JISCMail - PHD-DESIGN Archives

Design / systems / complexity / evolution / etc.
Some considerations regarding old-fashioned concepts in design, mainly based on Jonas (2003).

Design process models
Stated in the most general manner, a design task consists in transferring an existing state of a real world "system" into a preferred one, whereby "system" will normally be considered as some kind of complex "whole", consisting of elements and relations between these elements. The preferred state can be defined as an optimal "fit" of the system or artefact and its environment. The artefact is what designers design, whereas the environment consists of the given requirements that have to be met and which cannot be directly controlled by design. The "interface" region between the artefact and the environment is the "location" of design activities.

The systems concept in design appears to be rather simplistic indeed. There is hardly any reference to the elaborate thermodynamic and biological theories of open / dissipative systems, which explain how systems are able to keep a state of high order far from equilibrium, thus overcoming the 2nd law of thermodynamics. Systems concepts in design are mainly based on simplified applications of Wiener's cybernetics (Wiener 1948), dealing with feedback processes in goal-oriented processes, and Weaver's concept of "organized complexity" (Weaver 1948), which filled the obvious gap between the classical concepts of "problems of simplicity" and "problems of disorganized complexity".
This happened in the 1940s, and Operations Research (OR) can be regarded as the first application of systems thinking in "designerly" processes, such as planning and engineering, from the 1950s onward. The problem-solving process in OR consists of the definition of the solution space, the formulation of the measure of merit, the fixing of constraints, and the optimisation process, leading to a local or global optimum.

The design methods movement in the 1960s adopted and developed these approaches. Symbolic models of the design problem have to be built, consisting of factors, which describe the problem situation and causal relations between these factors. Ideally, the solution criterion is given in a quantitative manner, as a measure of merit function. Even aesthetic criteria have been treated in this way, as we know. Numerical optimisation methods based on closed mathematical calculus or iterative heuristic algorithms can be applied to this problem type. The problem space has to be limited and well-known, and if the problem is properly stated, then the solution is just a re-formulation of the problem, or a change of representation, which can be carried out by means of the same symbolic language that was used for the problem definition. But unfortunately, this has never been the normal situation in design.

Design problems may be categorized according to the parameters problem / solution space (elements + relations available), which can be either limited or open, and solution criterion (measure of merit), which can be either quantitative or qualitative, which means influenced by ethical and aesthetic factors. Entirely numerical solutions are possible, if the solution space is limited and the solution criterion is of quantitative nature, which is the case, for example, in a chess problem or in the optimisation of a streamlined shape according to aerodynamic criteria. In all other cases we have value-laden solutions of ethical or aesthetic nature. Even the apparently highly quantitative problem to bring a man to the moon has a large number of qualitative subtasks, as for example the interior of a vehicle. Value-based decisions of minor or major impact have to be taken at various moments during the solution process.

As soon as the relevant environment of a design problem is no longer natural, but influenced by psychic or social aspects, then the concept of time in the process is changing. Time is no longer a linear parameter, the "fourth dimension", but the source of uncertainty. The future can be conceived as a projective space, determined not only by natural trajectories, but by plans, wishes, hopes, fears, decisions, etc. In other words: it is a space of imagination. The development of social situations is proceeding in highly unpredictable ways; the fit between the artefacts and the environments will probably disappear before long. Nevertheless people cannot stop asking: What about remaining prediction capabilities for the future fit of solutions in non-natural contexts?

The question comprises the issue of "how do we want to live?", and marks the shift from "first-generation" to "second generation" methodology, which is closely connected to Horst Rittel (1972). In his view, first-generation methods seem to start once all the truly difficult questions have been dealt with already. He introduced the notion of "wicked problems" and tried to denote the limits of rationality related to this kind of problems. Rational behaviour means the attempt to foresee the consequences of intended actions, which results in 4 paradoxes:
- Tracking down the consequences of actions in advance has consequences (i.e. it costs time, money, effort, etc.) etc. This means, one cannot start to be rational.
- Actions have consequences, and so forth. This means, one cannot end to be rational.
- The more rational one is (in discovering the causal chains of future consequences), the more one is disabled to act. This means, the possible alternative paths become unmanageable.
- A model of the future consequences of actions has to include, as most important component, itself.

