Genes, Brains, and Human Potential The Science and Ideology of Intelligence

A CREATIVE COGNITION 229

involves a search through feelings as much as through in de pen dent cog-

nitions. Th is meshing of cognitive activity in feelings— and, through that,

their grounding in the outside world—is what distinguishes animals from

robots. It resolves as the deeper phenomenon of belief, which might be

defi ned as knowledge with feeling. We can talk about robots learning,

memorizing, making decisions, having knowledge, and so on. But we do

not talk about robots having beliefs. Without beliefs, they remain much

less creative than the humans who invent them.

Th is attractor landscape combining cognition and feeling is what

forms individual identity—in humans, emotional intelligence, personal-

ity, and the concept of self that is known by the self and others: our minds.

EVOLVING COGNITION: A SUMMARY

Darwin understood that natu ral se lection, as the primary architect of
evolution, would only work if there were some system of variation pro-
duction in living things. He did not understand how the variation was
produced. But he recognized its importance. What he also did not under-
stand was that survival in changing environments required diff er ent
systems of variation production. Th e standard neo- Darwinian view is
that all or nearly all variation arises from random gene mutations. Th is is
what the behavioral ge ne ticists of IQ take to be the basis of the heritabil-
ity of IQ and the grounds for gene hunting.
Complex changeable environments, however, require adaptation on a
diff er ent time scale from Darwinian natu ral se lection. Th at is, it requires
intelligent (adaptable) variation rather than random variation. Variation
arising from intelligent systems far outstrips that pos si ble from random
gene mutations. Yet the latter is still claimed by behavioral ge ne ticists
as the main source of diff erences even in human intelligence.
Th e origins of life prob ably entailed random variations among com-
ponents of molecular ensembles. By the time of yeasts and bacteria, how-
ever, living organisms had evolved into self- organized intelligent systems
involving a variety of variation- producing pro cesses (usually summarized
by the term “epige ne tics”). Th ey survive today, in changing environments,
through sensitivity to the available statistical structure. Moreover, the

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