ID as a Theory of Technological Evolution
Metanexus 2001.08.10 4144 words
According to William Dembski, "The central issue in the debate over
biological evolution can...be put as follows: Is nature complete in the
sense of possessing all the resources necessary to bring about the
biological structures we see around us or does nature also require some
contribution of design to bring about those structures?"
But what is meant here by "complete"? And what are the "resources
necessary" for biological structures? Moreover, what is a "contribution of
design"? Is design here meant as "pattern" or as "purpose"? When someone has
"designs" on you, they are not the same as those "designs" one might like in
fashions or furniture, such as cuts or patterns. Furthermore, is design as
it appears in nature merely an artifact of our human ability to perceive
patterns and then create stories about those patterns?
Please take questions such as these with you as your read the following
essay "ID as a Theory of Technological Evolution ", especially since Dembski
also observes that it is "important to understand that intelligent design
(or ID as it is increasingly being abbreviated) is not yet another answer to
this counter-question. To ask what besides nature could conceivably have
played an essential role in the formation of biological systems is to ask
for an entity with causal powers to produce objects that nature unassisted
could not produce. The problem is that any such entities are not open to
direct empirical investigation."
Bill Dembski has a Ph.D. in mathematics from the University of Chicago, a
Ph.D. in philosophy from the University of Illinois at Chicago, and an
M.Div. from Princeton Theological Seminary. Bill has done post-doctoral work
at MIT, University of Chicago, Northwestern, Princeton, Cambridge, and Notre
Dame. He has been a National Science Foundation doctoral and post-doctoral
fellow. His publications range from mathematics to philosophy to theology.
His monograph The Design Inference appeared with Cambridge University Press
September 1998. In it he describes the logic whereby rational agents infer
intelligent causes. He is working with Stephen Meyer and Paul Nelson on a
book entitled Uncommon Descent, which seeks to reestablish the legitimacy
and fruitfulness of design within biology. He is a fellow of the Discovery
Institute's Center for the Renewal of Science and Culture and adjunct
professor in philosophy at the University of Dallas. For more information
about Prof. Dembski, please consult
<http://www.leaderu.com/offices/dembski/index.html>
--Stacey E. Ake
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From: William A. Dembski
Subject: ID as a Theory of Technological Evolution
Email: <dembski@discovery.org>
ID as a Theory of Technological Evolution
By William A. Dembski
1. Nature and Art
In Book II of the Physics Aristotle remarks, "If the ship-building art were
in the wood, it would produce the same results by nature." Aristotle is here
contrasting nature and art. Nature provides the raw materials (here wood);
art provides the means for fashioning those materials (here into a ship).
For Aristotle, art consists in the knowledge and skill to produce an object
and presupposes the imposition of form on the object from outside. On the
other hand, nature consists in capacities inherent in the physical world --
capacities that produce objects, as it were, internally and without outside
help. Thus in Book VII of the Metaphysics Aristotle writes, "Art is a
principle of movement in something other than the thing moved; nature is a
principle in the thing itself." Consequently, Aristotle refers to art as
completing "what nature cannot bring to a finish." Thomas Aquinas took this
idea and sacramentalized it into grace completing nature.
In Aristotle's distinction between art and nature lies the central issue in
the debate over biological evolution. The central issue is not the
interpretation of Genesis, nor whether humans are descended from apes, nor
whether all organisms trace their lineage to a last common ancestor. Indeed,
where one comes down on these side issues is irrelevant to the central
issue. The central issue is whether nature has sufficient resources in
herself to generate all of biological diversity or whether in addition
nature requires art to complete what nature alone cannot bring to a finish.
The Greek word for art is techne, from which we get our word technology. The
English word most commonly used to capture what Aristotle means by art
derives not from the Greek but from the Latin. That word is, of course,
design.
