Information and the Nature of Reality Bernd-Olaf Küppers, page 180:
Let us consider the relationship between semantic information and complexity in more detail. Information is always related to an entity that receives and evaluates the information.This, in turn, means that evaluation presupposes some other information that underlies the process of registration and processing of the incoming information. But how much information is needed in order to understand, in the foregoing sense, an item of incoming information? This question expresses the quantitative version of the hermeneutic thesis, according to which a person can only understand some piece of information when it has already understood some other information. At first sight, it would seem impossible to provide any kind of answer to this question since it involves the concept of understanding, which, as we have seen, is already difficult to understand by itself, let alone to quantify. Surprisingly, however, an answer can be given, at least if we restrict ourselves to the minimal conditions for understanding. To this belongs first of all the sheer registration by the receiver of the information to be understood. If the information concerned conveys meaning – that is, information of maximum complexity – then the receiver must obviously record its entire symbol sequence before the process of understanding can begin. Thus, even the act of recording involves information of the same degree of (algorithmic) complexity as that of the symbol sequence that is to be understood. This surprising result is related to the fact that information conveying meaning cannot be compressed without change in, or even loss of, its meaning. It is true that the contents of a message can be shortened into a telegram style or a tabloid headline; however, this always entails some loss of information. This is the case for any meaningful information: be it a great epic poem or simply the day’s weather report. Viewed technically, this means that no algorithms – that is, computer programs – exist that can extrapolate arbitrarily chosen parts of the message and thus generate the rest of the message. But if there are no meaning-generating algorithms, then no information can arise de novo. Therefore, to understand a piece of information of a certain complexity, one always requires background information that is at least of the same complexity. This is the sought-after answer to the question of how much information is needed to understand some other information.
Ultimately, it implies that there are no “informational perpetualmotion machines” that can generate meaningful information out of nothing (Küppers, 1996). This result is the consequence of a rigorous relativization of the concept of information. It is a continuation of the development that characterized the progress of physics in the last century: the path from the absolute to the relative. This began with the abandoning of basic concepts that had been understood in an absolute sense – ideas such as “space,” “time,” and “object” – and has since led to well-known and far-reaching consequences for the foundations of physics. Whether the thorough-going relativization of the concept of information will one day lead to a comparable revolution in biological thinking cannot at present be said. This is largely due to the fact that the results up to now have been derived with respect to the semantic dimension of human language, and it is not yet clear to what extent they are applicable to the “language of genes.” For this reason, questions such as whether evolution is a sort of perpetualmotion machine must for the present remain open. At least it is certain that we must take leave of the idea of being able, one day, to construct intelligent machines that spontaneously generate meaningful information de novo and continually raise its complexity. If information always refers to other information, can then information in a genuine sense ever be generated? Or are the processes by which it arises in nature or in society nothing more than processes of transformation: that is, translation and re-evaluation of information, admittedly in an information space of gigantic dimensions, so that the result always seems to be new and unique? Questions such as these take us to the frontline of fundamental research, where question after question arises, and where we have a wealth of opportunities for speculation but no real answers.
If an intelligent creator is not excluded a priori, real answers emerge......
The world of abstract structures
Finally, I should like to return briefly to the question with which we began: Are the ideas of “information,” “communication,” and “language” applicable to the world of material structures? We saw how difficult it is to decide this on a philosophical basis. But it may also be the case that the question is wrongly put. There does indeed seem a surprising solution on the way: one prompted by current scientific developments. In the last few decades, at the border between the natural sciences and the humanities, a new scientific domain is emerging that has been termed “structural sciences” (Küppers, 2000b). Alongside information theory, it encompasses important disciplines such as cybernetics, game theory, system theory, complexity theory, network theory, synergetics, and semiotics, to mention but a few. The object of structural sciences is the way in which the reality is structured – expressed, investigated, and described in an abstract form. This is done irrespectively of whether these structures occur in a natural or an artificial, a living or a non-living, system. Among these, “information,” “communication,” and “language” can be treated within structural sciences as abstract structures, without the question of their actual nature being raised. By considering reality only in terms of its abstract structures, without making any distinction between objects of “nature” and “culture,” the structural sciences build a bridge between the natural sciences and the humanities and thus have major significance for the unity of science (Küppers, 2000b).
In philosophy, the structural view of the world is not new. Within the frame of French structuralism, Gilles Deleuze took the linguistic metaphor to its limit when he said that “There are no structures that are not linguistic ones … and objects themselves only have structure in that they conduct a silent discourse, which is the language of signs” (Deleuze, 2002, p. 239). Seen from this perspective, Gadamer’s dictum “Being that can be understood is language” (Gadamer, 1965, p. 450) takes on a radically new meaning: “Being” can only be understood when it already has a linguistic structure. Pursuing this corollary, the philosopher Hans Blumenberg (2000), in a broad review of modern cultural history, has shown that – and how – the linguistic metaphor has made possible the “readability” (that is, the understanding) of the world. However, the relativity of all understanding has of necessity meant that the material “read” was reinterpreted over and over again, and that the course of time has led to an ever more accurate appreciation of which “readings” are wrong. In this way, we have approached, step by step, an increasingly discriminating understanding of the reality surrounding us.