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Wiener & Shannon: Toward a Politics of Information (I)
A couple decades ago, the term Information Age was bandied about to define our new technological era, not so much anymore. Maybe, unlikely as it appears, we realize we remain firmly entrenched in industrialism and we've never really understood that. Claiming the era was the Information Age was never quite right. From our beginnings, information has been an integral, one can say an essential defining component of Homo sapiens. From the oldest culture, the ability to control fire, tilling the soil, and the relatively recent invention of the printing press, information has been an intrinsic feature of humanity. With the invention of electric media followed by the networked microprocessor, humanity's dependence on information increased exponentially. Today, our inability to effectively utilize both the quantity and quality of information overwhelms our established economic, cultural and government institutions. In order to understand this deluge of information and to in any way provide qualitative measures of value, we need a politics of information.
What precisely is information? This is a question still difficult to answer. There isn't a simple answer. We might borrow American Supreme Court Justice Potter Stewart's line about defining pornography, “I know it when I see it.” From the original Latin, sapiens could be defined as “thinking,” the popular connotation of “wise” is a little bit of stretch when preceded by Homo. Thinking implies information, whether provided by the senses or abstractly generated in our minds.
In 1948, at the dawn of the age of the transistor, two essential books about information were published. One was Claude Shannon's The Mathematical Theory of Communication, the second, Norbert Wiener's, Cybernetics or Control and Communication in the Animal and the Machine. As seen from the titles, both focus on communication, neither provide a strict or simple answer to what is information. In fact, in his wonderful introduction to Shannon's work, mathematician Warren Weaver writes,
“The concept of information developed in this theory at first seems disappointing and bizarre - disappointing because it has nothing to do with meaning, and bizarre because it deals not with a single message but rather with the statistical character of a whole ensemble of messages, bizarre also because in these statistical terms the two words information and uncertainty find themselves to be partners.”
Despite this uncertainty and the inherent contradiction of concept, both works have been essential to providing the thought and math upon which the computer industry and resulting communication infrastructures have been built. It's by no means extraordinary that so much has been accomplished with information without a definition of what exactly it is. After all, no one can tell you what gravity is. We understand it by dropping an object, watching tides, or calculating the planets paths around the sun. Similarly, energy and matter are known more by their characteristics and actions than any precise definition of what exactly they are. What all three have in common, starting with Galileo's and Newton's equations, is with ever more sophisticated mathematics, we have been able to create ever more sophisticated technologies to manipulate mass, energy, and information.
However, turning to Wiener's thought at the top of this paper, it is essential to understand information is not energy or matter. Begun ten-thousand years ago, we can look at the Agrarian Era, , as a leap in our abilities to manipulate matter. The Industrial Age, only several centuries old, is overwhelmingly shaped by our ability to manipulate mass quantities of energy. Wiener writes the difference between industrial and information technologies “as the distinction between power and communication engineering. It is this split which separates the age just past from that in which we are now living.” While industrialism is dependent on information, it is defined by the harnessing of vast quantities of energy. While the technologies developed over past 75 years are predominately defined by their ability to manipulate information, but entirely dependent on energy.
Both Shannon's and Wiener's theory reveal understanding information is inherently bound with its communication. Shannon's book focuses on the process of communication, how information is carried by a message comprised of signals. It focuses on a linear, a simple communication system architecture, that begins with a source and ends with the receiver, input matches output in sum and shape. Shannon provides a sophisticated math for this system that led to the creation of ever more sophisticated communication gadgets, most especially our digital systems comprised of computers and their now ubiquitous networks.
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In Weaver's introduction to Shannon's work, he breaks down communication theory into three parts:
“LEVEL A. How accurately can the symbols of communication be transmitted? (The technical problem.)”
“LEVEL B. How precisely do the transmitted symbols convey the desired meaning? (The semantic problem.)”
“LEVEL C. How effectively does the received meaning affect conduct in the desired way? (The effectiveness problem.)”
