1.6.      Consequences for a Theory of Computer Support

The ideas of situated cognition and Heidegger’s philosophy of interpretation stress how different human understanding is from computer manipulations of symbols. These analyses suggest a people-centered approach of augmenting, rather than automating, human intelligence. According to this view, software can at best provide computer representations for people to interpret based on their tacit understanding of what is being represented. Representations used in computer programs must be carefully structured by people who understand the task being handled thoroughly, because the computer itself simply follows the rules it has been given for manipulating symbols, with no notion of what they represent. People (e.g., software designers or software users) who understand the domain must codify their knowledge into software rules sufficiently to make the computer algorithms generate results that, when interpreted by people, will be the desired results. Only if a domain can be strictly delimited and its associated knowledge exhaustively reduced to rules, can it be completely represented in advance (by the software designers) so that tasks in the domain can be automated.

Many tasks like lunar habitat design that call for computer support do not belong to well-defined domains with fully catalogued and formalized knowledge bases. These tasks may require (a) exploration of possibilities never before considered, (b) assumption of creative viewpoints, or (c) formulation of innovative concepts. Software to support designers in such tasks should provide facilities for the designers themselves (as the software users) to create new representations and to flexibly modify old representations. As the discussion of Alexander emphasizes, the ability to develop appropriate understandings of the situation dynamically is critical to innovative design. Because they capture understandings that evolve through processes of interpretation, representations need to be modifiable during the design process itself and cannot adequately be anticipated in advance or provided once and for all. Lunar habitat design is an example of an exploratory domain in two senses: (1) it is a new domain with relatively little in the way of accepted conventional knowledge, and (2) it involves continual innovation to meet novel, over-constrained, politically sensitive mission specifications.

The assumption of the existence (even in principle) of an objective, coherent body of domain knowledge that can be used without being reinterpreted in new situations and from different perspectives is misleading. As Rittel says, non-routine design is an argumentative process involving the interplay of unlimited perspectives, reflecting differing and potentially conflicting technical concerns, personal idiosyncrasies, and political interests. Rather than trying to supply all knowledge in advance, software to support this type of design should capture alternative deliberations on important issues as they arise and document specific solutions. Then, these can be available to support interpretive deliberations. Furthermore, because all design knowledge is relative to perspectives, the computer should be used to define a network of over-lapping perspectives with which to organize issues, rationale, sketches, component parts, and terminology to reflect the different viewpoints designers adopt. That will facilitate the retrieval of information relevant to a particular interpretive stance.

As Schön emphasizes, design relies on moving from tacit skills to explicit conceptualizations, and on the ability to reformulate the implications in linguistic expressions. Additionally, design work is inherently communicative and increasingly collaborative, with high-tech designs requiring successive teams of designers, implementors, and maintainers. Software to support collaborative design should provide a language facility for designers to develop a sharable vocabulary for expressing their ideas, for communicating them to future collaborators, and for formally representing them within computer-executable software. An end-user language that provides an extensible domain vocabulary, is usable by non-programmers, and encourages reuse and modification could help provide support for designers trying to express their interpretations..

Heidegger’s analysis of interpretation says that new interpretations are based on preunderstandings developed in the past or handed down by tradition. In this sense, it is likely that the information designers need most when they reflect on problems may have previously been made explicit at some moment of interpretation during past designing. Accordingly, one promising strategy for accumulating a useful knowledge base is to have the software capture knowledge that becomes explicit while the software is being used. As successive lunar habitats are designed on a system, issues and alternative deliberations can accumulate in its repository of design rationale; new perspectives can be defined with their own modified representations, terminology, and critic rules; and the language can be expanded to include more domain vocabulary, conditional expressions, and query formulations.

This is an evolutionary, bootstrap approach, where the software can not only support individual design projects, but simultaneously facilitate the accumulation of expertise and viewpoints in open-ended, exploratory domains. This means that the software should support designers in formalizing their knowledge when it becomes explicit. The software should reward its users for increasing the computer knowledge base by performing useful tasks with the new information, like providing documentation, communicating rationale, and facilitating reuse and modification of relevant knowledge.

The theory suggested by the analysis of interpretation in design is diagrammed in Figure 1-2. As the cycle of interpretation proceeds, driven by the needs of designing and collaboration, explicit knowledge that is generated can be captured by the computer support system. The computer system relies on a combination of stored representations (for representing situations, defining perspectives, and articulating language expressions) and plasticity (for tailoring the existing representations to the requirements of the specific design process). This combination makes support of interpretation in design possible and simultaneously drives an evolution of the stored knowledge base.

