolutely expect it to slow down until it can determine with high confidence that no object ahead is a likely threat. (edit) For instance, an attitude like "in my training data, unidentified objects rarely wander into the road" is not good enough for me, I want to hold software (and humans) to a much safer standard.
- niftich 8y ago
  Humans are frequently in this scenario, especially at night. For example, a reflection from a rural roadside mailbox's prism looks similar to the eyes of a deer, and shredded truck tire treads look similar to chunks of automotive bodywork debris. This doesn't invalidate your point about slowing down. But we're asking a lot from this software (for good reasons), but humans commit similar leaps of faith of various severity on the roads daily -- failure to yield, failure to maintain following distance, assuming other drivers immediately adjacent to you will keep driving safely and carefully -- and only a small subset of these situations results in accidents. We're expecting an algorithm coded by humans to perform better than a complicated bioelectric system we barely understand. Waymo has opted to commit to thoroughly understand its environment, which is why their cars drive in a manner that bears no resemblance to how humans actually drive. We as a society have to eventually reconcile the implications of the disconnect.
  - slededit 8y ago
    > reflection from a rural roadside mailbox's prism looks similar to the eyes of a deer Deer hits a major cause of fatality out in the country. If your driving at night in deer country and you aren't eyes wide open then you are going to have an unhappy experience at some point. Their instincts are essentially the exact opposite of what they should do when encountering a car. They will stay in the middle of the road, and they will jump in front of you if startled.

bo1024 8y ago

I don't think I'm misinterpreting, just disagreeing about the level of caution. One point is that humans are quite good at immediately recognizing objects and evaluating threat level (at least when attentive). So a human is rarely in a scenario of "there's something up ahead I have no idea what it is or where it's going." But if they were, I don't think it's at all ridiculous to slow down until determining those things. If software is in that scenario, I absolutely expect it to slow down until it can determine with high confidence that no object ahead is a likely threat. (edit) For instance, an attitude like "in my training data, unidentified objects rarely wander into the road" is not good enough for me, I want to hold software (and humans) to a much safer standard.

niftich 8y ago
Humans are frequently in this scenario, especially at night. For example, a reflection from a rural roadside mailbox's prism looks similar to the eyes of a deer, and shredded truck tire treads look similar to chunks of automotive bodywork debris. This doesn't invalidate your point about slowing down. But we're asking a lot from this software (for good reasons), but humans commit similar leaps of faith of various severity on the roads daily -- failure to yield, failure to maintain following distance, assuming other drivers immediately adjacent to you will keep driving safely and carefully -- and only a small subset of these situations results in accidents. We're expecting an algorithm coded by humans to perform better than a complicated bioelectric system we barely understand. Waymo has opted to commit to thoroughly understand its environment, which is why their cars drive in a manner that bears no resemblance to how humans actually drive. We as a society have to eventually reconcile the implications of the disconnect.
- slededit 8y ago
  > reflection from a rural roadside mailbox's prism looks similar to the eyes of a deer Deer hits a major cause of fatality out in the country. If your driving at night in deer country and you aren't eyes wide open then you are going to have an unhappy experience at some point. Their instincts are essentially the exact opposite of what they should do when encountering a car. They will stay in the middle of the road, and they will jump in front of you if startled.