|
Scientists strive to understand nature,
engineers to transform nature for serving people. They complement
each other, for to transform nature effectively requires proper
understanding, and to discover nature’s secrets requires instruments
to modify it in experiments. Because they both address nature, they
share many knowledge and methods, although often with different
emphases.
Like science, engineering engages in analysis
and synthesis. But whereas scientists tend to break matter down to
its most basic building blocks, engineers ultimately aim to assemble
myriad components into a complex system. Because the components are
heterogeneous, engineers must integrate knowledge in many areas, and
multidisciplinary teamwork is common practice. Like science,
engineering covers both the general and the particular. But whereas
scientists tend to design particular experiments for discovering
general laws of nature, engineers tend to formulate general
principles for designing particular artifacts. Modern engineering
has developed general theories about large types of artificial
systems, notably information, control, and computation theories.
These engineering theories are most effective for designing concrete
artifacts, yet their abstract theorem-proof format is closer to pure
mathematics than the format of physical theories, which are closer
to applied mathematics. The apparent paradox accentuates the
engineering emphasis on creating things rather than discovering
phenomena already existent.
Unlike scientists, who can defer unsolved
mysteries to future advancement of knowledge, engineers, who must
deliver products on time, often have to make design decisions with
incomplete knowledge. Thus engineering has developed more
sophisticated ways to address uncertainties. Unlike science,
engineering has explicit utilitarian missions. To reckon with
utility, the contents of engineering incorporate many purposive
concepts – function, performance, optimality, control, trade-off –
that are absent in the contents of physical science. Unlike
science, whose product is mainly knowledge, the most prominent
products of engineering are things and infrastructures that permeate
the fabric of modern life. Engineers are involved in the whole life
cycle of technological products, from conception and design through
manufacturing and maintenance to final disposal. Their jobs demand
them to look beyond things to people and society. Besides designing
products, they also manage workers and organize productive
activities. Besides finding efficient means for given ends, they
also analyze ends to find out what people require of their products.
Incommensurability versus
complementarity
Talking her in Copenhagen, two of its favorite
sons concerned about the human condition readily jump to mind:
- Soren
Kierkegaard: Enten-Eller (Either/Or)
- Niels Bohr.
Complementarity
Kierkegaard and Bohn both rejected the Hegelian
ambition to an absolute framework that encompasses all there is to
know. Yet they responded in quite different ways. I am in no
position to expound these profound philosophies, but merely want to
borrow some of their ideas as inspirational perspectives.
In the mid nineteenth century Kierkegaard
advanced a philosophy that would be quite familiar in today’s
science and technology studies. Its gist is absolute disjunction,
either/or, quite similar to Thomas Kuhn’s notion of
incommensurability in the philosophy of science. It is either
technological determinism or sociological determinism.
Technology is either applied science or social
construction. Science is either a simple input from nature
or devoid of reality. The paradigms are polar and
incommensurate, to go from one to the other one must take a “leap of
faith,” to use Kierkegaard’s words, or undergo a religious
conversion, as Kuhn put it. This radical relativism leads to
Culture Wars and Science Wars. But I will not get engaged in them.
Instead, I will adopt the perspective of Bohr’s
complementarity, which opts for both instead of either/or.
To encompass a complementary dual for a more comprehensive worldview
is not a holism in which the two sides fuse into one. To use Bohr’s
prime example of quantum mechanics, two representations, position
and momentum, are distinctly defined. Our human condition limits us
to adopt only one representation in each particular observation, but
we know that we need the complementary representation for a more
comprehensive understanding of the quantum world. Furthermore, it
is not required that the two representations can be transformed into
each other according to some prescribed absolute criteria.
Uncertainty is central and intrinsic to complementarity. Under this
philosophy of striving for a broad worldview in the face of
uncertainty and incompleteness, I will explore technology as human
knowledge.
Technological knowledge resides mostly in the
disciplines of engineering and natural science. I will focus on
engineering. It is most responsible for the design and production
of technological goods and services, which most people identify with
technology itself. Also, engineering, especially modern
science-intensive engineering, is a much neglected area in science
and technology studies. I will explore several complementary duals
in engineering knowledge:
- Its drive for scientific foundation and
its heritage as practical arts.
- The nature that engineers modify and the
people that the modifications serve.
- Knowledge and uncertainty.