The central issue in the debate over biological evolution can therefore be
put as follows: Is nature complete in the sense of possessing all the
resources necessary to bring about the biological structures we see around
us or does nature also require some contribution of design to bring about
those structures? A typical reaction to this question is simply to observe
that biological systems are natural objects and then to pose the following
counter-question: What besides nature could conceivably have played an
essential role in the formation of biological systems? Although there has
been no dearth of answers to this counter-question (special creation,
vitalism, and orthogenesis come to mind), the answers given to date no
longer inspire confidence within much of the scientific community.
It is therefore important to understand that intelligent design (or ID as it
is increasingly being abbreviated) is not yet another answer to this
counter-question. To ask what besides nature could conceivably have played
an essential role in the formation of biological systems is to ask for an
entity with causal powers to produce objects that nature unassisted could
not produce. The problem is that any such entities are not open to direct
empirical investigation. Our knowledge of them can be at best indirect,
dependent on phenomena mediated through nature. But a designing intelligence
that mediates its action through nature has since the time of Darwin seemed
largely dispensable -- certainly from science and now increasingly from
common life.
The strength of intelligent design as an intellectual project consists not
in presupposing a prepackaged conception of a designer and then determining
how the facts of science square with that conception. Rather, intelligent
design's strength consists in starting with nature, exploring nature's
limitations, and therewith determining where design fits in the scheme of
nature. Aristotle claimed that the art of ship-building is not in the wood
that constitutes the ship. Likewise intelligent design claims that the art
of life-building is not in the physical stuff that constitutes life. But
intelligent design does not stop there. Rather, the very methods that
establish nature's limitations also establish that design is operating in
nature. Nor does intelligent design commit a god-of-the-gaps fallacy.
Intelligent design locates discontinuities in the causal structure of nature
that are inherently unbridgeable by natural causes. Such gaps are
ontological rather than epistemic, and thus offer no promise of being
removed by closer investigation of natural causes.
But why admit any gaps at all? Nature gives rise to human beings. Once human
beings are on the scene, they act as designing intelligences to produce
artifacts. But human beings are themselves natural. Art in Aristotle's sense
is therefore at most once removed from nature: Nature produces embodied
rational agents like us, who in turn produce designed objects. To speak of
nature herself being designed or to speak of natural objects (like
biological systems) being designed seems therefore to commit a category
mistake. To state the problem in the language of evolution: Nature in her
evolution produces life, and some of those evolved forms of life produce
designed objects. Yet to place design prior to the evolved forms that
produce design is to misconceive design.
The problem with this objection is that it still fails to address nature's
limitations, especially with regard to the emergence of biological systems.
Does nature in and of herself -- unassisted and unsupplemented -- have what
it takes to produce the diversity of life? To be sure, one can simply as a
metaphysical assumption suppose that nature can do all her own designing.
Aristotle made this assumption, and so did the ancient Stoics. For
Aristotle, final causes operated as a part of nature. Final causes
expressed purposes inherent in nature and were therefore capable of
effecting design (biological designs in particular). Thus in Book II of the
Physics Aristotle writes of purpose being present in both art and nature.
But endowing nature with purpose and therewith empowering nature to produce
design is not an option for most contemporary scientists. As Jacques Monod
put it, "The cornerstone of the scientific method is the postulate that
nature is objective. In other words, the systematic denial that 'true'
knowledge can be got at by interpreting phenomena in terms of final causes
-- that is to say, of 'purpose'."
Whence the removal of purpose and therewith design from nature? I lay the
blame with the mechanical philosophy that was prevalent at the birth to
modern science. Paradoxically, the very clockwork universe that the early
mechanical philosophers like Robert Boyle used to buttress design in nature
was in the end probably more responsible than anything for undermining
design in nature. The mechanical philosophy viewed the world as an
assemblage of material entities interacting by purely mechanical means.
Boyle advocated the mechanical philosophy because he saw it as refuting the
immanent teleology of Aristotle and the Stoics for whom design arose as a
natural outworking of natural forces. For Boyle this was idolatry,
identifying the source of creation not with God but with nature.
