Preproceedings 2006 - Austrian Ludwig Wittgenstein Society

Is naturalism progressive? A naturalistic approach to the philosophy of science - Frey
2. These attributes are not a subject to speculation,
there being lots of empirical results from cognitive
science for this.
3. These results can be explained by evolutionary
biology.
4. Historical and social factors are not neglected – they
are complemented.
5. The theories of philosophers of science have to be
warranted by historical case studies as another
source of empirical support.
The last point merits a short explanation. Donovan
and Laudan (1988) examine postulates from Kuhn and
Lakatos by checking them through case studies. The
majority of postulates are disproved. So, even very
thorough, credible and expert historicists like Kuhn or
Lakatos lose the connection to how „real science” is done.
This has to be avoided at all costs.
Of course there are objections to cognitive
naturalistic approaches as well. Four of them shall be
discussed below:
The first objection claims that individual cognitive
processes cannot be studied; and if they could, it would
not be possible to generalise from a genius to other
individuals. This objection can be rejected, in so far as
naturalists are interested in the cognitive processes that
are common to all individuals. There are loads of data
concerning human problem-solving, decision-theory,
confirmation of hypotheses which are all relevant to
discoveries (e. g. Tooby & Cosmides 1992; Newell &
Simon 1972; Gigerenzer 1999).
The second objection states that there is no wellfounded
psychological theory to describe those
phenomena. This is wrong, as the so-called Cognitive
Psychology has been around since 1970 and Evolutionary
Psychology since 1992.
The third objection holds that biological explanations
are too reductionistic and on the wrong level of description
– thus these explanations are not able to explain cultural
processes like scientific endeavors. Biological
explanations, however, do not claim to explain all levels of
analysis and I put emphasis on their complementary
nature. Plus, reductionistic approaches have been very
successful in theory and practice, e. g. biology
(Ruse 1988).
Fourth, accusations like evolutionary accounts imply
radical nativism, panadaptionism or no possibiliy of
falsification are outdated (nativism and panadaptionism:
see Cosmides & Tooby 1994; Vollmer 1985/2003; not
falsifiable: see Williams 1973; Buss 1989).
In the following paragraphs I would like to apply this
theoretical framework to a very short example. The
example also emphasises the importance of empirical
support and the necessity to do case studies.
Human beings have massive problems in handling
complex systems, a claim that is empirically well supported
by quite a number of (computer)-simulations (Dörner 1989,
1983, 1976). Dörner found that nearly all subjects –
scientists or not – use the same strategies for problemsolving
in artificial complex task environments. The
strategies used are often error-prone and certainly a long
way from optimal. Examples for errors are linear problemsolving,
failure to take into account side effects, long term
effects or feedback-loops. Moreover, humans tend to solve
problems first that loom large, but not those that are really
important – thus the question of priority is neglected. Other
errors include the absence of control, the inability to see or
correct one's own mistakes and difficulties to control a
process. These errors were found to be almost completely
independent of task and subject.
To explain these shortcomings in real complex
systems managed by scientists there is no need to
postulate other factors than those above. But this has
frequently been done.
Let's take a look at the management of ecosystems
like forests or national parks – real complex systems, most
often run by scientists. Consider the Yellowstone national
park:
Practically identical with the so called „Freezer”simulation
of Dörner we see the regulation of a state (the
animal population of deer, beaver, bears of the moment),
but not of the process. As these static tries to regulate
animal populations are often confined to only one animal
species (linear thinking) there have been big and
unwanted fluctuations with disastrous consequences
(Chase 1987). These fluctuations have been well-known
since 1930 (one catastrophe through the same type of
regulation) – but it seems to be very hard to learn from
these mistakes.
Another big problem arose when the existing
multiple interdependencies and feedback-loops were not
heeded. One result was the sharp decline of beaver and
grizzly populations, because too many deer (which were
regulated!) used up mutual food resources (Chase 1987).
Two other examples that show practically the same
problem-solving mechanisms are the management of the
Blue Mountains in Oregon during the last 100 years (see
Langston 1995 for details) and various very problematic
introductions of new species (see Low 1999). I cannot go
into these examples for lack of space, but they are – when
seen in all their details – very illuminating: Again and again
we notice the very same cognitive strategies and methods
independent of context or time.
These short considerations imply the answer to the
question: Is naturalism progressive?
The answer is a resounding yes, as I hope I could
demonstrate. Not only is a naturalistic program (at least in
the philosophy of science) superior in explanatory power to
other attempts, but it is very much alive and fruitful as the
very short example of a „case study” hopefully could show.
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