- Motivations of wonder and utility.
- Contents and contexts.
Social contexts of technology have attracted
many scholarly works, even to the extent of crowding out science and
engineering. When technical contents are discarded, “contextual”
discussions of technology become Hamlet without the Prince of
Denmark.
Complementarity of people and things
The main goal of engineering is to transform
nature to serve the needs and wants of large numbers of people.
This goal at once reveals its two complementary dimensions. It has
a physical dimension that calls for sophisticated knowledge about
nature and things, so that engineers can modify them effectively for
desirable products. To find out what products are desirable, and to
organize large numbers of workers to produce the goods and services
efficiently, however, requires knowledge about people, and this
brings in the human dimension of engineering. The two dimensions of
engineering are expressed in what I briefly call physical technology
and organizational technology.
The two kinds of technology can again be
divided into three major kinds of activities:
- Engineering science for research
into general principles of what can be useful.
- Design for developing particular
products and production processes.
- Management for exploring ends and
means, planning, and organizing workers.
The three aspects, engineering science, design,
and management overlap considerably with each other. The majority
of engineers engage in design. However, as a profession, design
cannot work without significant input from science and management.
It is through management that engineering is most tightly connected
to the economy, society, and policy
The duality of engineering’s physical and human
dimensions confounds a stereotype. Surveying the portraits of
engineers the historiography literature, B. Sinclair found: “Instead
of the portrait of a profession, what we have is a grab bag of
stereotypical images and they picture a group that seems politically
inflexible, socially awkward, culturally limited, and ethically
inert.” Engineers are often stereotyped as nerds or geeks,
technically proficient but socially inept, as if technical and
social skills are incommensurate, so that one can only be good with
either things or people. In fact one can be good with
both, or neither. As a profession, engineering must be good in both
to do its jobs well. Not all engineers are individually good in
both, but enough number of them are to refute the stereotype. This
can be seen in their success in management, both tactical and
strategic.
Tactical managers organize production lines,
factory floors, and supply chains. Henry Ford, an engineer, was a
superb and pioneering tactical manager. Scholars have paid much
attention to engineers’ role in tactical management, although they
often underplay the people skills involved. Moreover, they have
almost totally ignored the role of engineers in strategic or
corporate management.
Strategic managers design corporate
architectures, steer the corporation toward long and short term
goals, allocate human and other resources, coordinate production,
finance, marketing, and other branches of operation. For them,
adequate people skills and contextual vision are indispensable.
Engineers have been outstanding as strategic managers and top
executives. Ever since large corporations appeared, engineers have
been successful on corporate ladders that, crowded with aggressive
graduates from business and law schools, are killing grounds for the
socially handicapped. From mid century to now, some 20 – 30 % of
chief executive officers in large US firms have engineering
background. And for each who reaches the very top, many others make
senior management. The significance presence of engineers and
scientists at high corporate level illustrates the importance of the
practical integration of technological, economical, and other
factors in competitive business operations, in other words, the
complementarity of physical and organizational technologies.
Complementary of contents and
contexts
A major job in strategic management of
technological enterprise is to bring together the providers and
consumers of technology, to interlace technical contents and social
contexts. For such jobs, and many others, familiarity with both
sides gives a definite edge.
To develop a technological system require more
than technical knowledge about the system’s internal structures.
The first and most important step in the development project is to
find out the purposes of the system to be designed. What is the
system intended for? What functions is it to serve? What
performances are required of it? To answer them requires much
knowledge about the economical, social, and environmental contexts
of the intended system. Engineers must work closely with their
clients and people who have a stake in it, alert them to side
effects and environmental constraints, and help them to clarify
their priorities and define achievable goals. The job is so
important it has a special name – requirements engineering. It is
often a most difficult task, especially for software, because many
large software systems are novel, complex, and have endless
variations. Frederick Brooks, chief engineer for developing the IBM
360 operating system, remarked:
“The hardest single
part of building a software system is deciding precisely what to
build. . . . No other part of the work so cripples the resulting
system if done wrong. No other part is as difficult to rectify
later.”
Botched requirements account for many abandoned
or useless software systems. A high profile example is the air
traffic control system commissioned by U.S. Federal Aviation Agency,
which was abandoned after wasting more than a billion dollars. Many
military and big science projects suffer heavy cost overrun because
their requirements are unrealistic.