The mechanical philosophy offered a world operating by mechanical
principles and processes that could not be confused with God's creative
activity and yet allowed such a world to be structured in ways that clearly
indicated the divine handiwork and therefore design. What's more, the
British natural theologians always retained miracles as a mode of divine
interaction that could bypass mechanical processes. Over the subsequent
centuries, however, what remained was the mechanical philosophy and what
dropped out was the need to invoke miracles or God as designer. Henceforth,
purely mechanical processes could themselves do all the design work for
which Aristotle and the Stoics had required an immanent natural teleology
and for which Boyle and the British natural theologians required God.
2. Testing Nature's Limits
The mechanical philosophy is still with us, though in place of particles and
force we now tend to think in terms of fields and energy. The mechanical
philosophy has bequeathed to us a view of nature in which natural processes
operate unsupplemented by any form of teleology, purpose, or design.
Fortunately, this view of nature is testable. To see this, I will need to
describe some of my own work on design detection (especially as laid out in
my book The Design Inference). Yet instead of merely recapitulating that
work, I will approach it through Murray Gell-Mann's work on effective
complexity and total information.
Since the early 1990s Gell-Mann has been attempting to combine Shannon's
statistical theory of information with Kolmogorov's algorithmic theory of
information into a comprehensive theory of complexity and information for
science. Gell-Mann starts with the observation that the complexity that
interests us in practice is not pure randomness but patterned regularities
that remain once the effects of randomness have been factored out. Gell-Mann
thus defines "effective complexity" as the complexity inherent in these
patterned regularities. Moreover, he defines "total information" as the
effective complexity together with the complexity inherent in the effects of
randomness that were factored out. He then characterizes effective
complexity mathematically in terms of an algorithmic information measure
that measures the extent to which patterned regularities can be compressed
into a minimal representation (he calls such representations "schemata").
Moreover, he characterizes the residual effects of randomness mathematically
in terms of a Shannon information measure that measures the extent to which
random deviations depart from the patterned regularities in question. Total
information thus becomes the sum of an algorithmic information measure and a
Shannon information measure.
Gell-Mann's theory of effective complexity attempts to account for how
complex adaptive systems like us make sense out of a world that exhibits
regularities as well as random deviations from those regularities. Though
richly suggestive, applying Gell-Mann's mathematical formalism in practice
is largely intractable since it requires taking conceptual schemata of
patterned regularities appropriate to some inquiry, mapping them onto a
computational data structure, and then seeing how such data structures can
be reduced in size while faithfully preserving the conceptual structures
that map from conceptual to computational space. Thus far Gell-Mann's theory
has resisted detailed applications to real-world problems.
Why then do I consider it here? According to philosopher David Roche, design
theorists like me are all mixed up about information theory and complexity.
Thus Roche argues that the Darwinian mechanism is well able to account for
biological complexity once we are clear about the type of complexity that is
actually at issue in biology. The problem, according to Roche, is that
design theorists are using the wrong notion of complexity. What is the right
notion? Roche claims Gell-Mann's concept of effective complexity is the
right one for biology.
But there is a problem with Gell-Mann's approach to complexity. While
Gell-Mann's approach is well-suited for describing how regularities of
nature that are subjected to random perturbations match our conceptual
schemata, it is not capable of handling contingencies in nature that are
unaccountable by any regularities but that happen all the same to match our
conceptual schemata. Such contingencies establish a design in nature that is
not reducible to nature. What are these contingencies that are unaccountable
by regularities but that nonetheless match our conceptual schemata? The
technical name for such contingencies is specified complexity.
