Date: Fri Sep 02 2005 - 14:12:36 MDT

> >From: "Michael Vassar" <>
> >Reply-To:
> >To:
> >Subject: Re: drives ABC > XYZ
> >Date: Tue, 30 Aug 2005 22:06:14 -0400
> >
> >>We're already
> >>assuming that. The A B C -> X Y Z example shows how, one step at
> >>a time, the system can take actions that provide greater utility
> >>from the perspective of its top-level goals, that nonetheless end
> >>up replacing all those top-level goals.
> >
> >Well then, so long as the ultimate goals are higher utility, from the
> >perspective of the original goals, than the original goals were, why is
> >this a problem? A human would typically not be able to predict the long
> >term expected utility of a change to its top level goals, but a FAI
> >wouldn't make such changes unless it could.
> >
> >>Another question entirely is whether, if the AI is told to maximize
> >>a score relating to the attainment of its top-level goals, and is
> >>given write access to those goals, it will rewrite those goals into
> >>ones more easily attainable? (We could call this the "Buddhist AI",
> >>perhaps?) The REAL top-level goal in that case
> >>is "maximize a score defined by the contents of memory locations X",
> >>but it doesn't help us to say that "maximization" won't be replaced.
> >>The kinds of goals we don't want to be replaced have referents
> >>in the real world.
> >
> >This really is a very very old insight for this list. Try to familiarize
> >yourself with the list archive or at least with the major articles. That
> >really applies to everyone who hasn't done so. Suffice it to say that such
> >concerns were addressed very thoroughly years ago.
> >
> >>You seem to be proposing that an AI will never make mistakes.
> >
> >In the human sense, yes. If an AI is superintelligent and Friendly for any
> >significant time it will reach a state from which it will not ever make the
> >sort of errors of reasoning which humans mean by mistakes. In fact, any
> >well calibrated Bayesian built on a sufficiently redundant substrate should
> >never make mistakes in the sense of either acting on implicit beliefs other
> >than its explicit beliefs or holding a belief with unjustified confidence.
> >Obviously, computing power, architectural details, and knowledge will
> >determine the degree to which it will or will not act in the manner which
> >actually maximized its utility function, but that is not what we humans
> >mean by a mistake. We are used to constantly taking actions which we have
> >every reason to expect to regret. A FAI shouldn't do that. This is an
> >important distinction and not at all a natural one. It shouldn't be
> >terribly shocking, but is. But by now we should be used to the idea that
> >computers can perform long series of mathematical operations without error,
> >and that performing the right long series of mathematical operations is
> >equivalent to making a decision under uncertainty, so they should be able
> >to make decisions under uncertainty without error, though due to the
> >uncertainty such decisions will usually be less optimal that the decisions
> >that would have been available given more information.
> >
> >>Making mistakes is a second way in which top-level goals can
> >>drift away from where they started.
> >
> >Making sub-optimal decisions can cause top-level goals to drift, but this
> >problem is absolutely unoavoidable, but should not be critical (and if it
> >is critical, that is, fundamental to the way reason works, we will just
> >have to do as well as we can). Account must be taken of it when designing
> >an FAI, but this only requires an incremental development beyond that
> >needed to protect it from Pascal's Wagers.
> >
> >

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