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I'm thinking about "trolley problems" for autonomous vehicles...I'm thinking that a practical system would only degenerate to the classical trolley problem in a very few cases, but for the most part, you'd just design the system to maximize survivability of crashes for all observable or inferred humans and then, fixing that solution, to minimize property damage. Early on, you'd just have all humans classified the same. From there, you'd have a model based on size of the human or
(median human in, say, a structure you can't "see" inside).

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@2ck one potential issue is that many people would not want to use self driving cars which are merely maximizing for the number of lives as this can lead to situations where your own car would sacrifice you in order to save other people (regardless of who or what is to blame for the accident). There are many other such edge cases but the issue is rarely as black and white as simply optimizing a discrete variable.

@zpartacoos I would expect governments (or at least my government) to regulate that a vehicle capable of making such tradeoffs must minimize overall expected loss of life > injury > property damage. So, it's not that people even have the choice: AVs are just vehicles that try to minimize harm (or maximize survivability...I think those can be different things, but not sure at this moment how to distinguish more closely). The code for the vehicles can be signed and verified so that user-customizations can be identified and, if they don't adhere to the spirit of the harm-reduction regulation, the responsible party can be fined, jailed, or whatever.

I would also push back on the description of such optimizations as "black and white": my whole point is that they are not. The autonomous system is always optimizing *multiple* variables which include potential loss of life and other potential harms, but also travel time and ride quality. It has to be that way or all the cars would stay parked (safest that way) or go so slow no one would use them.

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