Sema Città: Deriving Elements for an applicable City Theory

Sema Città Deriving Elements for an applicable City Theory Klaus Wassermann1 1 Laboratory for Noosynthesis, ETH Zurich, Computer-Aided Architectural Design – Institute for Technology in Architecture, Switzerland 1 [email protected] Abstract. We approach the issue of city theory from three perspectives, the (i) methodo¬logical perspective, (ii) the perspective of the theoretic concept, and (iii) the perspective of an explication that folds the irst two perspectives together. The methodological perspective focuses on the status of theory in an area of research, where the subject – the city – is a complex entity. The second topic of the paper is the derivation of the Sema Città, which describes the city as an entity of intended semiosic productivity instead of conceiving it as a built entity of storages, heterotopic consumption and metabolism. The third part investigates how the concepts information, complexity and evolution can be adapted such that they can be operationalized for research, design and planning. Keywords. city theory; information theory; methodology; complexity; evolution. INTRODUCTION The interest of this paper is the question about an appropriate frame for a city theory. By this we do not want to express that there has not been suitable proposals for such a theory in the past, nor that it could be possible to introduce a complete version of such a frame. Yet we think that quite recently profound changes established a new societal context which poses many challenges for any city theory established so far. Among the biggest ones is the fast pace of changes caused by technology and the growth of the overall human population. The first translates into the notion of the networked and globalized society, the second one into the problematics of sustainability in a world of accelerating urbanization. The first is about rules and their design, the second about needs, underlying constraints and the question who should deal with it. 134 eCAADe 29 - City Modelling Yet, it would be a severe simpliication to limit the perspective to these readily visible topics. Societies’ aspiration towards the shaping of our cities changed along the change of life forms in history. Moreover, designing, planning and implementing is expected today to take place in and as a part of an open society. This prohibits pure functionalist approaches and any disciplinary coninements as well, but also unthoughtful normative stances or any kind of laissez-faire regarding planning or regulation. Ultimately, city theory has to address the question about how to act upon a city. We know that cities are complex and meta-stable, they are non-linear, productive and creative systems. This raises the question whether we can expect kind of causal eicacy with regard to the city. Can we really talk about planning and development, or should we involve evolutionary theory in some way? Even before, there is the problem of the ends: Into which direction one could think of a city could progress? And above all, how should we conceive of this phenomenon we call city, what should the city of the future “be”? It is generally acknowledged that we are in need of a city theory, which is able to respond to questions of the kind as listed above, and which can be operationalized into models for measuring, designing and planning. This article tries to demonstrate the usefulness of a particular igure of thought for any work on a theory about this cultural phenomenon we call “city”. We propose a clearly deined methodology to achieve such a theory. The key element of it is the determination of basic elements from which a theory could be built. These elements should be arranged in such a way that the theory could provide hints for taking suitable action. But how should it be possible to think about causality regarding a cultural phenomenon? Whatever the answers are, it should be clear that traic simulation or the attempt to smartify the city by means of data bases and data mining are not perfectly suitable for this kind of questions. The layout of this article is as follows. First we will deal with some methodological issues, particularly the concept of theory itself. Second we derive the semantic core of this article, the notion of the Sema Città. Third, and last, we briely demonstrate the application of the methodological issues – as discussed in the irst part – to the topics of information, complexity and evolution, which all are closely related to our main conceptual step, the Sema Città. THEORY (AND MODELS) This section is devoted to the issue of theory itself. Why do we need something like a theory, and how should we conceive of it? Delineation There is still a considerably discourse about the relative status of theory and model. The complication derives from the fact, that any model contains theoretical aspects, and specifying a “general” model further may render it into the status of a theory. Hence, there cannot be an absolute criterion to separate model from theory. Elsewhere we have argued (Wassermann 2011) that – provided that it is reasonable to distinguish those concepts – we could say that a theory in a particular domain sets the structural conditions for any modeling, including the modes of applying any particular model, within just that domain. These conditions