Many people think you can solve the Friendly AI problem just by writing certain failsafe rules into the superintelligent machine's programming, like Asimov's Three Laws of Robotics. I thought the rebuttal to this was in "Basic AI Drives" or one of Yudkowsky's major articles, but after skimming them, I haven't found it. Where are the arguments concerning this suggestion?
I read your comment again. I now see the distinction. One merely tries to satisfy something while the other tries to optimize it as well. So your definition of a 'failsafe' is a constraint that is satisfied while something else is optimized. I'm just not sure how helpful such a distinction is as the difference is merely how two different parameters are optimized. One optimizes by maximizing money and tax paying while the other treats each goal differently, it tries to optimize tax paying by reducing it to a minimum while it tries to optimize money by maximizing the amount. This distinction doesn't seem to matter at all if one optimization parameter (constraint or 'failsafe') is to shut down after running 10 seconds.