= one of the main points of the lecture |
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Some
Reference Points for Discussion
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Preliminary Class Business
- Online demo
of reading quizz
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From Literacy to Information Literacy
- Previous classes have covered the prehistory of information
and the early historical "information revolutions":
orality, literacy, print
- From now on we'll bring the story up to date by looking specifically
at the modern and postmodern history of information—i.e.,
electronic, digital, and networked information from the mid
20th century to the present.
- In particular, we'll be focusing on the following succession
of fundamental paradigms of contemporary information: "communication,"
"media," "computing," "networking":
20th-Century Paradigms
of Information
| Paradigm |
Signature Technologies |
Logical Architecture |
Peak Epoch (Period
of Monopolistic or Cartel Dominance) |
| Information
as Communication |
Telecom, Radio, Cryptography |
Transmission Model |
1940s-70s
(ATT breakup in 1984) |
| Information
as Mass Media |
Radio, TV, Magazines |
Broadcast Model |
1950s-1970s |
| Information
as Mainframe Computing |
Mainframes and Minicomputers,
Databases |
Centralized information services |
| Information
as Networking |
PC's, Networks, Hypertext, Graphical
User Interface (GUI) |
Client/Server Architecture |
1980s-2000s |
- These are not just technical paradigms but cultural paradigms.
- Analogy: During the era when what C.P.
Snow termed the "two cultures" of humanistic
and scientific knowledge diverged, Science and Technology
became not just a method but a cultural paradigm (e.g.,
as in the concepts of relativity, psychoanalysis, structural
linguistics). The power of the scientific method, indeed,
was in large part measured by its generalization to other
domains of social life, art, etc.
- "Information" is now the inheritor of the enormous
cultural prestige of Science and Technology. Information
is the technological paradigm that now claims a general
cultural relevance. (Cf., our earlier
discussion of the way information "represents"
postindustrialism symbolically)
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Claude Shannon's "Mathematical Theory of
Communication" (1948):
Some Main Principles
- A close reading of the first sentence
of the essay:
| "The recent development
of various methods of modulation such as PCM
and PPM which exchange bandwidth for
signal-to-noise ratio has intensified the interest in
a general theory of communication." |
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Principle of the Digital:
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Principle of Generality:
- Underlying Issues:
- The Digital and the General. An important question
that underlies our current notion of information: what is
the relation between the digital and the general?
- The "reductiveness" of the digital:
Information theory and the transmission
model of communication have sometimes been called "reductive";
and, in fact, the "digital"
as opposed to continuous analog models of signal transmission
that fostered Shannon's theory are technically reductive
(source information is sampled in steps or intervals).
Humanists have long been accustomed to treating "reductive"
as a bad word. Yet Marvin
Minsky has said that humanity has barely begun to
understand the full richness and potential of reductive
thought (the kind of thought that breaks complex problems
down into discrete particles [instructor's paraphrase
of Minsky's denunciation of the humanities at a talk at
UCLA]). What have humanists missed about the possibilities
of reductiveness?
The "bottom-up" rather than "top-down"
mode of explanation in modern science: complexity arises
from the interaction of atomistic bits, not from a deity,
metaphysical principle, or master program
- The digital provides a common medium of equivalence
between objects and phenomena: transcoding versus analog
mapping
- Why Generality? Why is generality important in the
information age?
- A close reading of the second paragraph
of Shannon's essay:
| "The fundamental problem
of communication is that of reproducing at one point either
exactly or approximately a message selected at another
point. Frequently the messages have meaning; that is they
refer to or are correlated according to some system with
certain physical or conceptual entities. These semantic
aspects of communication are irrelevant to the engineering
problem. The significant aspect is that the actual message
is one selected from a set of possible messages. The system
must be designed to operate for each possible selection,
not just the one which will actually be chosen since this
is unknown at the time of design." |
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Information as Entropy (and Noise):
- Information is not the same as meaning: "semantic
aspects of communication are irrelevant"
- Information is instead a mathematical quantity related
to the number of possible states of a message (to the probability
set from which a message is selected). Example: flipping
a coin vs. drawing a card.