According to Rittel, these dilemmas have to be overcome by opening up the closed algorithmic problem solving process and initiating a process of argumentation and negotiation among the stakeholders instead. In other words: he suggests a change from 1st order cybernetics to 2nd order cybernetics: not systems are observed, but systems observing systems. This introduces, as a central new part, the design of the "problem" itself. Under conditions of second order observation we have to account for the fact, that the problem itself is not "given", but has to be constructed by the stakeholders. In consequence, problems are changing their character in the course of the solution process. No information is available, if there is no idea of a solution, because the questions arising depend on the kind of solution, which one has in mind. One cannot fully understand and formulate the problem, before it is solved. Thus, in the end, the solution is the problem. Therefore Rittel argues for the further development and refinement of the argumentative model of the design process and the study of the logic of the designers' reasoning, where logic means the rules of asking questions, generating information, and arriving at judgements.

In view of this situation Rittel (Cross 1984: 326) states in his slightly ironic manner:
"All of which implies a certain modesty; while of course on the other side there is a characteristic of the second generation which is not so modest, that of lack of respect for existing situations and an assumption that nothing has to continue to be the way that it is. That might be expressed in the principle of systematic doubt or something like it. The second-generation designer also is a moderate optimist, in that he refuses to believe that planning is impossible, although his knowledge of the dilemmas of rationality and the dilemmas of planning for others should tell him otherwise, perhaps. But he refuses to believe that planning is impossible, otherwise he would go home. He must also be an activist."

John Chris Jones (1970) puts it more general and metaphoric, when emphasizing the necessity of designing the design process itself. A considerable part of the design capacities has to be re-directed from the problem to the process. The designer as "black box" (the artist) as well as the designer as "glass box" (the follower of 1st generation methods) have to change their attitude towards a self-conception of designer as "self-organizing system", who is observing the evolving artefact plus himself observing the evolving artefact.

This might already be taken as the ultimate conclusion. But I want to go further, trying to denote the problem more exactly. The systems concepts and models still seem to be deficient and sub-complex with respect to the task we are facing.

Inherent patterns - circularity and autopoiesis
Circularity as a characteristic of problem-solving and design processes is showing up. We know DO - loops as instructions for iterative processes in formal languages in software-programming. We know the TOTE - scheme (Test - Operate - Test - Exit) from cognitive psychology (Miller et. al. 1960) as the prototypical pattern for dealing with iterative heuristics and feedback in design methods. Most of these design methods consist of linear sequences of steps of specific subtasks plus TOTE cycles for the necessary feedback. Opaque systems, called "black-boxes" are rendered manageable by means of circular feedback-models. Human agents act as detached operators of these "machines". Thus systems have been typically treated mechanistically as open (for matter, energy and information), and in interaction with their context, transforming inputs into outputs as a means of creating the conditions necessary for survival. Changes in the environment are seen as input stimuli, to which the system must respond in defined manners.

The concept of autopoietic closure in living and meaning-based systems is of utmost importance for the further argument concerning design processes. Autopoiesis characterizes the logic of self-(re)producing systems. Maturana and Varela (1985) argue, that living systems are organizationally closed, i.e. without any input or output of control information. Operations only refer to themselves and the system's internal states. The impression, that living systems are open to an environment, results from an attempt to make sense of such systems from the perspective of an outside observer. The aim of autopoietic systems is ultimately to maintain their own identity and organization. Change in one element is coupled with changes elsewhere, setting up continuous circular patterns of interaction, which are necessarily self-referential. A system cannot enter into interactions that are not specified in the pattern of relations that define its organization. In this sense the system's environment is really a part of itself. The theory of autopoiesis thus admits that systems can be recognized as having "environments", but insists that relations with any environment are internally determined; systems can evolve only along with self-generated paths.

The theory of autopoiesis encourages us to understand the transformation of living systems as the result of internally generated change. Rather than suggesting that the system merely adapts to an environment or that the environment selects the system configuration that survives, autopoiesis places principal emphasis on the way the total system of interactions shapes its future. It is the pattern, or whole, that evolves. Autopoiesis presents a modification of Darwinian theory: while recognizing the importance of system variation and the retention of "selected" features in the process of evolution, the theory offers different explanations as to how this occurs. Changes are eventually induced, but not directed by means of perturbations from outside. The emphasis is shifting from adaptation of a system to its environment towards co-evolution of autonomous systems.

Morgan (1986: 245) was one of the first to apply the biological concept of autopoiesis to a design-related field, namely organization theory:
" When we recognize that the environment is not an independent domain, and that we don´t necessarily have to compete or struggle against the environment, a completely new relationship becomes possible. For example, an organization can explore possible identities and the conditions under which they can be realized. Organizations committed to this kind of self-discovery are able to develop a kind of systemic wisdom. They become more aware of their role and significance within the whole, and of their ability to facilitate patterns of change and development that will allow their identity to evolve along with that of the wider system."
This is a very positive interpretation of autopoiesis, and probably a step forward with respect to the problems of organizations. But it still neglects the fact that the environments of autopoietic systems consist of various other, equally stubborn autopoietic systems. This is essential for design, because design is not a single system and does not face a single environment, as for example an organization in a market.

