Shane Legg wrote:
On 5/27/07, *Richard Loosemore* <[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>> wrote:

    What possible reason do we have for assuming that the "badness" of
    killing a creature is a linear, or even a monotonic, function of the
    intelligence/complexity/consciousness of that creature?

    You produced two data points on the graph, and two inequalities:

            B(Human) > B(Mouse)
            I/C/C(Human) > I/C/C(Mouse)



I thought two was enough to illustrate the argument, but if
you really need more... let's do 6:

Human, Chimpanzee, Goat, Mouse, Ant, Bacteria.

I presume most people would rate the things in this list as
going from most complex/intelligent/conscious to least?

I also guess that most people would rate the killing of these
living things as going from most bad to least bad?

Obviously individual cases will vary, for example killing a
person who is about to blow up a whole city of people is
not going to be so bad.  But, such external factors aside,
there seems to be a general principle.

If one accepts that there is, then the question becomes:
Where should we put a super human intelligent machine
on the list?  If it's not at the top, then where is it and why?

I don't claim to have answers to any of these questions,
I'm just wondering what other people's thoughts are.

Extrapolating from any number of datapoints is unreliable when all you have is a rank ordering.

Your rank ordering is extremely culture-dependent: are you asking someone who lives in India, for example?

And one final lesson from experimental design: have you ascertained that the relevant factor in the suggested rank ordering, above, is degree of complex/intelligent/conscious, rather than, say, the more likely empathic response (which has more to do with cuteness than anything else)? For example, try:

Human, Chimpanzee, Jackal, Gerbil, Ant, Bacteria.

I suggest that most people would rate Gerbil more worthy than Jackal.

More generally, I think the question is silly: I have only responded from a narrowly technical, data-fitting perspective.



Richard Loosemore

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