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The Culture of Information
ENGL 25 - Spring 2007, Alan Liu
Notes for Class 5

This page contains materials intended to facilitate class discussion (excerpts from readings, outlines of issues, links to resources, etc.). The materials are not necessarily the same as the instructor's teaching notes and are not designed to represent a full exposition or argument. This page is subject to revision as the instructor finalizes preparation. (Last revised 4/11/07 )

Preliminary Class Business

  • What to watch for in future readings on history of computing:

    • main technical developments

    • conceptual and logical principles (e.g., von Neumann computer, stored program computer)

    • 50s culture, 70s culture

    • NCSA Beginner's Guide to HTML

Media and Communication

Where we are in the course:

Information Paradigm Signature Technologies Logical Architecture Peak Epoch (Period of Monopolistic or Cartel Dominance)
* Information as Mass Media Radio, Photography, Film, TV, Magazines Broadcast Model 1920s-1970s
* Information
as Communication
Telegraphy, Telephony, Radio Transmission Model 1940s-70s
(ATT breakup in 1984)
* Information as Computing I:

Age of the Mainframe
Mainframes and Minicomputers, Databases Centralized information services 1950s-1970s

(1969-82 anti-trust suit against IBM)

* Information as Computing II:

Age of Distributed Computing


Networks (LAN's, WAN's)

The "Software Revolution"

Graphical User Interface (GUI)


Client/Server Architecture



(1998-2002 anti-trust suit against MS)

The fundamental relationship between "media" and "communication"

Consider the notion of the "ancestral environment" of information:

Albert Borgmann, Holding On to Reality: The Nature of Information at the Turn of the Millennium (Chicago: Univ. of Chicago Press, 1999):

"Information about reality exhibits its pristine form in a natural setting. An expanse of smooth gravel is a sign that you are close to a river. Cottonwoods tell you where the river bank is. An assembly of twigs in a tree points to ospreys. The presence of ospreys shows that there are trout in the river. In the original economy of signs, one thing refers to another in a settled order of reference and presence. A gravel bar seen from a distance refers you to the river. It is a sign. When you have reached and begun to walk on the smooth and colored stones, the gravel has become present in its own right. It is a thing. And so with the trees, the nest, the raptors, and the fish." (p. 1)

"The ancestral environment is the ground state of information and reality. Human beings evolved in it, and so did their ability to read its signs." (p. 24)

How does one share information across time and space?

1 | 2 | 3 | 4

The story of media as communication:

early media ---------> advanced media

  • evolution of media as transportable, autonomous communication

Communications and media are two sides of the same coin-- humans (unlike animals) communicate through media

Co-evolution of 20th-C. Media and Communication

  • In the middle of the 20th century, the "media" and "communications revolutions"were parallel events that radically increased the transportability and autonomy of media-as-communications

  • Mediated communications "thickened" into an increasingly complex self-regulating system removed from the "ancestral" natural and social systems of human information:

                 Sender ------------> Media ------------> Receiver

       Sender ------------> Communication------------> Receiver

    Marshall McLuhan: "the medium is the message"

    (the medium is its own message separate from the meaning of the message)

    Claude Shannon: the communication system (bits in the channel) is the message

    "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 Communications Revolution: "The Mathematical Theory of Communication"

  • Today, we look at the communications revolution in the mid-20th century, specifically the "mathematical theory of communication" (or "information theory") as it was invented by Claude Shannon and Warren Weaver of Bell Labs

  • The theory revolutionized telecommunications and information processing immediately after WW II (and epitomized the epoch of problems in transmission, cryptography, and ultimately cybernetic technology that the war focused attention upon) (cf., Vannevar Bush's "As We May Think," 1945)

  • It also had a cultural influence well beyond its original technological context. Examples: Thomas Pynchon on entropy, or A. J. Greimas on narratology. From A. J. Greimas, Structural Semantics:
                      Narrative according to Greimas

Claude Shannon's "Mathematical Theory of Communication" (1948): Some Basic Principles

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."



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."


  • "Transmission," "Conduit," or "Transport" Model of Communication:

  • Shannon: "By a communication system we will mean a system of the type indicated schematically in Fig. 1. It consists of essentially five parts:

    Shannon's Diagran of Communication

  • Information as Statistical (Probability and Entropy):

    • 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 (i.e., 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 (on "entropy," see Wikipedia article)

    • The problem of noise: 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?


Excerpts from Warren Weaver, "Recent Contributions to the Mathematical Theory of Communication" (1949)

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 missile 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)

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.

Definitions of "PCM" and "PPM" (contrasted with "PAM")

from Microsoft Press Computer Dictionary, 3rd ed. (Redmond, Wash.: Microsoft Press, 1997)

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. 


  • Albert Borgmann, Holding On to Reality: The Nature of Information at the Turn of the Millennium (Chicago: Univ. of Chicago Press, 1999)
  • Jean Baudrillard, Simulations, trans. Paul Foss, Paul Patton, and Philip Beitchman (New York: Semiotext(e), 1983)
  • 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)

  • 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)