Requirements engineering aims to develop a
system that works in the real world. Therefore it insists on
practicality. Ideologues can talk pretty, but choices made in the
real world are sometimes ugly. Many decisions ultimately rest on
consumers or society at large. Yet engineers can help the clients
to make rational choices under realistic constraints. They study
relevant contextual factors: legal issues, safety regulations,
environmental policies, cultural acceptance, and other social
constraints. They explore various options available under exiting
technology and scientific knowledge, and consider whether the
options are achievable given the available resources. Often
resource limitations force the clients to cut back on their
expectations, and engineers propose trade-off for the clients to
choose. Negotiations go back and forth many times, until a set of
functional requirements is drafted. Then the engineers began in
earnest to define the technical contents of a system whose
performance can satisfy the requirements. Nothing exemplifies the
complementarity of contents and contexts more than requirements
engineering.
Complementary of structures and
functions
Now let us turn to the two more familiar
aspects of engineering, science and design. Engineering research
shifted into high gears after WWII. One result is the
crystallization of several bodies of systematic and empirically
tested knowledge, or several engineering sciences. Through them
engineering is closely linked to the natural sciences, mostly
physics, but increasingly chemistry and biology.
A natural science, such as atomic physics,
takes as its topic a broad type of natural phenomena and explores
what can be under the relevant physical laws. An engineering
science is defined similarly, but instead of natural phenomena, it
addresses a broad type of artificial phenomena, which is often
defined by not physical properties but functional
properties. It explores that can be of use.
Engineering sciences fall roughly into two
groups, physical and systems. Respectively addressing structures
and functions, they complement each in the design of technological
systems.
1. Physical theories: Examples are
mechanics, electromagnetism, thermodynamics, fluid dynamics, and
transport phenomena, which are application to many engineering
branches. They are applied physics, but not in the pejorative sense
of “applied science” popular in technology studies. Engineers
developed the physics laws relevant to a wide class of useful
systems, introduce theoretical concepts to represent peculiarities
of artificial systems, and discover general practical operating
principles. They contributed much to the development of
thermodynamics, fluid dynamics, aerodynamics, and other physical
theories. Thermodynamics originated in studying the performance of
steam engines and other heat-utilizing devices. Its practical
heritage is apparent in physics textbooks, which discuss heat pumps
and the Carnot cycle – Carnot was an engineer. One formulation of
the second law of thermodynamics itself is the impossibility of
perpetual motion machines.
2. Systems theories: Examples are
control theory, information theory, computation theory, theories for
estimation and signal processing. Most systems theories are
indigenous to engineering. In contrast to physical theories, they
abstract from physical properties and focus on the
functional properties of systems. A thing’s function is its
behavior that impacts on a larger context or the service it renders
an external community. Function is a purposive concept that seldom
appears in the physical science. It is central to engineering
because the purpose of an engineered system is to provide services.
Engineers are responsible to design the structure of the system so
that it performs those services satisfactorily. Complementarity of
internal structures and external functions are crucial to them.
Consider for example trains powered by steam
engines. For a train to travel with a steady speed, its engine must
work harder when it climbs an incline than when it travels on
leveled ground. To achieve this James Watt invented the flyball
governor to regulate the operation of the steam engine. The
physical structure of the governor utilizes the centrifugal
force of a pair of fly balls to move the valve that controls steam
input into the engine. However, engineers also abstract from these
specific physical characteristics to examine the governor’s general
function of controlling the engine so that its load – the
train – operates at a steady pace. This functional analysis is the
job of control theory. Control theorists discover the principle of
feedback control underlying the flyball governor, a principle
applicable to maintaining steady operations for a wide variety of
physical systems. General knowledge about feedback control enables
engineers to invent new controllers with other physical structures
that are effective in other physical situations, for instance the
electronic cruise control that keeps your car moving steadily at 100
kilometers per hour on an undulating road.
Complementarity of the general and
the particular
Theories in both engineering and natural
sciences usually offer general principles and frameworks, often
mathematical and rather abstract. On the other hand, an engineering
design or a scientific experiment is always a particular
undertaking, replete with its peculiar concrete details. Relations
between theory and experiment, or between science and design, are
also the relations between the general and the particular.
