Philip Kitcher
Belief without Proof
Philip Stuart Kitcher
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Philosopher of science,
now at Columbia
University.
Has written on
creationism,
sociobiology, the idea
of scientific progress
and on the implications
of biotechnology for
the future of humans.
Against simple distinctions
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It seems easy to draw a sharp line between
evidence, reason and science on one hand and
faith and religion on the other.
Tennyson: ‘believing where we cannot prove’.
Creationists accept this line, but insist that
evolution is a matter of faith just as much as
believing in the Bible (or the Quran) is.
Too simple a dichotomy
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“(S)cience is not a body of demonstrated
truths. Virtually all of science is an exercise
in believing where we cannot prove. Yet,
scientific conclusions are not embraced by
faith alone.” (269)
So what is this middle ground between proof
and faith?
Ideals of certainty
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Mathematical proof
Direct observation
But recall Descartes– if we work at it, we can muster
up a little doubt even about things as obvious as
these!
Sometimes eyewitnesses are just wrong (Dawkins’
Gorilla).
And some ‘theorems’ have proven false.
Science, too, has often got things wrong.
Past errors in science
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Phlogiston
Caloric
Ether
Protein as the ‘genetic material’
All reasonable conclusions at the time, but
now known to have been mistaken…
Science always reaches beyond the evidence
we have. Consider F=ma…
The search for evidence
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But science finds many clever ways of testing its
theories, and extending those tests to new conditions
and cases.
In the end we really do get evidence about how
things we can’t even see function.
But the conclusions scientists draw are always open
to new challenges.
Even Newton’s mechanics has been overturned.
So?
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Should we just give up and be outright
skeptics?
Or is there some middle ground here?
We have to reject over-confidence in science,
but we don’t want to completely dismiss it
either.
We can have good (even excellent) evidence
without certainty.
Theories
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“All theories are revisable, but not all theories
are equal.”
In particular, the evidence for evolution is as
good as it gets– in that sense, we can justify
saying that evolution is a fact.
The long time frame of evolution is no less
accessible to test and observation than atoms,
molecules, distant galaxies or fundamental
laws of physics.
The value of predictions
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The Hay Fever strategy: A theory about hay
fever makes some odd predictions.
Suppose those predictions turn out to be true.
Wouldn’t it be reasonable to suppose that the
theory is ‘on the right track’?
A real case: Pascal’s confirmation of
Torricelli’s atmospheric hypothesis.
Hypothetico-deductive tests
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Theories can be thought of as collections of ‘claims
or statements’.
We can reason with those claims and statements,
reaching various conclusions.
Some of those conclusions are the kinds of claims
we can test by observation.
When these conclusions are confirmed by
observation, the theory they follow from is also
confirmed.
On deduction vs. ordinary reasoning
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A deductively valid argument is such that, if
its premises are all true, its conclusion must
also be true. There’s no way (even in an
imaginary world) that the premises can hold
without the conclusion holding too.
“It was -20 last night, so the bird bath is
frozen.” This is not deductively valid, but it is
a good argument!
The temptation of falsificationism
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On one hand, if a theory is true, and some
observational consequence follows deductively from
that theory, then that consequence must also be true.
But on the other hand, if all of a theory’s
observational consequences that we can check are
true, the theory could still be true.
So truth of observational consequences is at best
weak evidence for a theory’s truth, but the falsehood
of just one is conclusive evidence against the
theory’s truth!
Sir Karl Popper (1902-1994)
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A scientific theory must
be falsifiable– it must
make some observable
predictions whose
falsehood would refute
it.
But no theory is really
confirmed by its
successful predictions.
Charges against evolution
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That it makes no predictions (so it’s not
scientific at all).
That it makes false predictions (so it’s been
refuted).
That it doesn’t make the kinds of predictions
it should (the kinds of experiments and
observations evolutionary biologists make
‘have no bearing’ on the theory’)
Ad Hoc
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Roughly means, ‘to this’. An ad hoc response
to a problem is one that we make up just for
that problem.
An ad hoc defence of a theory is a claim that
we have no independent support for, and that
(somehow) alters what the theory predicts so
that it no longer makes a prediction we know
to be false.
The trouble with falsificationism
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It’s either far too demanding or it’s far too loose as a
criterion for science.
Newton’s mechanics includes three laws: inertia,
F=ma and action-reaction, plus gravity. But by
themselves they predict nothing (nothing rules out
other forces)!
But if we extend the mechanics to make it falsifiable,
we fall into the guru’s trap: ‘quietness is wholeness
in the center of stillness’ is now equally ‘scientific’!
Pierre Duheme
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Hypotheses are tested
in bundles.
When a prediction
fails, we have options–
any claim in the bundle
that produced the false
prediction could be the
false one.
Scientific Success
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If it can’t be tested at all, it surely isn’t science.
Consider celestial mechanics and the case of Uranus.
Scientists couldn’t fit its orbit into their Newtonian
models.
But the answer wasn’t ‘give up on Newton’– it was,
‘find the unknown planet that’s altering Uranus’s
orbit’: a success!
Auxiliary hypotheses
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We test theories by combining them with auxiliary
hypotheses (only gravity affects the motions of the
planets; the bodies whose gravitational mass
significantly affects the orbit of Uranus are the sun,
Jupiter and Saturn,…).
Adams and Leverrier changed an auxiliary
hypothesis (adding Neptune to the story), and used
the resulting calculations to predict where Neptune
should be seen.
Their new auxiliary was independently testable.
Good Auxiliaries
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Hypotheses are tested in bundles.
But they can be part of different bundles.
When we use an auxiliary to ‘save’ a theory from
refutation, we should be able to test it as part of a
different bundle (with components that are otherwise
considered reliable).
Newton’s auxiliaries (and his strategy for applying
them) worked, not just one case at a time, but over
and over for many different cases, in celestial
mechanics and beyond.
Good theories
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Use independently testable auxiliaries
Are unified (apply similar auxiliaries and
strategies for solving a wide range of
problems).
Are fecund (lead us to discoveries that we
hadn’t anticipated– new planets (Neptune and,
later, Pluto), new/better measurements
(improvements in clocks, etc. guided by
mechanics)…
Openness and risk
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Science is always open/incomplete, and its
practitioners are almost always focused more
on what’s not (yet) settled than on what is
settled (for now).
This also means that it’s always at risk of
failing the test. New and better observations
and measurements can force us to give up old
theories and invent new ones.
Pseudo-science
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When auxiliaries aren’t independently testable,
And problem-solving strategies are developed
independently for each problem the theory faces,
And no new predictions or improved measurements
or other nice results are obtained, then,
We don’t have a scientific theory at all.
On the other hand,
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When auxiliaries are testable separately from the
theory,
When the theory applies its problem-solving
strategies systematically to a wide range of
problems,
And when the results are successful predictions
(even when applied to entirely new bodies of
evidence) and ideas for still more observations that
the theory makes predictions about, then
We have a good scientific theory.