are conceivable as rules about the modeling, how to organize the symbols, how to operationalize a question, how to organize the relations between concepts, which concepts to allow or to import from other domains and how, how to apply models and when not, and so on. Strictly spoken, we need to accept that theories are not about the segment of the world which is addressed by the models derived from within that theory. Theories are just about models, they regulate them. To indicate that the status of those rules are diferent from the rules implied by models, we call this regulation “orthoregulation”. This implies, inversely taken, that there cannot be any model without a theory, even if this theory has not been made explicit. We even may say, that any action as well as any perception implies at least one model, hence also a theory. Of course, it is better to make both explicit, at least in the context of science, than just implying it. A mathematical model about a subject, a simulation model or an organicistic model about the same subject – the city or any part of it – all convey a particular theory in the respective domain. If not explicitly stated, the theories are even likely to be incommensurable. The status of theory makes it impossible to ind decisive tests that would allow to prefer one theory against another. Theories are not testable by principle, they cannot be falsiied, quite contrary to the believes of positivism. In the case of the city theory the work of Shane (2005) is a good example for a proper theory. He irst deines the perspectives and the elements from which he is going to build models. Such elements are, for instance, the material as armature (mass), the enclave (form) and the heterotopia (dynamics). For each of them he also distinguishes City Modelling - eCAADe 29 135 sub¬types. The models then are built as a particular coniguration from these elements and inally contrasted to real cases. The structure of his arguments relects the attempt to establish elements that are necessary and suicient for reconstructing what Shane labels the “city”. As a contrast to that we can say that a simulation model is as little a theory as it is a mathe¬matical formula. It is just a model, which is based on some theory. Often, metaphors are used directly as integrated concepts, which then are imported from another domain in order to build up a theory. Methodologically, such operations are quite critical, even for abstract terms. A city is not an organism, nor an ecosystem or even a machine. Fortunately, there is a proper means to get rid of the efect of integrated concepts as imports: elementarization and probabilization. Probabilization transforms linguistic metaphors into concepts, which can be operationalized into empiric concepts. In a radical move, elementarization takes advantage of the basic fact that neither rationalist nor empiricist concepts are ever suicient to talk about a phenomenon. Elements are structural pre-cursors of any practical operationalization, and thus any measurement. The Big Four It is often argued that cities resemble distantly to organic structures. Hence we shall look for structures and methodologies developed in biology to grasp the particular characte-ristics of its subject(s). In biology there is the saying that nothing in biology makes sense except in the light of evolution (Dobzhansky 1951). A bit more detailed, Tinbergen (1963) formulated that research in biology is suitably structured by four major per-spectives: ontogeny, phylogeny, physiology and behavior. Typical for biology is more¬over the strive for the identiication of mechanisms within any of those perspectives, as in biology there is no such thing like a “cause”. The question for research about the city then would be, whether there is also such a group of a “Big Four” (or, maybe, three), and if yes, how would these perspectives be 136 eCAADe 29 - City Modelling represented? We cannot provide an answer here, but signs and/or the mediality implied by it may well be one of the suitable candidates. DERIVING EVIDENCE FOR A CONCEPT Shane (2005) proposes an interesting developmental scheme in his city theory. Based on a metrics built from the elementary and constructive dimensions of armatures, enclaves and heterotopias, he distinguishes Archi Città, Cine Città and Tele Città. In a brief and almost brutal summary we could say that “Archi” refers to a form of organization driven more by faith, myths and individuals than by institutions, “cine” indicates the dominant role of movement and lows, and “Tele” inally indicates the efects of technologies to create illusions of any kind, including the collapse of space and time. While a Tele Città may contain aspects even of the Archi Città, the opposite will never be the case. We now are inclined to observe that both series, on the level of the elements as well as on the level of the descriptive and integrated forms, can be characterized by a tendency towards an increasing immaterialization. Shane even distinguishes diferent forms of heterotopias, for which the same observation holds. The irst one, the heterotopia of crisis, is linked to material or corporeal relations, while the last one, the heterotopia of illusions is completely immaterial. It is now interesting that we can construct a bridge to the concepts of another author who mastered