Weaver then writes,
“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 face, 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. It is this, undoubtedly, that Shannon means when he says that 'the semantic aspects of communication are irrelevant to the engineering aspects.'”
Attempting to provide any rigor to the term “ordinary usage,” we fairly quickly find any definition of information rather nebulous. What's imperative to understand with Shannon's work, it doesn't deal with information's meaning. Information is defined through its communication, the engineering aspect of getting a message transmitted from source to receiver
In regards to Weaver's three part outline of communications theory, Shannon's work only concerns Level A ,”the technical problem.” However, Weaver adds, “But this does not mean that the engineering aspects are necessarily irrelevant to the semantic aspects.” Inherent in any communication technology we use, the medium shapes information both in its transmission and its reception in certain ways that can be as important as the information itself. A decade later, this was brilliantly expressed by technology historian Marshall McLuhan with, “The medium is the message.”
This might simply be recognized by the differences in our senses, which are information collectors, yet the variety of engineering behind sight, hearing, smell, and touch are all essential to understanding the information received.
In some ways, Wiener's Cybernetics is more essential to the present and future, most especially for constructing a politics of information. Wiener's work is more encompassing, rooted in historical and political context, not just simply the operation of technology from the insights of engineering, but how it comes to be and grappling with the greater societal implications. As Wiener's astutely comments, an acute criticism that could be applied to the then just forming Tech industry, “I know very great engineers who never think further than the construction of the gadget and never think of the question of the integration of the gadget with human beings in the society.”
Most importantly, Wiener's insights differ from Shannon's in that he looks at not just one direction communication, but how messages are sent and then returned, which necessitates a greater understanding of whatever larger organization the communication system is embedded. Cybernetics looks not simply at Weaver's Level A communication, but requires an understanding of both Levels B, the information's meaning, and C, it's impact on the receiver. Key to this understanding is feedback, simply understood as when a source emits a message, what message is returned in response. Feedback is “centered not around the technique of electrical engineering but around the much more fundamental notion of the message, whether this should be transmitted by electrical, mechanical, or nervous means.” Feedback provides a more rigorous, though by no means comprehensive understanding of information. It places the communication system into larger context in that it concerns how a mechanical or organic entity operates autonomously.
Just as with Shannon's work, Wiener's insights are largely mathematical constructs, feedback “is a phenomenon which we understand very thoroughly from a quantitative point of view.” Most importantly, the math underneath both theories is the statistical math used to provide the insights of quantum mechanics. The theories “belong to the Gibbsian statistical mechanics rather than to the classical Newtonian mechanics.”
Weaver notes on Shannon’s theory,
“In doing this, we have made of communication engineering design a statistical science, a branch of statistical mechanics. …The notion of the amount of information attaches itself very naturally to a classical notion in statistical mechanics: that of entropy. Just as the amount of information in a system is a measure of its degree of organization, so the entropy of a system is a measure of its degree of disorganization; and the one is simply the negative of the other.”
This fundamentally probabilistic, uncertain, and relative world, is completely ignored in the proclamations and evangelizing of our technological determinists. Wiener states, “In quantum mechanics, the whole past of an individual system does not determine the future of that system in any absolute way but merely the distribution of possible futures of the system.” Essentially adding, “In general, there is no set of observations conceivable which can give us enough information about the past of a system to give us complete information as to its future.”
This understanding is imperative to understanding the development of technology, the unacknowledged degree of randomness involved, or in looking at politically, the amount of choice or who chooses. Instead, the history of established technologies are written as if their existence and adoption were always pre-determined, maybe some underlying Calvinistic predestination accounts for this mindset, though it's not surprising given these histories largely emanate from power structures the technologies themselves created. Worse, our last half-century “Tech” era haphazardly or more accurately hazardously, indiscriminately bestows labels like visionary to technologists, yet it is a process overwhelmingly shaped today, as Wiener astutely described in a 1950 talk as “extremely tempting to anybody who wants to make a quick fortune and leave the rest of the community to try and pick up the pieces.”