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If self-driving cars 1. don't read texts whilst driving, 2. don't drink alcohol, 3. stick to the speed limit, 4. keep a 3-4s distance to the car in front, 5. do

by icc97 9y ago

If self-driving cars 1. don't read texts whilst driving, 2. don't drink alcohol, 3. stick to the speed limit, 4. keep a 3-4s distance to the car in front, 5. don't drive whilst tired 6. don't jump stop signs / red lights it will solve a majority of crashes and deaths. [0] The solutions to not killing people whilst driving aren't rocket science but too many humans seem to be incapable of respecting the rules. [0]: http://www.slate.com/articles/technology/future_tense/2017/11/the_six_main_causes_of_car_crashes.html http://www.slate.com/articles/technology/future_tense/2017/1...

dmreedy 9y ago
You missed a rather important point 0: If self-driving cars are, at their best, roughly as capable as a human driver. This is a big 'if'. The solution to not killing people is a kind of rocket science. In fact, it's probably harder than rocket science[0]. It's predicated on a lot of things that are very, very, very hard. The fact is that humans, who are already pretty capable of most of these very very hard things, often choose to reduce their own capabilities. If the best self-driving tech is no better than a drunk human, however, then we haven't gained much. --- [0] though perhaps not harder than brain surgery.
- icc97 9y ago
  I really don't think it's a big 'if'. As long as there is human level performance data, neural networks can be trained to match that level of performance. So it's a matter of time. It is indeed very, very hard, but also solvable.
  - dmreedy 9y ago
    I agree that it's solvable. However, the process your describing, of collecting human-level performance data, requires the ability to gather all of the data relevant to the act of driving in a manner consumable by the algorithm in question. This is the simulation problem, and it's very, very, very hard (it's why genetic algorithms have traditionally not gotten much further than toy examples, in spite of being a cool idea). Perhaps it is the case that it is very important to have an accurate model of the intentions of other agents (e.g., pedestrians) in order to take preventative action rather than pure reaction. Perhaps it is very important to have a model of what time of day it is, or the neighborhood you're driving in. The likelihood that it is going to rain some time in the next hour. Whether the stock market closed up or down that day. It also assumes that neural networks (or the more traditional systems used elsewhere) are sufficiently complex to model these behaviors accurately. Which we do not yet have an answer to yet. So, when I say, 'a big if', I mean for the foreseeable future, barring some massive technological/biological breakthrough. That could be a very long time.
- clon 9y ago
  For those who do not get the reference: https://www.youtube.com/watch?v=THNPmhBl-8I https://www.youtube.com/watch?v=THNPmhBl-8I
mejari 9y ago
But it doesn't work like that. You can't just say "If they don't do X Y or Z", because while they may not do X Y or Z, that doesn't mean they won't do A B or C that are equally bad or worse. Human and self-driving are two completely separate categories, you can't just assume that things one does well the other also does well, and so just subtract the negatives. You could easily flip your comment to go the other way: "If human drivers don't mistake trucks for clouds or take sharp 90o turns for no reasons then they're safer". I do think that self-driving cars will be safer, but it's upon it's proponents to prove that.
- icc97 9y ago
  As the sibling comment says, it does depend on self-driving cars matching human level performance. But with all AI/Neural Networks it is very possible to match human performance because most of the time you can throw more human-level performance data at it. Each of the crashes that self-driving cars can be fixed and prevented from happening again. The list I gave are human flaws that will almost certainly never be fixed. I further agree with you it's up to the proponents to prove that. It's a good thing to force a really high bar for self-driving cars. Then assuming the technology is maintained once AI passes the bar it should only ever get better.
  - pmoriarty 9y ago
    "Each of the crashes that self-driving cars can be fixed and prevented from happening again." If those situations recur exactly as they happened the first time, sure they can be prevented from happening again. That is, if a car approaches the exact same intersection as the exact same time of day, and a pedestrian that looks exactly like the pedestrian in this accident crosses the street in exactly the same way, with exactly the same other variables (like all the other pedestrians and cars around there that the sensors can see), the data could be enough the same that the algorithm will detect it at close enough to the original situation to avoid the accident this time. But it's not at all clear how well their improvements will generalize to other situations which humans would consider to be "the same" (ie. when any pedestrian in any intersection crosses any street).
  - 9y ago