General principles sacrifice details for
covering large scopes. Particular descriptions sacrifice scope for
accounting details. How to connect the general and the particular
is always a difficult problem. A manifestation of this difficulty
is the tension between the philosophy and sociology of science and
technology. Unable to connect the general and the particular,
scholars opt for either macro philosophizing or micro
sociological portraits. Their bitter debates sound as if the two
views are incommensurate. In contrast, the success of natural
sciences and engineering lies in the complementarity of the general
and the particular.
The power of a science can be measured by how
rigorously it ties together general principles and particular
instances. The physical sciences and engineering are powerful in
this sense. The connection usually involve several steps, each step
narrows the scope by specifying more details. For example, Newton’s
laws of motion provide general principles of all motion. They
leaves out the form of the motion-generating force, for example the
gravitational force, the inverse square law of which Newton
introduced separately from the laws of motion. The force can be
electromagnetic, which will lead to a separate range of phenomena.
Within gravity, a narrow scope focuses on the solar system, and a
particular instance of the solar system was the return in 1705 of
the comet previously known as the Spirit of Caesar or the Wrath of
God. Similar hierarchies of generality are found in engineering
science. For instance, Claude Shannon’s information theory lays out
the general bounds for reliable communication. A systems theory
that focuses on communicative functions, it leaves out the physical
media of communication, which can use copper wires, optical fibers,
or wireless, propagation in free space. A narrower scope is the
study of optical communication through glass fibers. A still narrow
scope is the OC1 system of optical communication, which can carry
672 simultaneous telephone conversations in a single strand of glass
fiber the width of a human hair. An instance of it was the first
system rolled out in Chicago in 1977. The intermediate steps are
important, because they ensure that the justifications for
generalization can be clearly stated and criticized.
The ability to proceed from general principles
to particular instances underlies the ability to predict and
explain. This is not easy. For instance, Charles Darwin introduced
broad principles on evolution: descent by modification and natural
selection. They are powerful but not powerful enough to predict or
even explain satisfactorily the emergence of specific species.
Predictions require not only deduction from principles; they require
additional input about specific conditions relevant to the instance
at issue. Knowledge about appropriate conditions is usually
complicated and requires much research to ascertain.
Galileo gave a simple example. He
distinguished between “machine in the abstract” and “machine in the
concrete.” The principle of lever, a basic principle for
constructions, had been known since Archimedes. This, Galileo said,
was only machine in the abstract. Archimedes could boast that he
could raise the earth given a pivot only because he had ignored the
kind of lever required for the job – any realistic level would
break. For machines in the concrete, the abstract lever principle
must be supplemented by conditions such as the lever’s strength and
bending under load, which would vary according to its particular
material and structure. To acquire systematic knowledge about these
conditions took almost two centuries before engineers confidently
build long bridges and tall buildings that bear heavy loads.
Complementarity of analysis and
synthesis
The debate between holism and reductionism is a
familiar topic in science and technology studies. In the extreme
positions, radical reductionists insist that a whole is nothing
but its parts, if you know the parts, then you know all there is
to know. Radical holists insist that a whole is a whole that is
destroyed by any attempt at analysis. The anti-analysis position is
captured in the “seamless web” metaphor; a seamless web allows no
parts, because it unravels at the tiniest loose ends. “Seamless
web” and “nothing but parts” are incommensurate; you must stay at
either the top or the bottom.
A far more productive approach is to regard the
whole and the parts as complementary and investigate the connections
between them. Socrates adopted the method of division and
collection, Galileo, of resolution and composition. Descartes and
Newton talked about analysis and synthesis. Engineers practice
functional decomposition and physical integration in systems design.
A long list of scientific successes, from
subatomic physics to molecular biology, testifies to the power of
analysis, in which scientists seek the basic constituents of complex
systems. This is partly because the properties and interactions of
the basic constituents often turn out to be the fundamental
principles underlying the properties of larger systems that they
make up. Nevertheless, radical reductionists who jump to the
conclusion that large system are nothing but their constituents have
overlook the equally prevalent phenomenon that scientists seldom if
ever stop at the constituents. As soon as they figure out the
behaviors and interactions of the constituents, they turn around to
investigate how the constituents make up infinite variety of
compounds. They turn from analysis to synthesis, which is often a
turn from general principles to particular instantiations of the
principles. Thus atomic physics explores the structures of atoms as
wholes composed of nuclei and electrons. More recently, as soon as
molecular biologists decipher the detail structures of genes, they
turn to genomics for answers about how genes and their interactions
contribute to the physiology of organisms. Analysis is not
reductionism. It decomposes a whole into parts, but does not assert
that the parts are all. Scientists realize that to understand
anything of complexity, one must pull it apart, study its details in
depth, and then put it together again. Thus synthesis complements
analysis.
