342 SUMMARY AND CONCLUSIONSgenes. Chapter 2 then described the many assumptions that have to be
incorporated into statistical models to uphold a par tic u lar picture of
genes and intelligence. Th ese were exposed one by one and show the fi nal
picture to be a rather weird concoction of unlikely, even bizarre, conjec-
tures. Th e data— most prominently from twin studies— are easily ex-
plained by the clear falsity of such assumptions.
Chapter 3 described something similar for intelligence testing, as seen
in the IQ test. Remarkably, such tests have no test validity in the way that
ordinary scientifi c and medical instruments have— that is, we do not
know what they mea sure. In the absence of a proper scientifi c model of
intelligence it is, of course, impossible to know. Instead, I show how the
tests are constructed on a far more subjective basis. Th at is to assume in
advance which people have more or less intelligence— and then construct
the test to agree with it. Th e rest of the chapter examined attempts to gloss
over that subjectivity; challenged the many defenses of it; and described
the vari ous ripples through, and aft ermaths in, our socie ties, their insti-
tutions, and their real people.
Chapter 4 introduced the alternative new view. It attempted to bring
together many recent fi ndings and theoretical advances in a coherent pic-
ture. It explained that a dynamic systems view of living things is needed,
because the standard picture of the genes—as fi xed codes for form and
variation— would be useless in the rapidly changing environments that
most organisms encounter. Instead what is needed are adaptable systems
that can develop suitable forms and variations in the course of life. Th e
chapter explained that living systems can do this by assimilating the
informational structure in the environment as experienced. Hence we
got “intelligent systems” even at the origins of life, but more spectacularly
in their evolution into more complex forms in increasingly changeable
environments.
Such systems create potential, rather than merely expressing it; they
generate far wider, but more useful, variations than could be produced
by the standard genes- plus- environments model. Th e chapter described
the many implications of these new foundations for understanding po-
tential. For example, in intelligent systems, we would expect to fi nd little
relationship between variation in genes and variation in forms and
be hav iors— just as research fi nds. Another is that intelligent systems are a
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