> The issue of androids is going to be an annoying one in a thousand years.
Do you really think it will take a thousand years for that situation to arise? I'm betting on less than fifty.
Do you really think it will take a thousand years for that situation to arise? I'm betting on less than fifty.
And "total lack of socialization" can instead be a full blown cooperative driving network of cars that inform one another for their course.
All of the things you mentioned can (and most have) been solved even in the current bunch of self-driving cars.
A toddle stepping into the street? A modern self-driving car sensor can "see" it better than the average driver -- and it doesn't even have to involve actual vision.
I'm not sure what you're arguing against exactly. Actual current research problems with self-driving-car vision are totally different (e.g. disambiguating signals when raining or snowing etc). And nothing insurmountable about these either.
>that dude X thinks he ought to be able to go first or simply doesn't give a shit what the car thinks
Whatever he thinks, if it translates to an actual action in his car, other automatic cars can respond to it in the blink of an eye.
Explicitly programming scenarios in is not how it really works.
>How much of it have we mapped, and how well does the machine cover it?
Enough for Google cars for example to have logged over 300K miles in actual conditions with no incidents.
Also enough to have such things (besides Google's) in pilot operation in several cities the world other, for things ranging from cargo transport to mass transportation (self-driving busses).
It's not like "programming the scenario in" is some huge switch/case statement that needs to cover all possible arrangements of things on the street -- it's machine learning algorithms with several rules and invariants to check and various corrective responses when those are off, and the smartness comes from the combinations of such rules.
>machines will remain shitty drivers because they can't respond with creative judgment to a new situation.
The think is, with the appropriate machine learning algorithms they can both add experience and respond with creative judgement to new situations -- they don't have to have hardcoded responses to them from the start.
Here is an example of the car failing for precisely the sorts of reasons I describe above.
So he made the same assumption as the car did. So what else could it do, magically guess?
Self-driving cars are not infallible -- they model the same assumptions we do. But a benefit is that they can also react much faster than we do -- which won't always save the day of course: if some idiot driving against the traffic, for example, suddenly appears in front of such a car, they will still be an accident in all probability.
As have thousands of actual human drivers -- and worse.
The human driver also said that he thought the bus would do the same thing the car "brain" thought it would.
>You are being a credulous fanatic, and I am done.
Oh, the irony.
We could have them now if we equipped all vehicles and pedestrians using roads with simple device to broadcast position, velocity, and planned route.