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Machines are much better than humans at detecting pedestrians, but only in situations they are specifically designed or trained for. If a machine finds itself i

Machines are much better than humans at detecting pedestrians, but only in situations they are specifically designed or trained for. If a machine finds itself in an unfamiliar or unknown settings (or if its sensors fail in a way not accounted for in the design), it will fail catastrophically. A human will not. Hell, machines tend to fail even if the setting varies slightly from what they are designed for; just see the numerous ways self-driven machines failed recently for examples. Machines must gain sensory and cognitive capabilities that exceed ours and a working comprehension of human values for me to trust them.

euyyn 10y ago
> but only in situations they are specifically designed or trained for Where are you getting this from? An obstacle in the LIDAR is an obstacle, there's no common-sense or training needed for the car to know that. > the numerous ways self-driven machines failed recently I can only think of the Tesla crash, Tesla cars being notorious for trying to work around the need of LIDAR or similar (being deemed too expensive). What are the other, numerous examples? > If a machine finds itself in an unfamiliar or unknown settings (or if its sensors fail in a way not accounted for in the design), it will fail catastrophically. A human will not. Fail catastrophically how? Worst-case scenario for a well-designed car in a situation it can't understand is to park itself and refuse to go on unassisted. There's no neeed for general AI to implement such a behavior.
- goodplay 10y ago
  >An obstacle in the LIDAR is an obstacle, there's no common-sense or training needed for the car to know that. >Worst-case scenario for a well-designed car in a situation it can't understand is to park itself and refuse to go on unassisted. All these are false positives. What I object to are the costs of false negatives; A situation where the car mis-recognizes an abnormal situation as normal, and then proceeds to act on it's failed understanding. The Tesla is a good example of this; the car failed to recognize the obstacle in front of it and acted accordingly (namely, crashing full speed into the object). Regardless of the underlying reason, a machine did not recognize it was in an unknown setting, and thus failed to react correctly. A human, on the other hand, notices, and will generally use what capabilities they possess to at least attempt to handle the situation safely. I do acknowledge that self-driving cars will likely be statistically safer, but until these cars completely exceed the all the capabilities of human drivers, I refuse to trust them. Regardless of statistics.
  - mixedCase 10y ago
    >The Tesla is a good example of this A car without LIDAR, only relying on camera. >A human, on the other hand, notices The camera didn't even doubt that there wasn't an obstacle in its path due to how it camouflaged against the background. I doubt the human would've seen it. And you're speaking of a prototype hacked on a car barely prepared for self-driving situations (again, no LIDAR and early iteration) and being used improperly. You're not making a good argument here.
  - euyyn 10y ago
    So your numerous examples are the one example of a car crash for not using a LIDAR?

euyyn 10y ago

> but only in situations they are specifically designed or trained for Where are you getting this from? An obstacle in the LIDAR is an obstacle, there's no common-sense or training needed for the car to know that. > the numerous ways self-driven machines failed recently I can only think of the Tesla crash, Tesla cars being notorious for trying to work around the need of LIDAR or similar (being deemed too expensive). What are the other, numerous examples? > If a machine finds itself in an unfamiliar or unknown settings (or if its sensors fail in a way not accounted for in the design), it will fail catastrophically. A human will not. Fail catastrophically how? Worst-case scenario for a well-designed car in a situation it can't understand is to park itself and refuse to go on unassisted. There's no neeed for general AI to implement such a behavior.

goodplay 10y ago
>An obstacle in the LIDAR is an obstacle, there's no common-sense or training needed for the car to know that. >Worst-case scenario for a well-designed car in a situation it can't understand is to park itself and refuse to go on unassisted. All these are false positives. What I object to are the costs of false negatives; A situation where the car mis-recognizes an abnormal situation as normal, and then proceeds to act on it's failed understanding. The Tesla is a good example of this; the car failed to recognize the obstacle in front of it and acted accordingly (namely, crashing full speed into the object). Regardless of the underlying reason, a machine did not recognize it was in an unknown setting, and thus failed to react correctly. A human, on the other hand, notices, and will generally use what capabilities they possess to at least attempt to handle the situation safely. I do acknowledge that self-driving cars will likely be statistically safer, but until these cars completely exceed the all the capabilities of human drivers, I refuse to trust them. Regardless of statistics.
- mixedCase 10y ago
  >The Tesla is a good example of this A car without LIDAR, only relying on camera. >A human, on the other hand, notices The camera didn't even doubt that there wasn't an obstacle in its path due to how it camouflaged against the background. I doubt the human would've seen it. And you're speaking of a prototype hacked on a car barely prepared for self-driving situations (again, no LIDAR and early iteration) and being used improperly. You're not making a good argument here.
- euyyn 10y ago
  So your numerous examples are the one example of a car crash for not using a LIDAR?