To create a perfect AI for self-driving, one first must resolve all that complicated, badly-understood stuff that might interfere with bulling ahead. For example, if the car should prefer the driver’s life over the pedestrian’s life.
But while we contemplate such questions, we lose tens of thousands of lives in car crashes per year.
The people of Tesla made the rational decision of bulling aheadinstead. As their AI is not perfect, sometimes it makes decisions with deadly consequences. But in total, it saves lives.
Their AI has an imperfect but good enough formalism. AFAIK, it’s something that could be described in English as “drive to the destination without breaking the driving regulations, while minimizing the number of crashes”, or something like this.
As their AI is net saving lives, it means their formalism is indeed good enough. They have successfully reduced a complex ethical/societal problem to a purely technical problem.
Rogue AGI is very likely to kill all humans. Any better-than-rogue-AGI is an improvement, even if it doesn’t fully understand the complicated and ever changing human preferences, and even if some people will suffer as a result.
Even my half-backed sketch of a formalism, if implemented, will produce an AI that is better than rogue AGI, in spite of the many problems you listed. Thus, working on it is better than waiting for the certain death.
In fact, even asking for an “adequate” formalism is putting the cart before the horse, because nobody even has a set of reasonable meta-criteria to use to evaluate whether any given formalism is fit for use
A formalism that saves more lives is better than the one that saves less lives. That’s good enough for a start.
If you’re trying to solve a hard problem, start with something simple and then iteratively improve over it. This includes meta-criteria.
fate worse than death
I strongly believe that there is no such a thing. Explained it in detail here.
We could use the Tesla AI as a model.
To create a perfect AI for self-driving, one first must resolve all that complicated, badly-understood stuff that might interfere with bulling ahead. For example, if the car should prefer the driver’s life over the pedestrian’s life.
But while we contemplate such questions, we lose tens of thousands of lives in car crashes per year.
The people of Tesla made the rational decision of bulling ahead instead. As their AI is not perfect, sometimes it makes decisions with deadly consequences. But in total, it saves lives.
Their AI has an imperfect but good enough formalism. AFAIK, it’s something that could be described in English as “drive to the destination without breaking the driving regulations, while minimizing the number of crashes”, or something like this.
As their AI is net saving lives, it means their formalism is indeed good enough. They have successfully reduced a complex ethical/societal problem to a purely technical problem.
Rogue AGI is very likely to kill all humans. Any better-than-rogue-AGI is an improvement, even if it doesn’t fully understand the complicated and ever changing human preferences, and even if some people will suffer as a result.
Even my half-backed sketch of a formalism, if implemented, will produce an AI that is better than rogue AGI, in spite of the many problems you listed. Thus, working on it is better than waiting for the certain death.
A formalism that saves more lives is better than the one that saves less lives. That’s good enough for a start.
If you’re trying to solve a hard problem, start with something simple and then iteratively improve over it. This includes meta-criteria.
I strongly believe that there is no such a thing. Explained it in detail here.