Luhmann (1984) has formulated this radical generalization of biological autopoiesis. He extends the auto-poiesis concept of living systems for the purpose of describing mental and social sy-stems. His theory of social systems provides more delicate instruments for an identification of the problem and a composed deconstruction of unfounded expectations in design theory. Organizations, as described by Morgan, are one of several sub-categories of communicative / social systems, all of which are operationally closed, autopoietic systems. Living systems act in the medium of life, mental systems in con-sciousness, and social systems in com-muni-cation. Both mental and social systems operate with language and meaning. Com-munica-tion cannot happen without presupposing consciousness and vice versa, nevertheless both are closed, without any transfer of information. Language, which Luhmann calls a "variation mechanism of socio-cultural evolution", is the ultimate instrument for coupling mental and social systems. This coupling seems to be the most powerful driver of human evolution and learning.

Sociocultural evolution - application to design
Autopoietic systems show a high independence from internal and external perturbations (negative feedback compensates for the irritations). On the other hand it is one of the insights of chaos theory, that circularity in simple mathematical models, can cause so-called deterministic chaos. Minimal differences in initial conditions of the system parameters can cause completely different outcomes, so that predictability of final states is lost (positive feedback amplifies perturbations and triggers evolutionary change). Natural evolutionary patterns of development, with their sequence of stable phases and sudden variations seem to be based on an interplay of negative and positive feedback mechanisms.

The evolution of artefacts shows similar patterns. It is not really new to describe artefacts as entities struggling for the survival of the fittest in the hostile environment of the market (Hybs and Gero 1992). But the approach is still sub-complex. We (seem to) know where we come from, but we do not know, where we are going. At least we know the ancestors of our current artefacts, which means some interpretation capacity for design history. Nevertheless we normally do not know the influences that acted upon the bifurcation situations and resulted in exactly this and no other development.

Also representations of design processes reveal these patterns (see e.g. Roozenburg / Eekels, 1991). The nicely cut branches after the bifurcation points suggest, that there is a rational means to overcome the indeterminacy, to take a decision, which provides more than a random chance, that the decision is viable in the future. Rittel (1971/72: 48, 54, translation W.J.) comments this laconic:
"Constrictions are not 'natural conditions' but deliberate restrictions of the variety of solutions, mostly implicit signs of resignation. Š
... In reality there is no opposition / sharp conflict between an Š intuitive approach to solve a problem and Š a controlled, reasonable and rational approach. The more control one wants to exert, the more well-founded one wants to judge, the more intuitive one has to be.
The endpoints in the more and more ramifying tree of causal explanations are always spontaneous judgements."

These evident analogies in the processual patterns of natural and artefact evolution suggest the application of evolutionary concepts to the design of artefacts. (There are those generative approaches that apply evolutionary algorithms to produce topologies and geometrical forms. This path will be neglected here, even if one could argue, that the approach might be able to evaluate the theory presented here.) If we are aiming at new descriptions for the design process, we have to identify the elements and processes of natural evolution, which can be transferred to the evolution of artefacts. We should focus on the problem of increasing the probability of success with respect to a decision to be taken.

Luhmann's theories are closely related to evolutionary epistemology. In his main oeuvre (1997) he has started to work out the concept of social evolution. Evolution theory is based upon the system / environment distinction; it is this difference, which enables evolution. Evolution theory does not distinguish historical epochs, but the circular sequence of variation, selection, and re-stabilization. It serves for the unfolding of the paradox of "the probability of the improbable". Re-stabilization is essential, because it is the condition for variation and selection being possible at all. Evolution theory thus explains the emergence of essential forms and substances from the accidental, relieving us of attributing the order of things to an form-giving telos or origin. It simply turns the terminological framework of world-description upside-down. Evolution theory is not a theory of progress, and it does not deliver projections or interpretations of the future. Autopoiesis, as outlined above, enforces a revision of the concept of "adaptation". Adaptation is a condition, not the goal or outcome of evolution: on the basis of being adapted it is possible to produce more and more risky ways of non-adaptation - as long as the continuation of autopoiesis is guaranteed.

