The Fabric of Reality David Deutch

partly on the attributes of other genes and species (i.e. other ideas) that are
already present there. The new world-view that may be implicit in a theory
that solves a problem, and the distinctive features of a new species that
takes over a niche, are 
emergent properties of the problem or niche. In other
words, obtaining solutions is inherently complex. There is no simple way of
discovering the true nature of planets, given (say) a critique of the celestial-
sphere theory and some additional observations, just as there is no simple
way of designing the DNA of a koala bear, given the properties of eucalyptus
trees. Evolution, or trial and error — especially the focused, purposeful form
of trial and error called scientific discovery — are the only ways.
For this reason, Popper has called his theory that knowledge can grow only
by conjecture and refutation, in the manner of Figure 3.3, an 
evolutionary
epistemology. This is an important unifying insight, and we shall see that
there are other connections between these two strands. But I do not want to
overstate the similarities between scientific discovery and biological
evolution, for there are important differences too. One difference is that in
biology variations (mutations) are random, blind and purposeless, while in
human problem-solving the creation of new conjectures is itself a complex,
knowledge-laden process driven by the intentions of the people concerned.
Perhaps an even more important difference is that there is no biological
equivalent of 
argument. All conjectures have to be tested experimentally,
which is one reason why biological evolution is slower and less efficient by

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an astronomically large factor. Nevertheless, the link between the two sorts
of process is far more than mere analogy: they are two of my four intimately
related ‘main strands’ of explanation of the fabric of reality.
Both in science and in biological evolution, evolutionary success depends on
the creation and survival of 
objective knowledge, which in biology is called
adaptation. That is, the ability of a theory or gene to survive in a niche is not
a haphazard function of its structure but depends on whether enough true
and useful information about the niche is implicitly or explicitly encoded
there. I shall say more about this in Chapter 8.
We can now begin to see what justifies the inferences that we draw from
observations. We never draw inferences from observations alone, but
observations can become significant in the course of an argument when they
reveal deficiencies in some of the contending explanations. We choose a
scientific theory because arguments, only a few of which depend on
observations, have satisfied us (for the moment) that the explanations
offered by all known rival theories are less true, less broad or less deep.
Take a moment to compare Figures 3.1 and 3.3. Look how different these
two conceptions of the scientific process are. Inductivism is observation- and
prediction-based, whereas in reality science is problem- and explanation-
based. Inductivism supposes that theories are somehow extracted or
distilled from observations, or are justified by them, whereas in fact theories
begin as unjustified conjectures in someone’s mind, which typically 
precede
the observations that rule out rival theories. Inductivism seeks to justify
predictions as likely to hold in the future. Problem-solving justifies an
explanation as being better than other explanations available in the present.
Inductivism is a dangerous and recurring source of many sorts of error,
because it is superficially so plausible. But it is not true.
When we succeed in solving a problem, scientific or otherwise, we end up
with a set of theories which, though they are not problem-free, we find
preferable to the theories we started with. What new attributes the new
theories will have therefore depends on what we saw as the deficiencies in
our original theories — that is, on what the problem was. Science is
characterized by its problems as well as by its method. Astrologers who
solve the problem of how to cast more intriguing horoscopes without risking
being proved wrong are unlikely to have created much that deserves to be
called scientific knowledge, even if they have used genuine scientific
methods (such as market research) and are themselves quite satisfied with
the solution. The problem in genuine science is always to understand some
aspect of the fabric of reality, by finding explanations that are as broad and
deep, and as true and specific, as possible.
When we think that we have solved a problem, we naturally adopt our new
set of theories in preference to the old set. That is why science, regarded as
explanation-seeking and problem-solving, raises no ‘problem of induction’.
There is no mystery about why we should feel compelled tentatively to
accept an explanation when it is the best explanation we can think of.
TERMINOLOGY

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 solipsism The theory that only one mind exists and that what appears to be
external reality is only a dream taking place in that mind.
problem of induction Since scientific theories cannot be logically justified by
observation, what does justify them?
induction A fictitious process by which general theories were supposed to
be obtained from, or justified by, accumulated observations.
problem A problem exists when it seems that some of our theories,
especially the explanations they contain, seem inadequate and worth trying
to improve.
criticism Rational criticism compares rival theories with the aim of finding
which of them offers the best explanations according to the criteria inherent
in the problem.
science The 
purpose of science is to understand reality through
explanations. The characteristic (though not the only) 
method of criticism
used in science is experimental testing.
experimental test An experiment whose outcome may falsify one or more of
a set of rival theories.
SUMMARY
In fundamental areas of science, observations of ever smaller, more subtle
effects are driving us to ever more momentous conclusions about the nature
of reality. Yet these conclusions cannot be deduced by pure logic from the
observations. So what makes them compelling? This is the ‘problem of
induction’. According to inductivism, scientific theories are discovered by
extrapolating the results of observations, and justified when corroborating
observations are obtained. In fact, inductive reasoning is invalid, and it is
impossible to extrapolate observations unless one already has an
explanatory framework for them. But the refutation of inductivism, and also
the real solution of the problem of induction, depends on recognizing that
science is a process not of deriving predictions from observations, but of
finding explanations. We seek explanations when we encounter a problem
with existing ones. We then embark on a problem-solving process. New
explanatory theories begin as unjustified conjectures, which are criticized
and compared according to the criteria inherent in the problem. Those that
fail to survive this criticism are abandoned. The survivors become the new
prevailing theories, some of which are themselves problematic and so lead
us to seek even better explanations. The whole process resembles biological
evolution.
Thus we acquire ever more knowledge of reality by solving problems and
finding better explanations. But when all is said and done, problems and
explanations are located within the human mind, which owes its reasoning
power to a fallible brain, and its supply of information to fallible senses.
What, then, entitles a human mind to draw conclusions about objective,
external reality from its own purely subjective experience and reason?

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