Thought Experiments can be Harmful
R. I. Damper,
Image, Speech and
Intelligent Systems Research Group,
Department of
Electronics and Computer Science,
University of
Southampton,
Southampton SO17 1BJ,
UK.
Abstract
“One real experiment
is worth far more that a half century of debate about
the meaning of a
thought experiment.” (Gribbin 1984)
“Experience teaches
us, however, that there is no such thing as a thought experiment so clearly
presented that no philosopher can misinterpret it.” (Dennett 1995)
This paper presents
an argument in three parts:
1. Thought
experiments are a necessary and inescapable part of the process of theory
formation and scientific discovery.
2. Thought
experiments can be helpful in pinpointing and illuminating key theoretical
issues in a discipline. At best, when a critical level of development is
reached, they may even trigger revolutionary advances.
3. In other
disciplines, where the theoretical underpinnings are less developed or absent,
the value of thought experiments is uncertain. It is possible that they could
be misleading - even harmful.
So how can we tell if
a given thought experiment is in category 2 or 3? I will give examples of
various (mostly rather famous) thought experiments, and attempt to identify the
features which mark them out as being either helpful or harmful.
1. Thought
experiments are necessary. The
number of questions which can be posed, from a scientific perspective, about
the way that nature works is obviously infinite, so we cannot hope to answer
more than a fraction of them by practical experiment. Also, certain disciplines
such as evolutionary biology and economics do not lend themselves to
experimentation. Although computer simulation can play a part (Casti 1997), it
remains the case that we cannot avoid frequent recourse to ‘thinking our way
through’ a problem, i.e., to thought experiment.
Much of the material
taught to us as fact during our early scientific education has effectively to be taken on trust:
Neither the time nor the resources are there to verify everything for ourselves
by practical experiment. We accept and learn (mostly) what we are taught because
we believe implicitly in (to borrow the terms of Kuhn 1962) the ‘paradigm’
which defines ‘normal science’, because we are attracted to the apparent
rigour, rationality and predictive power of the paradigm, and because this
acceptance is the price of entry into the profession and community of science.
Once our knowledge and understanding of our discipline reaches a sufficient
level, however, we no longer need such heavy reliance on trust. Thanks to the
predictive power of scientific theories, it becomes possible to answer novel
questions by thought experiment.
But this way lies
danger! Before Galileo, the result of the following thought experiment would
have been ‘obvious’ (but wrong) to any thinking person: Drop separate light and
heavy masses together from a height (in a vacuum) and observe which accelerates
fastest. Clearly, the majority answer will be relative to the current state of
knowledge, but the simple fact of being in a majority is no guarantee of being
right. Yet a thought experiment relies on obtaining a consensus answer (albeit
from a select group of specialists) if it is to offer something more than
paradox.
The discussion of
Kuhn (1962, pp.99-101) on the relation of Einsteinian to Newtonian mechanics
bears on this point. The latter is an excellent theory within its range of
validity - that of low relative velocities - as its widespread, everyday use in
modern engineering attests. Incorrect predictions of Newtonian mechanics arise
from applying it outside of that range, which “... must be restricted to those
phenomena and to that precision of observation with which the experimental
evidence in hand already deals” (p. 100). But acceptance of this maxim rules
out thought experiments which, as we have seen, are necessary. As Kuhn (1962,
p. 101) says: “Is it really any wonder that the price of significant scientific
advance is a commitment that runs the risk of being wrong?” Thus, the same
difficulties arise as with other modes of reasoning such as abduction and
inductive inference.
2. Thought
experiments can be helpful. In
a number of justly famous and brilliant thought experiments circa 1905,
Albert Einstein revolutionised the whole basis of modern physics (see Jammer
1966, 1974 for comprehensive details). Partly, his extensive use of Gedankenexperiments
was a ‘forced move’, reflected the (then) technical difficulty of performing
practical experiments with elementary particles or bodies moving at
relativistic velocities. But an additional factor was that this modus
operandi perfectly matched Einstein’s incisive ability to identify and
illuminate the nub of the matter. However, the technical difficulties of
performing practical experiments have slowly receded. One of the more exciting
stories in science is surely Sir Arthur Eddington’s expedition to the 1919
solar eclipse in West Africa, during which the bending of starlight by the
sun’s gravitational field was observed, so confirming Einstein’s predictions.
But his predictions were not always so triumphantly right! In 1935, Einstein,
Podolsky, and Rosen described the famous EPR thought experiment, in which two
particles interact and then fly apart, retaining some ‘imprint’ of the
interaction. At a later time, a measurement is made of the state of one
particle which has implications for the state of the other. Space does not
allow us to develop the important theoretical point at issue here (see Penrose
1989, pp.361-369 for an accessible description) except to say that it bears on
the influence one particle can have on the other once they are no longer in the
same locality.