The major aim of engineering is to design and
build particular systems, which are wholes comprising many parts.
Engineers depend on analysis-synthesis as much as scientists, but
perhaps with different emphases. Just as scientists tend to
emphasize general principles and engineers particular designs, the
former lean toward analysis and the latter synthesis.
Natural scientists often analyze existing
phenomena replete with concrete details. Engineers differ from
natural scientists in that they primarily aim not to understand
existing phenomena but to create systems that do not yet exist.
Therefore they start with an abstract conception of the whole
system, for example, the idea of a fuel-efficient airplane. The
conception is centered on a set of functional requirements: what the
intended airplane is supposed to do, what service it is to perform.
Then they analyze the conceptual airplane into subsystems, often
along functional instead of physical lines, for instance, the
subsystems of the airplane for propulsion, lift, and payload,
which are to be physically realized as the engine, wing, fuselage.
In the functional decomposition, it is most important to specify how
the subsystems will work together, what life and propulsion would
support the required payload. When engineers have a reasonable
conception of a subsystem, for example a jet engine, they then
decompose it further into smaller subsystems, until they arrive at
parts simple enough to be specified to the last detail. These small
parts are then manufactured according to specification, tested,
assembled into subsystems, and so on, until finally an airplane is
ready for test flight. This round trip from the whole to the parts
and back, from the top to the bottom and back, consists many smaller
round trips of analysis, design, synthesis, testing, feedback.
Analysis and synthesis complement each other on many levels.
Complementarity of science and art
Art and science are sometimes regarded as
incommensurate paradigms. However, the two are not diametrically
opposite, neither are they mutually exclusive. Being scientific
implies being rational, critical, and systematic. In this sense,
art, in contradistinction to arbitrariness or mechanical routine, is
scientific to some degree. Aristotle remarked that téchnē
(art) has its intrinsic logos (reasoning), and it is the
possession of true reasoning that distinguishes art from mere
experience or blind cut-and-try. Perhaps at Aristotle’s time and
long after, the reasoning in the state of art fell short of the
clarity, criticality, and systematicity of modern science.
Practical arts in construction and machinery contained many
principles, rules of thumb, and facets of scientific knowledge. But
these were either too weak or too limited to deal with the
complexity of real world conditions, so that practitioners relied
mainly on intuition and trial and error. Nevertheless, over the
past century they have so advanced their reasoning that modern
engineering is largely scientific.
Science generally means possessing knowledge
that is sufficiently general, clearly conceptualized, carefully
reasoned, systematically organized, critically examined, and
empirically tested. However, because scientific knowledge is
limited by human understanding, which is finite, it has no claim to
exhaustiveness and absolute certainty. Much remains unknown in
science and engineering. Much knowledge remains intuitive; in other
words, much remains an art. Modern engineering has developed many
engineering sciences, but it has not outgrown its practical arts
root. It never will, for art and intuition knowledge is
continuously being generated in life and work.
Scientific knowledge is mostly explicitly
articulated and clearly represented. However, much knowledge in
engineering and technology is not explicit but tacit, not written
out but embodied in:
- human capital: human skills, experiences,
understanding, practices
- social capital: work organizations and
institutional structures
- physical capital: plans and operations of
machines and plants
Explicit knowledge can be quickly disseminated
because it is clearly explained and easily taught. Implicit
knowledge cannot. Experience cannot be taught; it can only be
patiently acquired through practice and accumulated over time.
Tacit knowledge is the most valuable asset of technologically
advanced nations, their greatest comparative advantage over
catcher-ups. The transmission of tacit knowledge in “technology
transfer” depends heavily on the travel or migration of technical
experts and managers, and the moving or building of physical plants.
Explicit knowledge can be subject to rigorous
arguments and tests. Tacit knowledge is much less susceptible to
critical examination, and hence to improvement. There is a
continuous effort to make tacit technological knowledge explicit, to
make art more scientific. It runs simultaneously with efforts to
produce more sources of tacit knowledge through education and social
and industrial development. The cycle drives the technological
progress.