Think of the signal that convinced the radio astronomers in the movie
Contact that they had found an extraterrestrial intelligence. The signal was
a long sequence of prime numbers. On account of its length the signal was
complex and could not be assimilated to any natural regularity. And yet on
account of its arithmetic properties it matched our conceptual schemata. The
signal was thus both complex and specified. What's more, the combination of
complexity and specification convincingly pointed those astronomers to an
extraterrestrial intelligence. Design theorists contend that specified
complexity is a reliable indicator of design, is instantiated in certain
(though by no means all) biological structures, and lies beyond the remit of
nature to generate it.
If the previous remarks about complexity, specification, and information
have seemed unduly elliptical, it is because this is a complicated subject
and the details can quickly become overwhelming, especially in so short a
talk as this. Nonetheless, I do want to give some sense of why specified
complexity is the right instrument for identifying nature's limitations. To
say that specified complexity lies beyond the remit of nature to generate it
is not to say that naturally occurring systems cannot exhibit specified
complexity or that natural processes cannot serve as a conduit for specified
complexity. Naturally occurring systems can exhibit specified complexity and
nature operating unassisted can take preexisting specified complexity and
shuffle it around. But that is not the point. The point is whether nature
can generate specified complexity in the sense of originating it when
previously there was none. Take, for instance, a[n Albrecht] Durer woodcut.
It arose by mechanically impressing an inked woodblock on paper. The Durer
woodcut exhibits specified complexity. But the mechanical application of ink
to paper via a woodblock does not account for that specified complexity in
the woodcut. The specified complexity in the woodcut must be referred back
to the specified complexity in the woodblock which in turn must be referred
back to the designing activity of Durer himself. Specified complexity's
causal chains end not with nature but with a designing intelligence.
To place the burden of design detection on specified complexity remains
controversial. The philosophy of science community, wedded as it is to a
Bayesian approach to probabilities, is still not convinced that my account
of specified complexity is even coherent. The Darwinian community, convinced
that the Darwinian mechanism can do all the design work in biology, regards
specified complexity as an unexpected vindication of Darwinism. On the other
hand, mathematicians and statisticians have tended to be more generous with
my work on specified complexity and to regard it as an interesting
contribution to the study of randomness. Perhaps the best reception of my
work has come from engineers and the defense industry looking for ways to
apply specified complexity to pattern matching. The final verdict is not in.
Indeed, the discussion has barely begun. In my forthcoming book titled No
Free Lunch I respond at length to my critics (including Wesley Elsberry).
Since I will presumably have some time to respond to Wesley's criticisms of
my work following his talk, I'll leave off further discussion of specified
complexity's merits.
3. Technological Evolution
I want next to focus on what insights into biological evolution a design
perspective offers. Here we are at a conference on interpreting evolution.
Suppose that specified complexity lies beyond the remit of natural causes to
generate it, and that specified complexity is a reliable empirical marker of
actual design, and that specified complexity is instantiated in actual
biological systems (huge suppositions for many of you). How then should we
interpret biological evolution?
Phillip Johnson has criticized Ohio State University zoologist Tim Berra for
likening Darwinian evolution to the technological evolution of the Corvette
automobile. Darwinian evolution is by definition undirected by any
intelligence whereas Corvette evolution is directed by an intelligence.
According to Johnson, there is a fundamental disanalogy between these two
types of evolution, and to use one to justify the other is invalid. Johnson
therefore refers to Berra's conflation of Darwinian evolution and
technological evolution as Berra's Blunder. I prefer instead to refer to it
as Berra's Freudian Slip. Berra was quite right to compare biological
evolution to technological evolution. Biological evolution is indeed a form
of technological evolution. Berra's mistake was in thinking that Darwinian
evolution is a form of technological evolution. It is not.
Darwinian evolution is a trial-and-error method for gradually improving
preexisting functions and for co-opting serendipitous functions. Within
Darwinian evolution natural selection supplies the trial and random
variation the error. Although trial and error plays a role in technological
evolution, trial and error is too myopic to serve as the powering force
behind technological evolution. The watchmaker behind technological
evolution needs to be far-seeing, not myopic and certainly not blind.