Einstein and Bohr
disagreed fundamentally on the outcome with Einstein arguing that the
intuitively correct (‘common sense’) answer was at odds with quantum mechanics.
The latter seemed to require that one particle must somehow ‘know’ about the
state of the other which Einstein maintained was contradictory. Accordingly,
quantum mechanical description could not be considered complete. A brilliant
experiment by Aspect and his colleagues (Aspect, Grangier, and Roger 1982;
Aspect, Dalibard, and Roger 1982) has largely resolved the issue in favour of
Bohr. Although it would be a mistake to see this as the last word on the
matter, there was indeed an ‘entanglement’ of states even though the particles
were far from each other’s locality.
So what do we learn?
First, Gedankenexperiments can be blindingly insightful as in the majority of
Einstein’s predictions. Second, a thought experiment which gives birth to a
paradox (cf. the EPR paradox) can be nonetheless useful, laying down an agenda
for subsequent work aimed at resolving it.
Before continuing, we
should note that Turing’s seminal (1936) paper is properly a thought
experiment. He effectively invented a (virtual) digital computer - the Turing
machine - so allowing him to solve a problem in mathematical logic. In this
sense, his thought experiment was a trigger to subsequent revolutionary
advances in computer technology. Helpful indeed!
3. Thought
experiments can be harmful. Thought
experiments have been a popular investigative device in artificial
intelligence, cognitive science and philosophy of mind, where the theoretical
underpinnings are nowhere near as well developed as in physics. In AI, the
classic thought experiment is Searle’s (1980) Chinese Room argument (CRA): a
computer program intended to ‘understand Chinese’ would not really do so
because Searle himself could manually execute the same algorithmic steps while
understanding nothing of Chinese. The argument has, of course, been thoroughly
well debated (e.g., Harnad 1989; Penrose 1989; Copeland 1993; Boden 1994;
Franklin 1995; Preston and Bishop (2002) and the peer commentary appearing with
the original article), yet it is surprising how few commentators remark on the
practicality of doing what Searle proposes. An exception is Copeland (1993, p.
127) who writes of “the built-in
absurdity of Searle’s scenario”. What Searle and others seem ready blithely to
assume - the existence of a Chinese ‘understanding’ program able to pass the
Turing test (Turing 1950) - is so far beyond the current capabilities of AI and
computer technology as to amount to science fiction. What could we possibly
learn from such a fanciful conception? There is no realistic way of resolving
any paradoxes which arise, save appeals to common sense, and we know from the
example of quantum mechanics how fallible this is.
One can conceive of
two (at least) possible rejoinders. It could be said that Einstein’s
Gedankenexperiments were similarly fanciful: no one could chase after a light
beam at the speed of light! Yet experimental tests of Einstein’s predictions
were on the verge of being practical - by observing binary stars, eclipses of
the sun, etc. So there seems to be a matter of degree here. Another point of
view might be that it is too early to pronounce on the CRA: in time, Searle’s
predictions might be proved (more or less) right or wrong by empirical means.
My own feeling is that this will not happen: the proposed scenario is just too
far from practical, experimental test. But perhaps some good can come out of
the CRA if we substitute a task closer to the capabilities of current computer
programs than understanding Chinese. This direction was first explored by
Puccetti (1980), who substituted the chess room for the Chinese room, although
to my mind he did not press the point home.
Searle’s CRA was
chosen here for illustration, but there is no shortage of wildly implausible
thought experiments in cognitive science
and the philosophy of mind. One might mention the Twin Earth argument of
Putnam (1975) - see Lloyd (1989) and Kim (1998) for discussion - which relies
on confusing your earthly conception of some object with its apparently
identical (but subtly different) counterpart in a twin world. Here, Dennett
(1995, pp. 410-411) lays the argument bare by presenting “a more realistic
example” which “could be” true, involving cats and Siamese cats. Next on my
list is the thought experiment that actually convinced me that a paper such as
this one was necessary. Dietrich (1989), in developing his argument that
computational states involve content (semantics) as well as merely formal
manipulation (syntax), writes: “Imagine that I had an exact duplicate made of
me yesterday” (p. 123). Well, yes, imagine.
Finally, to negate
the impression that thought experiments could never be of any great value in
this area, I offer Braitenberg (1984) as a clear counter example. We have built
‘vehicles’ similar to those proposed in Braitenberg’s series of thought
experiments in synthetic psychology, with interesting results (Damper, French,
and Scutt 2000). Here, of course, the value of Braitenberg’s contribution lies
in not departing too far (if at all) from what is practical.
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This article is based
on a paper given at the conference “Model-Based
Reasoning” (MBR ’01), May 17-19, Pavia, Italy.