The three separated processual components of evolution can be related to the components of society, conceived as a communicative / social system:
- Variation varies the elements of the systems, i.e. communications. Mainly variation means deviating, unexpected, surprising communication. It may simply be questioning or rejecting expectations of meaning. Variation produces raw material and enables further communication with more open connections than before.
- Selection relates to the structures of the system, i.e. the creation and use of expectations that control communication. Positive selection means the choice of meaningful relations that promise a value for building or stabilizing structures. Selections serve as filters to control the diffusion of variations. Religion has been such a filter. Truth, money, power, as symbolically generalized media serve as filters in modern societies.
- Re-stabilization refers to the state of the evolving system after a positive / negative selection. It has to take care of the system-compatibility of the selection. Even negative selections have to be re-stabilized, because they remain in the system's memory. Today stability itself becomes a more and more dynamic concept, indirectly serving as a trigger for variation.

The problems of control and prediction - causality gaps
The previous findings allow us to summarize as follows: Designing consists of interacting and co-evolving autopoietic systems and artefacts. Random mutations in nature plus deliberate decisions and accidental events and connections in social life initiate open-ended processes of self-organization, in which positive and negative feedback interact and produce changing patterns that may at some point assume relatively stable forms, called fashions or trends. This kind of mutual causality implies, that it is not possible to exert unilateral control over any set of variables; interventions are likely to reverberate throughout the whole. Though it is often possible to spot an initial "kick" that sets a system moving in a particular direction, it is important to realize, that to our understanding such kicks are not the cause of the end result. They merely trigger transformations embedded in the logic of the systems involved.
We can identify two problem areas: (1) control, due to the system / environment distinction, and (2) prediction, due to the variation / selection / re-stabilization distinction.

(1) The problem of control:
Luhmann' systems theory provides a map of the possible gaps related to these interventions, called design activities. We have the following combinations to denote the locations, where the gaps are manifest:
- artefacts / organisms
- artefacts / consciousnesses
- artefacts / communications
- artefacts / organisms / communications
- artefacts / consciousnesses / communications
- artefacts / organisms / consciousnesses, and

- artefacts / organisms / consciousnesses / communications.

Artefacts as artefacts are assumed to function; this is not the primary task of designing. With respect to the autopoietic systems, I introduce the following gaps, which are always occurring in interaction with different shares, according to the specific design task:
- organisms ý the function gap, which indicates, that it is not a trivial (Š) task to adapt an artefact to an organism, for example, because bodies cannot speakŠ
- consciousnesses ý the taste gap, which indicates, that it is not a trivial (Š) task, to coordinate individual consciousnesses, for example to optimise a solution for the 80 million consumers of the German market. They are all different, and they cannot speak about their taste in clear and distinct mannerŠ
- communications ý the fashion gap, which indicates, that it is not a trivial (Š) task to generalize a variety of information gathered from individual consciousnesses and to transfer this into the shape of an artefact, for example to plan a new collection of household goods for the Turkish marketŠ

(2) The problem of prediction:
- Variation is aiming at alternatives. This is no problem, since consciousnesses provide abundant "creativity", which is essential for increasing the variety of choice. This is the "timeless" task of designing artefactsŠ

- Selection is aiming at the fit of alternatives into structures. This is a problem indeed, because communicative structures are detectable, but not their future stability. To a certain degree, at least, design research can examine existing structuresŠ
Single aspects can be tackled by isolated approaches: organism - artefact gaps by means of ergonomics, consciousness - artefact gaps by means of cognitive ergonomics, communication - artefact gaps by means of market research, etc.
- Re-stabilization is aiming at the integration of selected alternatives into the system. There is hardly any predictability, because this is a question of long-term viability of selected alternatives within communicative systems. Futures studies and scenario planning are dealing with evolving systemsŠ

Returning to design: The present does not at all mark the "wave front" of progress, but merely consists of what has remained from the past. And so it happens, that we do not live in the best of all possible worlds. Harmony, if at all, is "post-stabilized" harmony, created in our narratives. The study of failed innovations ("floppology") might be a promising approach to improve designing: the "dark side" of the field is probably much richer than the "best practice" view. Design activities happen "in-between", they intervene into the relations of co-evolving autopoietic systems by means of creating artefacts that pretend to improve those relations. The basic problem is neither lacking individual creativity nor insufficient planning, but the uncontrollable and unpredictable nature of communication in the environment of the artefacts. The most developed instrument for bridging this kind of causality gaps between psychic systems is language, which enables communication. Functioning communication is highly improbable. Functioning design is even more improbableŠ

To sum up: there are two basic problems related to systemic gaps:
(1) The gaps between autopoietic systems involved in designing. This is fundamental systemic "obstinacy", which is labelled or covered with the nice and common, but fuzzy terms "creativity", "subjectivity", "values", "trends", Š
(2) The gaps between the evolutionary mechanisms involved in designing. Or: the future orientation of design activities. The artefact, once released, remains as it is. The environments of the artefact change in manners, which are in principle unpredictable.

Conclusion