architectural theory, Robert Venturi. Venturi (1977) developed a powerful and still widely neglected adoption of Peircean semiotics to architecture and city theory using the case of Las Vegas. Shane, on the other hand, invokes Las Vegas as a good example for the Tele Città, which according to Shane is structured mainly by the hetero-topia of illusions. This bridge is strong one, as we will see. Peircean semiotics is based on two major insights. First, signs always refer to signs. Second, signs are not a material to which we could point or which we could store; for Peirce the concept of “sign” is given by an irreducible triadic relation, set up by the originator, the interpreter and the trans-ferred signal. Basically, a sign is “existent” only within the situation of interpretation. We could say that the sign is given by that situation. Obviously, Peircean semiotics is com-pletely incompatible with the infamous positivist and reductionist “semiotic triangle”, which displays a sender, a receiver, a sign as a distinctive object and the referenced ixed object. This view is utterly lawed and just unfeasible due to its closed character. Peircean Semiotics on the other hand can be used not only to establish a coherent perspective on the history of facades up to the late media facades but also as a theoretical basis to explain the modes of production of spaces in the city (Wassermann and Bühlmann, 2010). Space and its perception is a major site for the societal negotiation of the relationship between the spheres of the material and the immaterial. Note, however, that by the notion of “Sema Città” we do not propose semiotics as the sole methodological approach. As a philosophical concept, Peircean semiotics expresses the primacy of inter¬pretation similarly to the subsequent primacy of language as formulated by Wittgenstein several decades later. Semiotics sits also at the roots of the concept of probabilistic associative networks, as we have pointed out recently (Wassermann 2010). Cultural phenomena cannot be understood without a proper assimilation of associativity. Though standard urban network theory (Baccini and Oswald, 2003) is far ahead of more reductionist approaches like Hillier’s “Space Syntax” (cf. Hillier 2009), e.g. in its capability to separate the quality of the urban from more traditional assignments of visual and morphological characteristics, it focuses on logistic networks almost exclusively, hence it fails to explain the speciic productivity of urban contexts. Yet, it provides an indispensable starting point to think about growth and diferentiation of and in the city, but logistic networks are rather limited in their ability to connect to developmental schemes of any kind. It is remarkable, that associative networks are probably the only structures which are able to link material and informational phenomena. This renders them to a “vertical” conceptual structure, to which one can take a completely conceptual stance as well as one can implement them in practical models. It is precisely the dimension of association where our contemporary technology of the digital brought an almost “Cambrian explosion” of means and varieties. Obviously, all these immaterial aspects, from Shane’s heterotopia through semiotics up to associative networks are related to a speciic potential for possible impressions as well as expressions. Cities and urban environments become not only more dynamic in the realm of immaterial, as the role of the material is shifted to just an infrastructural role. More important, cities become more exciting for its inhabitants and visitors due to the dedicated shift to the aspect of semantics. As associative networks, which are fuelled by volatile dynamics of open signs, urban contexts become productive in the realm of signs and information. The common term of new media or mediatization of the city (Kronhagel 2010) describes a symptom of this deep change in the structural make-up of the city. We thus may expect a fundamental change of the way we will conceive cities: much more as an entity of intended semiosic productivity than just as a built entity of logistic infra-structure, heterotopic consumption and metabolism, in short, as a “Sema Città”. In order to understand the Sema Città, its productivity, its power and the required new modes of design, we also need to understand the relationship between the material and the immaterial, especially the transitions between those two realms. ARCHAEOLOGY OF THE SEMA CITTÀ The remainder half of this contribution will deal with three concepts, which are settling at the boundary between the material and the immaterial: Information, complexity and evolution. More precisely, we will introduce adaptations of these abundant concepts, which are formulated in a way allowing their assimilation by a city theory. Further topics belonging to this crucial transition are growth and the associativity of networks in the city, the last of which we City Modelling - eCAADe 29 137 already treated elsewhere (Wassermann 2010). All of these concepts could be more than valuable, but they fail to do provide substantial beneit to studies about the city when we refer to them in their traditional form. Information Apparently, information is a natural companion of the sign to which the label “Sema Città” refers. Almost unintended, we already arrived