One of the most annoying arguments when discussing AI is the perennial "But if the AI is so smart, why won't it figure out the right thing to do anyway?" It's often the ultimate curiosity stopper.
Nick Bostrom has defined the "Orthogonality thesis" as the principle that motivation and intelligence are essentially unrelated: superintelligences can have nearly any type of motivation (at least, nearly any utility function-bases motivation). We're trying to get some rigorous papers out so that when that question comes up, we can point people to standard, and published, arguments. Nick has had a paper accepted that points out the orthogonality thesis is compatible with a lot of philosophical positions that would seem to contradict it.
I'm hoping to complement this with a paper laying out the positive arguments in favour of the thesis. So I'm asking you for your strongest arguments for (or against) the orthogonality thesis. Think of trying to convince a conservative philosopher who's caught a bad case of moral realism - what would you say to them?
Many thanks! Karma and acknowledgements will shower on the best suggestions, and many puppies will be happy.
Many of our tools are supposed to be web browsers, email clients, etc., but have a history of suddenly doing something completely nuts like taking over the whole computer, which was obviously not the intended purpose. Programming is hard that way - the result will only follow your program, verbatim. Attempts to give programs a greater sense of context and implications aren't new - they're called "higher level languages". They feel less like hand-holding a dumb machine and more like describing a thought process, and you can even design the language to make whole classes of lower-level bugs unwriteable, but machines still end up doing what they're instructed, verbatim (where "what they're instructed" can now also include the output of compiler bugs).
The trouble is that you can't rule out every class of bugs. It's hard (impossible?) to distinguish a priori between what might be a bug and what might just be a different programmers' intention, even though we've been wishing for the ability to do so for over a century. "Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?"
Yet, people around here seem to believe that the AI will develop an accurate model of the world even if its input isn't all that accurate.