- The more uncertain a message is (because it is being selected
from a larger probability set), the more information it
contains. Therefore: information is related to "entropy,"
the most general phenomenon in the universe: Weaver's explanation
of the link between "information" and "entropy":
pp. 103, 177
- Indeed, information is so general in its relation to entropy
that even "noise" seems to be information: Weaver,
pp. 108-109.
- So what prevents the concept of "information"
from thus becoming too general, so that even noise
is information?
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The "Transmission," "Conduit," or "Transport"
Model of Information:
| Shannon: "By a communication system we will mean
a system of the type indicated schematically in Fig. 1.
It consists of essentially five parts:
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- Point-to-point model of information transmission (restriction
of the channels, roles, and relations of information)
- Quarantining of "noise" from "information"
(Weaver, pp. 108-109)
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| (Continued
in next lecture) |
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Excerpts from Warren Weaver, "Recent Contributions
to the Mathematical Theory of Communication" (1949) (citation)
The word communication will be
used here in a very broad sense to include all of the procedures
by which one mind may affect another. This, of course, involves
not only written and oral speech, but also music, the pictorial
arts, the theatre, the ballet, and in fact all human behavior.
In some connections it may be desirable to use a still broader
definition of communication, namely, one which would include the
procedures by means of which one mechanism (say automatic equipment
to track an airplane and to compute its probable future positions)
affects another mechanism (say a guided missle chasing this airplane).
(p. 95)
The
word information, in this theory, is used in a special
sense that must not be confused with its ordinary usage. In particular,
information must not be confused with meaning.
In fact, two messages,
one of which is heavily loaded with meaning and the other of which
is pure nonsense, can be exactly equivalent, from the present
viewpoint, as regards information. (p. 99)
The quantity which uniquely meets the
natural requirements that one sets up for "information"
turns out to be exactly that which is known in thermodynamics
as entropy. [ . . . ] Thus when one
meets the concept of entropy in communication theory, he has a
right to be rather excited—a right to suspect that one has
hold of something that may turn out to be basic and important.
That information be measured by entropy is, after all, natural
when we remember that information, in communication theory, is
associated with the amount of freedom of choice we have in constructing
messages. Thus for a communication source one can say, just as
he would also say it of a thermodynamic ensemble, "This situation
is highly organized, it is not characterized by a large degree
of randomness or of choice—that is to say, the information
(or the entropy) is low." p. 103)
Remember that the entropy (or information)
associated with the process which generates messages or signals
is determined by the statistical character of the process—by
the various probabilities for arriving at message situations and
for choosing, when in those situations the next symbols. The statistical
nature of messages is entirely determined by the character
of the source. But the statistical character of the signal
as actually transmitted by a channel, and hence the entropy in
the channel, is determined both by what one attempts to feed into
the channel and by the capabilities of the channel to handle different
signal situations. [ . . . ] The best transmitter,
in fact, is that which codes the message in such a way that the
signal has just those optimum statistical characteristics which
are best suited to the channel to be used—which in fact maximize
the signal (or one may say, the channel) entropy and make it equal
to the capacity C of the channel. p. 108)
How does noise affect information?
Information is, we must steadily remember, a measure of one's
freedom of choice in selecting a message. The greater this freedom
of choice, and hence the greater the information, the greater
is the uncertainty that the message actually selected is some
particular one. Thus greater freedom of choice, greater uncertainty,
greater information go hand in hand.
If noise is introduced,
then the received message contains certain distortions, certain
errors, certain extraneous material, that would certainly lead
one to say that the received message exhibits, because of the
effects of noise, an increased uncertainty. But if the uncertainty
is increased, the information is increased, and this sounds as
though the noise were beneficial!
[ . . . ]
It is thus clear where the joker is in saying that the received
signal has more information. Some of this information is spurious
and undesirable and has been introduced via the noise. To get
the useful information in the received signal we must subtract
out this spurious portion. (pp. 108-109)
The
obvious first remark, and indeed the remark that carries the major
burden of the argument, is that the mathematical theory is exceedingly
general in its scope, fundamental in the problems it treats, and
of classic simplicity and power in the results it reaches.