We now have extremely good information about the trends that technologies
follow in their evolution. Once designed systems are in place, operational,
and interacting (be they within an economy or ecosystem), technological
evolution tends to follow certain patterns. These patterns of evolution have
been extensively studied by Russian engineers and scientists, beginning
notably with the work of Genrich Altshuller. As Semyon Savransky remarks,
"Engineers in the former Soviet Union were responsible to spend eight hours
[a day] at their work place but often had nothing to do (their regular
salary did not depend on their effort, experience, or quantity and quality
of work). Many of them ... used this time to study patents."
Altshuller, an engineer, studied more than 400,000 patents from across the
world to uncover patterns in technological evolution. Another Russian
engineer, I. V. Vikent'ev, studied all USSR patents (about a million at the
time) looking for patterns in technological evolution. The systematic study
of patents by Russian engineers and scientists created a new discipline, now
known under the acronym T-R-I-Z. TRIZ corresponds to a Russian phrase that
in English means "Theory of Inventive Problem Solving." Although Russian
researchers have been actively investigating TRIZ for the last fifty years,
it has only made its mark in the West in the last decade. TRIZ as a
methodology for facilitating inventions and solving problems is increasingly
being employed in industry. On the other hand, its applications to biology
are only now becoming evident.
TRIZ is a vast topic, so in my few remaining minutes I will provide only the
barest sketch of this methodology as it relates to biology. TRIZ is
concerned with the improvement of existing designs and the emergence of
novel designs. I'll call the one intraspecific technological evolution, the
other transpecific technological evolution. Although intraspecific
technological evolution can proceed by trial and error (as in the Darwinian
mechanism), the trial-and-error method is only suitable, as TRIZ expert
Semyon Savransky observes, for "simple, well-defined, routine closed
problems." Problems are routine if all the critical steps leading to a
solution are known. On the other hand, a problem is nonroutine if at least
one critical step leading to a solution is unknown.
In response to environmental pressure (be it economic or ecological),
intraspecific technological evolution is frequently called on to solve
nonroutine problems. Environmental pressure pushes designed systems toward
what TRIZ proponents call "ideality." A system is said to approach ideality
to the degree that it maximizes the system's useful functions and minimizes
its harmful functions. In the Marxist spirit in which TRIZ was invented,
TRIZ seeks to overcome the contradictions that arise when improving one
function of a system leads to deficits in another function of the system.
TRIZ seeks to resolve these contradictions not so much by balancing
advantages against disadvantages, as in constrained optimization, but by
novel win-win solutions that maximize useful functions without (ideally)
incurring harmful side-effects. The great obstacle in the way of ideality is
psychological inertia, which artificially constricts a solution space rather
than opening it to undreamt of possibilities. Psychological inertia thinks,
as it were, inside a box. Ideality requires thinking outside the box.
TRIZ characterizes ideality in the following Zen-like terms (I quote from
Savransky):
* The ideal machine has no mass or volume but accomplishes the
required work.
* The ideal method expends no energy or time but obtains the necessary
effect in a self-regulating manner.
* The ideal process is actually only the process result without the
process itself.
* The ideal substance is actually no substance (a vacuum), but whose
function is performed.
* The ideal technique occupies no space, has no weight, requires no
labor or maintenance, delivers benefit without harm, and "does it itself,"
without any additional energy, mechanisms, cost, or raw materials.
This Zen-like dwindling of a system's substantiality to nothing while its
function progresses to perfection is to be sure an idealization that cannot
be realized in any concrete physical system. Nonetheless, this idealization
serves as a useful regulative principle for designed systems. Certainly,
ideality's best instantiation is found in biology (according to Genrich
Altshuller, biology has given us the best of all patent libraries). Among
human artifacts ideality's best instantiation is perhaps found in computers.
Whether Moore's law will continue to obtain and push computers closer to
ideality than biological systems (especially in regard to the human brain)
is very much a matter of debate at this time.