at the core of the problem. With regard to the language game “information”, all of us are actually playing two incompatible games. We are used to say “store information” as well as “information is interpreted data”. To sharpen this point a bit more, we see that we either do not distinguish between information and data (the result of information must be storable, i.e. data) or we do not store information but only data. As a third alternative we could suggest that information has nothing to do at all with interpretation. Well, obviously we need interpretation, even as a primacy, but equally obvious we then meet a problem here. This section sets out to resolve this problem by eliminating the incompatibility of the language games. It is clear that we have to succeed. Otherwise, the Sema Città would be a proposal without potential content. The traditional formalization of information has been provided by Shannon. It has been triggered by the need to describe the error propagation in a message, encoded using a ixed alphabet, where the process creating the stream has no memory. Thus it is a purely syntactical measure. Yet, already Weaver (1949) proposed a tripartite analysis of information. These parts are (1) technical problems using Shannon’s theory, (2) semantics as represented by meaning and truth and (3) the impact and efectiveness of information on human behavior. Despite the fact that he correctly points out the importance of interpretation as a constitutive element of a more holistic concept, Weaver’s proposal cannot serve as a sound basis for a conceptualization. The core of the problem is in the second part. By mid of the last century Wittgenstein (1973) succeeded in demonstrating 138 eCAADe 29 - City Modelling that meaning is dependent on conventions and thus can neither be operationalized nor set a priori; in his Tractatus (Wittgenstein 1963) he also proofed that – counter-intuitively enough – truth cannot be a category in the actual world at all. To understand information, to which interpretation is also constitutive, we have to integrate the convention, i.e. we have to map the dynamic roots of meaningfulness into the concept. Floridi [1] suggested a semantic conception of information, but ended with the diagnosis, that the meaning of the concept of information is still not clear. The main law in Floridi’s approach is that he still tries to formalize meaning in a static approach, i.e. in a single set of formulas. We proposed a diferent strategy (Wassermann 2011), which (i) is based on a recursive procedure establishing a limit process, and (ii) proposes three aspects of information. It is important to keep in mind that these aspects cannot be changed independently, neither they are reducible to any subset. These aspects are the form, eicacy and extension of information. Information can be formatted (irst aspect) as bit, word, image etc. using symbols and these symbols of a formatting is what can be stored, transferred etc. The aspect of eicacy refers to the eiciency of information, which can be operationalized by uncertainty measures. This uncertainty refers to a use case without actually determining it. Finally, the extension of information describes the strictness of the encoding and decoding process, for example given by a sample rate and the complete-ness of the involved measurement regarding the sensory channel. This however is a meta-information which is mandatory for any interpretation. It can be secured and regulated only by conventions. Any of the parts can be conceived again as (2nd order) information, being subject to the triangle of aspects. Playing the information game involves always all three aspects. Diferent kinds of information can be expressed by weighing these aspects diferentially, which often is itself dependent on the context, i.e. dependent on the pur-pose of an action or measure¬ment. Even if so far no standard has been deined on how to quantify this “3 aspectional” information, it provides a stable foundation on how to con-ceive of information regarding a city, city design and city management. The aspect of eicacy relates information to causality. Information and causality can be linked using measurement as kind of a frame joint. “Pure” causality is in the same way impossible as “pure” information, we cannot invoke them separately. Complexity Complexity is probably one of the most abused concepts in contemporary discourses, except perhaps in physics. Luhmann (1978) proposed that complexity denotes things a system cannot deal with, because it cannot comprehend it. This conclusion was a necessary by-product of his so-called “systems theory”. Since then, complexity developed into a widely accepted and elegant symbolic notion for incomprehensibility and ignorance. So far there is no acceptable nor an accepted working deinition. Sometimes it is related to adaptivity (by deinition or unclear empirical impression), sometimes to the “edge of chaos” (Lewin 2000), very often it is just equaled with self-organization. Complex systems are characterized by a phenomenon which could be described from a variety of perspectives. We could say that symmetry breaks, that there is strong emergence (Chalmers 2000), that it develops patterns that cannot be described on the level of the constituents of the process, and so on. If such an emergent pattern is being