This is a theory
so general that one does not need to say what kinds of symbols
are being considered—whether written letters or words, or
musical notes, or spoken words, or symphonic music,or pictures.
The theory is deep enough so that the relationships it reveals
indiscriminately apply to all these and to other forms of communication.
This means, of course, that the theory is sufficiently imaginatively
motivated so that it is dealing with the real inner core of the
communication problem—with those basic relationships which
hold in general, no matter what special form the actual case may
take. (pp. 114-15)
An engineering communication theory
is just like a very proper and discreet girl accepting your telegram.
She pays no attention to the meaning, whether it be sad, or joyous,
or embarrassing. But she must be prepared to deal with all that
come to her desk. (p. 116)
The appearance of entropy in the theory,
as was remarked earlier, is surely most interesting and significant.
Eddington has already been quoted in this connection, but there
is another passage in "The Nature of the Physical World"
which seems particularly apt and suggestive:
Suppose
that we were asked to arrange the following in two categories—distance,
mass, electric force, entropy, beauty, melody.
I think there
are the strongest grounds for placing entropy alongside beauty
and melody, and not with the first three. Entropy is only found
when the parts are viewed in association, and it is by viewing
or hearing the parts in association that beauty and melody are
discerned. All three are features of arrangement. It is a pregnant
thought that one of these three associates should be able to figure
as a commonplace quantity of science. The reason why this stranger
can pass itself off among the aborigines of the physical world
is that it is able to speak their language, viz., the language
of arithmetic.
I feel sure that
Eddington would have been willing to include the word meaning
along with beauty and melody; and I suspect he would have been
thrilled to see, in this theory, that entropy not only speaks
the language of arithmetic; it also speaks the language of language.
(p. 117)
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Excerpts from Daniel Chandler,
"The
Transmission Model of Communication" (1995)
[1] Information and meaning arises only
in the process of listeners, readers or viewers actively making
sense of what they hear or see. Meaning is not 'extracted', but
constructed.
[2] Linearity
The transmission model fixes and separates the roles of 'sender'
and 'receiver'. But communication between two people involves
simultaneous 'sending' and 'receiving' (not only talking,
but also 'body language' and so on). In Shannon and Weaver's model
the source is seen as the active decision-maker who determines
the meaning of the message; the destination is the passive target.
It is a linear, one-way model, ascribing a secondary role
to the 'receiver', who is seen as absorbing information. However,
communication is not a one-way street. Even when we are simply
listening to the radio, reading a book or watching TV we are far
more interpretively active than we normally realize.
There was no provision in the original model for feedback (reaction
from the receiver). Feedback enables speakers to adjust their
performance to the needs and responses of their audience. A 'feedback
loop' was added by later theorists, but the model remains linear.
[3] Transmission models treat decoding
as a mirror image of encoding, allowing no room for the receiver's
interpretative frames of reference. Where the message is recorded
in some form 'senders' may well have little idea of who the 'receivers'
may be (particularly, of course, in relation to mass communication).
The receiver need not simply accept, but may alternatively ignore
or oppose a message. We don't all necessarily have to accept messages
which suggest that a particular political programme is good for
us.
[4] In the transmission model the participants
are treated as isolated individuals. Contemporary communication
theorists treat communication as a shared social system. We are
all social beings, and our communicative acts cannot be said to
represent the expression of purely individual thoughts and feelings.
Such thoughts and feelings are socio-culturally patterned.
[5] In models such as Shannon and Weaver's
no allowance is made for relationships between people as communicators
(e.g. differences in power). We frame what is said differently
according to the roles in which we communicate. If a friend asks
you later what you thought of this lecture you are likely to answer
in a somewhat different way from the way you might answer the
same question from the undergraduate course director in his office.
The interview is a very good example of the unequal power relationship
in a communicative situation.
People in society do not all have the same social roles or the
same rights. And not all meanings are accorded equal value. It
makes a difference whether the participants are of the same social
class, gender, broad age group or profession. We need only think
of whose meanings prevail in the doctor's surgery. And, more broadly,
we all know that certain voices 'carry more authority' than others,
and that in some contexts, 'children are to be seen and not heard'.
The dominant directionality involved in communication cannot be
fixed in a model but must be related to the situational distribution
of power.