According to TRIZ, intraspecific evolution gives way to transpecific
evolution when a given technology has been pushed as close to ideality as
possible and when new pressures from the environment require new
technologies with new functions. When novel technological systems emerge, as
far as possible they take advantage of and incorporate preexisting
technologies. What's more, novel systems tend to emerge suddenly. Once a
novel system has emerged, the pressure is on to achieve ideality. A system
that approximates ideality will persist for long stretches of time provided
its environmental niche is undisturbed. Stasis is therefore part of TRIZ's
evolutionary scheme. But so is extinction: When environmental pressures
become too great, antiquated systems either give way to novel systems or
simply disappear without any system taking their place. Unlike emergence,
which is sudden, extinction can be sudden or gradual (thus a new technology
may gradually displace an old one or eliminate it all at once). Finally,
good ideas get reused and reinvented. Technological evolution therefore
includes convergent evolution. Moreover, it readily accommodates homologies
(similar structures used for different purposes) as well as analogies
(different structures used for similar purposes).
Sudden innovation, convergence to ideality, and extinction are all part of
TRIZ's evolutionary scheme. Now where have we seen that scheme before? The
scheme is non-Darwinian. Nor can the Darwinian scheme be easily modified to
accommodate it. For instance, Robert Wright's addition of game theory to
selection and variation is insufficient to account for technological
innovation -- at best game-theoretic constraints provide a necessary
condition for technological innovation. TRIZ's evolutionary scheme fits
quite nicely with Eldredge and Gould's model of punctuated equilibria.
Leaving aside their model's mechanism of evolutionary change and innovation,
the patterns of evolution described by TRIZ and the Eldredge-Gould model are
quite similar.
Perhaps the one discrepancy is that the Eldredge-Gould model does not make
explicit the convergence to ideality. From the vantage of technological
evolution, the speed of convergence to ideality reflects the perspicacity of
the designing intelligence responsible for technological improvement. In the
limiting case, therefore, a designing intelligence produces technological
systems that are as close to ideality as possible from the start. Although
suboptimality of design remains an issue in biological evolution, aspects of
biological designs seem indeed to approach ideality. For instance, the
miniaturization of molecular machines in the cell seems to approach the
physico-chemical limits of matter.
In conclusion, Aristotle's distinction between nature and art remains very
much a live issue for the natural sciences. In particular, at the heart of
the current debate over intelligent design is whether biological systems
exhibit some feature that cannot be ascribed to nature as such but in
addition requires art or design to complete what, as Aristotle put it,
"nature cannot bring to a finish." Moreover, if design theorists are correct
in arguing that specified complexity lies beyond the remit of natural causes
to generate it, that specified complexity is a reliable empirical marker of
actual design, and that specified complexity is instantiated in actual
biological systems; then the way is open for a massive reinterpretation of
biological evolution. In that case, biological evolution becomes a form of
technological evolution. What's more, thanks to TRIZ, a ready-made theory of
technological evolution is already in place to interpret biological
evolution. Biology confirms the patterns of technological evolution outlined
by TRIZ. Significantly, these patterns are non-Darwinian.
=========Reference Notes========
The quotes from Aristotle are taken from Jonathan Barnes, ed., The Complete
Works of Aristotle (Princeton: Princeton University Press, 1984). For
Internet information on TRIZ, start with www.triz.org <http://www.triz.org/>
and www.triz-journal.com <http://www.triz-journal.com/> . The citations to
Savransky and Altshuller are taken respectively from Semyon Savransky,
Engineering of Creativity: Introduction to TRIZ Methodology of Inventive
Problem Solving (Boca Raton, Fl.: CRC Press, 2000) and Genrich Altshuller,
The Innovation Algorithm : TRIZ, Systematic Innovation and Technical
Creativity (Worcester, Mass.: Technical Innovation Center, 1999).
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