Take for example the technologies of
large-scale manufacturing of cars. As is well known, mass
manufacturing, which capitalized on the economy of scale, was the
leading technology that made Detroit the car capital of the world.
Then beginning in the 1960s, the Japanese, especially Toyota Motors,
developed a better technology, which the Americans call “lean
production.” In mass production, assembly lines and their parts
suppliers pump out as many pieces as fast as possible. In contrast,
the “just-in-time” supply chain of lean producers strives to produce
just the right things at the right time. In mass production,
assembly lines spit out cars of various qualities and leave it to
quality controllers to weed out the defective ones. In contrast,
the “total quality control” of lean producers stops the assembly
line any time a worker spots a defect, so that defects are nipped at
the tip. Total quality control and just-in-time production are
difficult technologies, because they involve not only one factory
but the entire automobile industry with thousands of suppliers in
many nations. Toyota took decades to develop it. It was so
successful that in the 1980s Americans were panicky about being
overwhelmed by the Japanese. Industry and academia teamed up to
respond to the challenge; MIT, for instance, initiated a big
program. Engineers have ferreted out many principles underlying
lean production practices. Books are written and seminars held.
Thus tacit knowledge originated in industrial practice is made
partially explicit. However, much of it remains tacit and
embedded. Tried as they did to copy lean production practices,
American manufacturers have so far fallen behind Toyota in
efficiency. The science of lean production is shared, but the
Japanese are superior in the art. Even so, decades of competition
advanced the technology of automobile manufacturing in both
countries.
Complementarity of knowledge
and uncertainty
Explicit and tacit, our knowledge of the world
is far from complete. As Einstein remarked, certainty is
unattainable in natural science, not to mention in daily life.
However, postmodernists are wrong to jump from the lack of
absolutely certain knowledge to the dogma that science is nothing
but politics, in which anything goes.
Scientists and engineers are doers, not empty
talkers; bold, but not reckless. They are aware of desirable
ideals, but they are also realistic about what they can achieve. It
is well to be able to know everything all at once, exactly, and with
certitude. But that goal is unrealistic. The success of science
and technology depends partly on the patience to take one step at a
time and bite off what one can chew. One common practice is to
idealize closed system in an open universe, as in controlled
experiments and limited models. Scientists and engineers make
approximations and acknowledge the approximations by estimating
errors and introducing corrective steps whenever possible.
Engineers design products that will be used by
real people in the real world. Safety and reliability are
paramount. When engineers are uncertain, they prefer to err on the
safe side and use tried methods. Bold designs may be exciting and
glamorous, but their risks of failure are also greater, and at stake
are lives and properties. “When in doubt, be stout” is a dictum I
heard in the first lecture of two separate freshman engineering
courses. For this engineers are often stereotyped as conservative,
dull, and unimaginative. The stereotype is unfair. Engineers are
conservative, but not from lack of imagination but from their sense
of responsibility.
At the frontier of research, scientists always
face the unknown. When they are unable to solve a problem, they
leave it to future research. Newton did not like the idea of
gravity acting at a distance. He calmly said that he did not know
the cause of gravity and left it to future generations. Three
centuries passed before Einstein filled the gap in Newton’s
knowledge.
Waiting is a luxury engineers can ill afford;
they have to deliver products in time. The practicality of their
mission is a heavy burden that forces them to make decisions and
take actions, even in the face of incomplete knowledge and
uncertainty. Here is where critical rationality, the sense of
responsibility, and the effort to seek alternatives become most
important. Hard choices under practical constraints are often
unpleasant and ugly. Ideologues demand perfection and absolute
safety; they can talk pretty because they do not bear responsibility
for their grandiloquent. Engineers ask “How safe is safe? How much
are you willing to pay for additional safety?” Ideologues denounce
engineering trade-offs as crass and vulgar, but what practical
alternatives have they offered? To avoid hard choices is a choice,
an easy but often most irresponsible one.
Science and technology have brought an enormous
amount of knowledge, explicit and tacit. They have also shown how
much we do not know. This complementarity is captured in Confucius’
remark: “To know what one knows, to acknowledge what one doesn’t
know, that’s knowledge.”
Talk presented in the Conference on the Philosophy of Technology,
Copenhagen.
October 13, 2005.
by Sunny Y. Auyang
|
