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12.5 Clarifying the Ethics of Justice: Extending the Golden Rule in to a Multifactorial Ethical Model 221
And the concept of “setting a good example” ties in with an important concept from learning
theory: imitative learning. Humans appear to be hard-wired for imitative learning, in part via
mirror neuron systems in the brain; and, it seems clear that at least in the early stages of AGI
development, imitative learning is going to play a key role. Copying what other agents do is an
extremely powerful heuristic, and while AGIs may eventually grow beyond this, much of their
early ethical education is likely to arise during a phase when they have not done so. A strength
of the classic Golden Rule is that one is acting according to behaviors that one wants one’s
observers to imitate — which makes sense in that many of these observers will be using imitative
learning as a significant part of their learning toolkit.
The truth of the matter, it seems, is (as often happens) not all that simple or elegant. Ethical
behavior seems to be most pragmatically viewed as a multi-objective optimization problem,
where among the multiple objectives are three that we have just discussed, and two others that
emerge from learning theory and will be discussed shortly:
1. The imitability (i.e. the Golden Rule fairly narrowly and directly construed): the goal of
acting in a way so that having others directly imitate one’s actions, in directly comparable
contexts, is desirable to oneself
2. The comprehensibility: the goal of acting in a way so that others can understand the
principles underlying one’s actions
3. Experiential groundedness. An intelligent agent should not be expected to act according
to an ethical principle unless there are many examples of the principle-in-action in its own
direct or observational experience
4. The categorical imperative: Act according to abstract principles that you would be
happy to see implemented as universal laws
5. Logical coherence. An ethical system should be roughly logically coherent, in the sense
that the different principles within it should mesh well with one another and perhaps even
naturally emerge from each other.
Just for convenience, without implying any finality or great profundity to the list, we will refer
to these as the "five imperatives."
The above are all ethical objectives to be valued and balanced, to different extents in different
contexts. The imitability imperative, obviously, loses importance in societies of agents that don’t
make heavy use of imitative learning. The comprehensibility imperative is more important
in agents that value social community-building generally, and less so in agent that are more
isolative and selffocused.
Note that the fifth point given above is logically of a different nature than the four previous
ones. The first four imperatives govern individual ethical principles; the fifth regards systems of
ethical principles, as they interact with each other. Logical coherence is of significant but varying
importance in human ethical systems. Huge effort has been spent by theologians of various
stripes in establishing and refining the logical coherence of the ethical systems associated with
their religions. However, it is arguably going to be even more important in the context of AGI
systems, especially if these AGI systems utilize cognitive methods based on logical inference,
probability theory or related methods.
Experiential groundedness is important because making pragmatic ethical judgments is
bound to require reference to an internal library of examples (“episodic ethics”) in which eth-
ical principles have previously been applied. This is required for analogical reasoning, and in
logic-based AGI systems, is also required for pruning of the logical inference trees involved in
determining ethical judgments.
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