To construct a friendly AI, you need to be able to make vague concepts crystal clear, cutting reality at the joints when those joints are obscure and fractal - and them implement a system that implements that cut.
There are lots of suggestions on how to do this, and a lot of work in the area. But having been over the same turf again and again, it's possible we've got a bit stuck in a rut. So to generate new suggestions, I'm proposing that we look at a vaguely analogous but distinctly different question: how would you ban porn?
Suppose you're put in change of some government and/or legal system, and you need to ban pornography, and see that the ban is implemented. Pornography is the problem, not eroticism. So a lonely lower-class guy wanking off to "Fuck Slaves of the Caribbean XIV" in a Pussycat Theatre is completely off. But a middle-class couple experiencing a delicious frisson when they see a nude version of "Pirates of Penzance" at the Met is perfectly fine - commendable, even.
The distinction between the two case is certainly not easy to spell out, and many are reduced to saying the equivalent of "I know it when I see it" when defining pornography. In terms of AI, this is equivalent with "value loading": refining the AI's values through interactions with human decision makers, who answer questions about edge cases and examples and serve as "learned judges" for the AI's concepts. But suppose that approach was not available to you - what methods would you implement to distinguish between pornography and eroticism, and ban one but not the other? Sufficiently clear that a scriptwriter would know exactly what they need to cut or add to a movie in order to move it from one category to the other? What if the nude "Pirates of of Penzance" was at a Pussycat Theatre and "Fuck Slaves of the Caribbean XIV" was at the Met?
To get maximal creativity, it's best to ignore the ultimate aim of the exercise (to find inspirations for methods that could be adapted to AI) and just focus on the problem itself. Is it even possible to get a reasonable solution to this question - a question much simpler than designing a FAI?
I'm probably explaining myself poorly.
I'm suggesting that there should be a mathematical operator which takes a "digitized" representation of an agent, either in white-box form (e.g. uploaded human brain) or in black-box form (e.g. chatroom logs) and produces a utility function. There is nothing human-specific in the definition of the operator: it can as well be applied to e.g. another AI, an animal or an alien. It is the input we provide the operator that selects a human utility function.
I don't understand how such an operator could work.
Suppose I give you a big messy data file that specifies neuron state and connectedness. And then I give you a big complicated finite-element simulator that can accurately predict what a brain would do, given some sensory input. How do you turn that into a utility function?
I understand what it means to use utility as a model of human preference. I don't understand what it means to say that a given person has a specific utility function. Can you explain exactly what the relationship is between a brain and this abstract utility function?