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
1/16/02
)
Preliminary Class Business
David Trend, Reading Digital Culture
Media and Communication
Where we are in the course:
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
Telecom,
Radio, Cryptography
Transmission
Model
1940s-70s
(ATT breakup in 1984)
Information
as Mainframe Computing
Mainframes
and Minicomputers, Databases
Centralized
information services
1950s-1970s
Information
as Personal Computing/ Networking
PC's, Networks
(LAN's, WAN's), Graphical User Interface (GUI),
the Software Revolution, Hypertext
Client/Server
Architecture
1980s-2000s
What is the relationship between the ideas of
"media" and "communication"?
The integral relationship between human communication
and media: humans (unlike animals) communicate
through media
The nature of mediated communication is that
it is experienced "separately" from
the "ancestral environment of information"
(Borgmann) for which humans were originally
hard coded:
The history of media and communications
is one of increasing separation from "naturalness"
(e.g., print)
Media do not just transmit reality. They
also:
Model reality according to their
own system
Allow humans to use that system to
interiorize, analyze, or otherwise manipulate
reality in symbolic form
Shape or control humans based on their
system.
The "media" and "communications
revolutions" in the middle of the 20th
century were parallel events that "thickened"
the self-systemic, non-natural influence of
mediated communications:
Sender
MEDIA
Receiver
Sender
COMMUNICATIONS
Receiver
This "thickening" or complication
of the worlds of media and communications were
the immediate predecessor to the computing revolution
The Communications Revolution:
"Information Theory"
Today, we look at the communications revolution
in the mid-20th century. Specifically, we consider
"information theory," the movement that revolutionized
information processing and telecommunications
immediately after WW II (and epitomized the
epoch of problems in transmission, cryptography,
and ultimately cybernetic technology that the
war focused attention upon).
The specific work to be examined is that
of Claude Shannon and Warren Weaver of Bell
Labswork that has had a cultural influence
well beyond its original technological context.
A testimony to the broad reach of the "Mathematical
Theory of Communication" is its influence in
such branches of literary study as narratology
(e.g., A. J. Greimas, Structural
Semantics):
Claude Shannon's "Mathematical
Theory of Communication" (1948)
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."
Some Main Principles of the New Communication/Information
Theory:
"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."
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 (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
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?
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:
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)
Overall Implications of the
Media & Communication Revolutions
[As I said above:] The "media" and
"communications revolutions" in the
middle of the 20th century were parallel events
that "thickened" the self-systemic,
non-natural influence of mediated communications:
Sender
MEDIA
Receiver
Sender
COMMUNICATIONS
Receiver
McLuhan: "the medium is the message"
(i.e., the medium is its own message separate
from the ostensible content of a message)
Shannon: "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" (i.e., communication is its own
message separate from the ostensible content
of a message)
This "thickening" or complication
or systemization of the worlds of media and
communications were the immediate predecessor
to the computing revolution:
The principles of the general, self-systematic,
and digital were the soil upon which computing
could grow. Consider this prophecy of computing
embedded in Weaver (p. 109):
"The theory provides for very sophisticated
transmitters and receiverssuch,
for example, as possess 'memories,' so
that the way they encode a certain symbol
of the message depends not only upon this
one symbol, but also upon previous symbols
of the message and the way they have been
encoded."
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 exciteda 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 choicethat 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 processby
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 usedwhich
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 consideredwhether
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 problemwith
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)
Suppose
that we were asked to arrange the following in
two categoriesdistance, 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)
[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.
References
James R. Beniger,
The Control Revolution: Technological and
Economic Origins of the Information Society
(Cambridge, Mass.: Harvard Univ. Press, 1986)
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)