selected by another system, we can say that something novel has been established. Many researchers feel that complexity potentially provides some important yet opaque beneits, despite the abundant usage as a synonym for incomprehensibility. As it is always the case in such situation, we need a proper operationalization, which in turn needs a clear-cut identiication of its basic elements in order to be suicient to re-construct the concept as a phenomenon. As we already pointed out above, these elements are to be understood as abstract entities, which need a deliberate instantiation before any usage. From a large variety of sources starting from Turings seminal paper (1952) and up to Foucault’s igure of the heterotopia we can derive ive elements, which are necessary and suicient to render any “system” from any domain into a complex system. We emphasize that taken individually they are not new, yet their formulation as a compound principle. So far, such a construction is missing in all of the research about complexity. The elements are as follows. (e1) dissipation implemented in a population of entities (e2) antagonistic inluences of asymmetric range and strength, also represented by populations (e3) standardization, (e4) active compart¬mentali¬zation and, inally, (e5) systemic knots as topo¬logical shortcuts between distant layers. e1 expresses that the system needs to be far from equi¬librium (Nicolis and Prigogine, 1989). Such systems are not in an optimized state. e2 relects the basic structure of any reaction-diffusion-systems (cf. Turing 1952). e3 is necessary for any establishment of shared code. Without e4 there is no transition from order to organization, as the process itself would represent the only memory available. Thus, compartments are essential for the initiali¬zation of histori¬cibility, aging and learning. We could simply call it “diferentiation”, but then we would lose the link to the dynamics of the level of the mechanism. Compart¬ments can be of very different kinds. For instance, in a world full of codes and messages, a new compartment can be built just by mixing two codes. The element e5 inally is just an inversion of the principle of enslaving parameters in synergetics (Haken 1981). Complex systems are only stable if there is some top-down control. Any crosslayer control can be understood as a mapping using some kind of model, which as a matter of fact (we are talking about strong emergence) is far from being perfect. If top-down control embraces several layers this unavoidably leads to contradictions between the lower layer’s self-model and the higher layer’s control model. In other words, the whole system creates condition e2 onto itself. If the density of such events is large enough, the other elements are co-constituted, City Modelling - eCAADe 29 139 leading to a self-sustained higher order complexity. In complex systems, we not only ind populations creating compartments or populations interacting within compartments, we necessarily also will always ind populations of interacting compartments. A irst relevance of complexity for the Sema Città is given as a basis for mechanistic models for heterotopia. In other words, such a concept of complexity allows the operatio-nalization of urban heterotopias, which should not be taken as a failure. Instead, they directly indicate the presence of complexity. A suitable model for complexity is also necessary to relect the fact that only complex systems are able to distil patterns from randomness. In order to establish such patterns into novel¬ty, another complex system is needed. Hence we can say that populations of compart¬mentalized populations are able to create and establish novelty, which is mandatory for any kind of adaptability. Contrary to intuition, complexity is thus needed to achieve sustainability. A theory of complexity based on elements like those suggested allows to understand the semiosic productivity of a city. It is in the mechanisms of complexity where we ind the transition from the material to the immaterial. It is clear that a lot of work has to be done to make the beneits of this concept fully graspable for the practice of city theory, even as it is rather simple to ind explications for it. Nevertheless it is also clear that this operationalization of the concept of complexity provides an applicable basis to rationalize the concept of heterotopia. Finally, the proposed deinition of complexity provides well-deined parameters to enable, avoid or tune complexity, just dependent on the purpose. Evolution From a bird’s view one could say that evolution is the historical creation of information through complexity. Cities change, but they don’t do so completely randomly. There is a temporal coherence side by side with contingency. Our claim of a transition towards the Sema Città is inherently also a claim about the evolution of the city. 140 eCAADe 29 - City Modelling The concept of evolution has been conceived primarily as concept from biology for more than 150 years. Almost since its irst coherent formulation by Darwin (2003) there also have always been attempts to apply it to the progression of human culture. Generally, those attempts have been refuted, because a more or less direct transfer implicitly denies cultural achievements. Thus, we have to reconstruct a more general form of evolutionary