The theory proposed in Chapter 6 views the computer as a design medium. It is a multimedia device capable of representing the diverse forms of information used in design: text, graphics, pictures, pen sketches, numbers, voice, animation, and even video. It can use all these media to externalize design concepts and to store them for future use, serving as a medium of externalization and long-term memory. This means it can be used as a medium of communication among team members and a medium for embedding an artifact’s design history within the design of the artifact itself—Reeves (1993) argues for the role of such a medium in supporting collaborative work.

Figure 1-2. The theory of computer support for interpretation in design.

The cycle of human interpretation (illustrated on the top) is mirrored by a cycle of evolution of the computer knowledge base (below), that uses captured explicit knowledge to support future interpretation.

The uses of the computer as designing medium mentioned in the preceding paragraph are primarily passive uses. The impact of written language on civilization shows that even passive media can be powerful. However, the computational power of the computer suggests using it as an active medium as well. Certainly, numerical computations can be left to the computer: calculate square footage of designs or total their costs. But information can also be made dynamic, with representations modified on the basis of the state of other parts of a design. Furthermore, the information stored in the computer can be managed by it, perhaps organizing and displaying information based on a structure of defined perspectives. A language can make the system programmable by designers, so they can adjust displays to their changing needs. Part III will show how Hermes accomplishes this by means of a computationally active form of hypermedia, that integrates a perspectives mechanism and an end-user programming language.

One of the most powerful consequences of designing in a computational medium is the possibility of integrating all the relevant information. An example of this is the mechanism of interpretive critics (see Fischer, et al., 1993a). It is an extension of specific critics (Nakakoji, 1993). Specific critics are critiquing rules that analyze the representation of a design situation and optionally display a message depending on the results of the analysis. For instance, if two appliances are closer than they should be in the design of a habitat, a critic might display a warning, suggest looking at related design rationale issues, and show similar stored designs that avoid the problem. The specific critics are dynamically computed based on the design specification that has been entered into the design rationale. The critic thus integrates information about the graphical design, the textual rationale, the computational critic rules, and other designs. It does this in a way that supports the needs of the designer without providing overwhelming amounts of information. Interpretive critics are even further embedded in the contexts of design because they can be defined differently in different interpretive perspectives. Their active behavior depends on the current perspective and the way in which terms in the language are defined in that perspective. They use the language that is being used for the particular design, they are tied to the currently active perspective, and they analyze the represented situation.

The view of computer support systems as computationally active communication media is consonant with a liberatory view of the role of computers in society. Feenberg (1991) argues that the expert system approach based on technical rationality philosophy is profoundly anti-democratic and that an alternative approach to computers as communicative media is needed to give people control over their lives:

Systems designed for hierarchical control are congruent with rationalistic assumptions that treat the computer as an automaton intended to command or replace workers in decision-making roles. Democratically designed systems must instead respond to the communicative dimension of the computer through which it facilitates the self-organization of human communities, including those technical communities the control of which founds modern hegemonies. (p.108)

The theory of computer support presented in this dissertation pursues the democratic alternative, founding it on a respect for the irreducible nature of human interpretation.

The key is control. Computer systems are sophisticated tools for exerting control of information. As powerful as they are, computers have no understanding of the information they manipulate. Even in autonomous AI systems, all the interpretation is done by people—typically by the programmers who set up the system and the users who view the output. Innovative design is an arena in which the interpretation cannot be done in advance because this design requires understanding and interpretation at every step. Therefore, the role of computers in non-routine design must be to support designers. Human designers must retain control over (a) how things are represented, (b) which things are stored together, and (c) what terms are used to articulate ideas. Unless this control is vested in people who can use their interpretive skills, questions concerning what information might be relevant in a given context or in the future remain intractable for all but carefully delimited, well-understood, completely codified domains. The only heuristics proposed for the management of design knowledge are those tacitly followed by traditional design practice: (1) that knowledge represented, organized, and articulated in the past may be useful in the future, and (2) that designers will need to use their powers of interpretation to modify and apply reused knowledge in unique situations. (The problem of application addresses the fact that every situated, perspectival, linguistic understanding is unique and yet must be interpreted as similar to other cases; it is discussed in Chapter 5.)

The theory of computer support provides a principled basis for designing a computer system to support innovative design in such tasks as lunar habitat design. Before exploring the ideas suggested for such a system, the existing tradition of design environments is considered. This is a tradition of computer systems supporting the augmentation of human design efforts. It provides a basis upon which new ideas can be developed through extensions that are guided by the theory.

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