[6] Finally, the model is indifferent
to the nature
of the medium. And yet whether you speak directly to, write
to, or phone a lover, for instance, can have major implications
for the meaning of your communication. There are widespread social
conventions about the use of one medium rather than another for
specific purposes. People also differ in their personal attitudes
to the use of particular media (e.g. word processed Christmas
circulars from friends!).
Furthermore, each medium has technological features which make
it easier to use for some purposes than for others. Some media
lend themselves to direct feedback more than others. The medium
can affect both the form and the content of a message. The medium
is therefore not simply 'neutral ' in the process of communication.
[7] Conclusion
In short, the transmissive model is of little direct value to
social science research into human communication, and its endurance
in popular discussion is a real liability. Its reductive influence
has implications not only for the commonsense understanding of
communication in general, but also for specific forms of communication
such as speaking and listening, writing and reading, watching
television and so on. In education, it represents a similarly
transmissive model of teaching and learning. And in perception
in general, it reflects the naive 'realist' notion that meanings
exist in the world awaiting only decoding by the passive spectator.
In all these contexts, such a model underestimates the creativity
of the act of interpretation.
Alternatives to transmissive models of communication are normally
described as constructivist: such perspectives acknowledge
that meanings are actively constructed by both initiators and
interpreters rather than simply 'transmitted'. However, you will
find no single, widely-accepted constructivist model of communication
in a form like that of Shannon and Weaver's block diagram. This
is partly because those who approach communication from the constructivist
perspective often reject the very idea of attempting to produce
a formal model of communication. Where such models are offered,
they stress the centrality of the act of making meaning and the
importance of the socio-cultural context.
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Definitions
of "PCM" and "PPM" (contrasted with "PAM")
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from Microsoft Press Computer Dictionary, 3rd ed.
(Redmond, Wash.: Microsoft Press, 1997)
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 PAM:
Pulse Amplitude Modulation. A method of encoding information
in a signal by varying the amplitude of pulses. The unmodulated
signal consists of a continuous train of pulses of constant
frequency, duration, and amplitude. During modulation the
pulse amplitudes are changed to reflect the information
being encoded.
PCM: Pulse Code Modulation. A method
of encoding information in a signal by varying the amplitude
of pulses. Unlike pulse amplitude modulation (PAM), in which
pulse amplitude can vary continuously, pulse code modulation
limits pulse amplitudes to several predefined values. Because
the signal is discrete, or digital, rather than analog,
pulse code modulation is more immune to noise than PAM.
 PPM:
Pulse Position Modulation. A method of encoding information
in a signal by varying the position of pulses. The unmodulated
signal consists of a continuous train of pulses of constant
frequency, duration, and amplitude. During modulation the
pulse positions are changed to reflect the information being
encoded.
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References
- James R. Beniger, The Control
Revolution: Technological and Economic Origins of the Information
Society (Cambridge, Mass.: Harvard Univ. Press, 1986)
- Daniel Chandler, "The
Transmission Model of Communication" (1995)
- Clifford Geertz, The Interpretation
of Cultures (New York: Basic, 1973), Chap. 1, "Thick Description:
Toward an Intepretive Theory of Culture," Chap. 15, "Deep Play:
Notes on the Balinese Cockfight"
- A. J. Greimas, Structural
Semantics: An Attempt at a Method, trans. Daniele McDowall
et. al. (Lincoln: Univ. of Nebraska Press, 1983)
- C. P. Snow, The Two Cultures
and the Scientific Revolution (New York: Cambridge Univ.
Press, 1959)
- Warren Weaver, "Recent Contributions
to the Mathematical Theory of Communication" (1949), in
Claude E. Shannon and Warren Weaver, The Mathematical Theory
of Communication (Urbana: U. Illinois Press, 1949)
- On cryptography and early computing
during WW II:
- Simon Singh, The Code Book: The Evolution of
Secrecy from Mary, Queen of Scots to Quantum Cryptography
(New York: Doubleday, 1999)
- Neal Stephenson, Cryptonomicon (New York:
Avon, 1999)
Supplementary
links for this class on Study Materials page
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