theory in order to import it to a theory about the change of cities. Unfortunately, we can provide only a brief outline of the reformulation here. In biology, evolutionary theory has been revised or extended several times. Never-theless, its core can be still compressed to the following two propositions (the plus sign does not mean arithmetic addition here), which express the basic elements of this theory: Evolution = Variation + Heredity + Selection (1) Fitness = number of ofsprings in secondary ilial generation F2 (2) The concept of itness is the core of the operationalization of evolutionary theory. As a measure it is only meaningful within a system of competing species. There are, of course, a lot of side conditions one have to be aware of and the mechanisms regarding the single terms of this equation are still under investigation. These equations relect the characteristics of biological matter, i.e. genes and physiology making up a body, which is immersed in a population of bodies, similar (within a species) and diferent ones (competing species). A city does not have such a structure, thus we have to extract the abstract structure from the equation above in order to harvest the beneit. Fortunately, this is quite easy. Our key element is a probabilized version of memory, where memory is a possibly structured random process that renders bits of information unreliable up to its complete deletion. This concept is very diferent from the concept of memes, which refers “directly” to the metaphor of the gene. We start by conceiving here-di¬ty and selection as (abstract) memories. Heredity is obviously a highly accurate long-term memory, actualized as lasting, replicable structures. Selection on the other hand is just the inverse of forgetting, or the diference established by it. Finally, variation can be con¬ceptualized as a randomness operator acting on those two memories. Now we can reform¬ulate all ingredients of basic evolutionary theory in terms of probabilistic memory. Lemma 1: An organism is a device which “exists as” and which can maintain an assemblage M, called a probabilistic memory coniguration. M consists of diferent kinds of memories mi, each of diferent duration and resolution. Lemma 3: Given a population of organisms, the combination (synchronic union) of at least two cross-linked memories M with diferent duration d and, optionally, of diferent temporal resolution r, modiied by an operator for synchronous randomness , results in an evolution, if most of the individuals contain such a memory structure. (5) Finally we can deine itness as the capability to deal (f=0) with the risk of vanishing ( prob({Q}) approaches 0) as an informational coniguration, i.e. a probability prob>0: (6) (3) Any embedding “evolutionary” process picks at least two diferent “memories” from that ensemble. If the durations are suiciently diferent, that organism as deined in (3) will be a “subject” of evolution, i.e. a species. For principle reasons, a species should not deined by an identity relation. Instead we deine it as a limit process, which expresses the compatibility of two diferent memory conigurations. Lemma 2: In a population of size n, we deine the limes of the probability for a uniication of two diferent sets of probabilistic memory conigurations M (e.g. biological organisms, structured cultural ensembles) under conditions of potential interaction. A species then can be deined by the limit value 0 of this limes. (4) Now we have a concept of evolution at our disposal that we can apply to cultural pro¬cess-es like the progression of cities. A city then would be comprised of populations of pro¬li-ferating and differentiating entities (“species”). These entities need not be sharply dis-tinctive! These entities can be anything, the only requirement is that this “anything” could be conceived as “organism” in the sense given above. Note, that this conceptuali¬zation of evolution allows for Darwinian as well as for Lamarckian processes, for indivi¬dual-based selection as well as for group selection, for horizontal as well as for vertical transfer of information. Thus we may conclude that it is truly a generalization of the biological notion of evolution. The signiicance of adopting evolutionary processes for the Sema Città is obvious. Our memory dynamics is closely linked to the con¬cept of com¬plexity and information. We also may start to build operable models of memory stacks. The free parameters for a “memory design” of a city are the number of memory layers, their mutual dynamics and their inner properties. Based on this we quite City Modelling - eCAADe 29 141 likely will be able to tune the stability of urban neighborhoods. Note that this achievement became accessible just through our turn to the sign as the frame for theorizing about the city. CONCLUSION Our endeavor here in this paper was primarily twofold. First we proposed the Sema Città as a proper continuation of David Shane’s (2005) city theory. This turn to the semiosic properties of a city triggers the adoption of concepts like information, complexity or evolution. Our second interest was to demonstrate a particular methodological approach for assimilating such otherwise diicult to apply concepts. This approach builds on two operations, elementarization and probabilization. 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