by icc97 9y ago

dmreedy 9y ago

You missed a rather important point 0: If self-driving cars are, at their best, roughly as capable as a human driver. This is a big 'if'. The solution to not killing people is a kind of rocket science. In fact, it's probably harder than rocket science[0]. It's predicated on a lot of things that are very, very, very hard. The fact is that humans, who are already pretty capable of most of these very very hard things, often choose to reduce their own capabilities. If the best self-driving tech is no better than a drunk human, however, then we haven't gained much. --- [0] though perhaps not harder than brain surgery.

icc97 9y ago
I really don't think it's a big 'if'. As long as there is human level performance data, neural networks can be trained to match that level of performance. So it's a matter of time. It is indeed very, very hard, but also solvable.
- dmreedy 9y ago
  I agree that it's solvable. However, the process your describing, of collecting human-level performance data, requires the ability to gather all of the data relevant to the act of driving in a manner consumable by the algorithm in question. This is the simulation problem, and it's very, very, very hard (it's why genetic algorithms have traditionally not gotten much further than toy examples, in spite of being a cool idea). Perhaps it is the case that it is very important to have an accurate model of the intentions of other agents (e.g., pedestrians) in order to take preventative action rather than pure reaction. Perhaps it is very important to have a model of what time of day it is, or the neighborhood you're driving in. The likelihood that it is going to rain some time in the next hour. Whether the stock market closed up or down that day. It also assumes that neural networks (or the more traditional systems used elsewhere) are sufficiently complex to model these behaviors accurately. Which we do not yet have an answer to yet. So, when I say, 'a big if', I mean for the foreseeable future, barring some massive technological/biological breakthrough. That could be a very long time.
clon 9y ago
For those who do not get the reference: https://www.youtube.com/watch?v=THNPmhBl-8I https://www.youtube.com/watch?v=THNPmhBl-8I

mejari 9y ago

But it doesn't work like that. You can't just say "If they don't do X Y or Z", because while they may not do X Y or Z, that doesn't mean they won't do A B or C that are equally bad or worse. Human and self-driving are two completely separate categories, you can't just assume that things one does well the other also does well, and so just subtract the negatives. You could easily flip your comment to go the other way: "If human drivers don't mistake trucks for clouds or take sharp 90o turns for no reasons then they're safer". I do think that self-driving cars will be safer, but it's upon it's proponents to prove that.

icc97 9y ago
As the sibling comment says, it does depend on self-driving cars matching human level performance. But with all AI/Neural Networks it is very possible to match human performance because most of the time you can throw more human-level performance data at it. Each of the crashes that self-driving cars can be fixed and prevented from happening again. The list I gave are human flaws that will almost certainly never be fixed. I further agree with you it's up to the proponents to prove that. It's a good thing to force a really high bar for self-driving cars. Then assuming the technology is maintained once AI passes the bar it should only ever get better.
- pmoriarty 9y ago
  "Each of the crashes that self-driving cars can be fixed and prevented from happening again." If those situations recur exactly as they happened the first time, sure they can be prevented from happening again. That is, if a car approaches the exact same intersection as the exact same time of day, and a pedestrian that looks exactly like the pedestrian in this accident crosses the street in exactly the same way, with exactly the same other variables (like all the other pedestrians and cars around there that the sensors can see), the data could be enough the same that the algorithm will detect it at close enough to the original situation to avoid the accident this time. But it's not at all clear how well their improvements will generalize to other situations which humans would consider to be "the same" (ie. when any pedestrian in any intersection crosses any street).
- 9y ago