Chapter 7. RELATED COMPUTER SYSTEMS FOR DESIGN

The theory of computer support in the previous chapter has suggested that systems to support interpretation in innovative design should be oriented toward the evolution of domain knowledge and should provide for plasticity of knowledge representations. It suggests that such systems should be people-centered and should offer—among other things—(a) a computationally active form of external medium for representing the situation, (b) a mechanism for displaying alternative perspectives, and (c) a language for articulating interpretations. Above all, it stresses that such functionality should be implemented so as to support a healthy mix of tacit and explicit understanding. This mix is required to support the process of human interpretation as the explication of tacit understanding. This chapter will look at software systems that have been developed to support designers and see what techniques they incorporate for meeting these suggestions. These related systems provide many of the ideas that led to the mechanisms, functionality, and concerns of the Hermes substrate.

The approach of this dissertation is within the tradition of situated cognition. A number of influential works in this tradition have addressed the question of computer support for design. They are uniformly opposed to the approach of expert systems like Mycin (Buchanan & Shortliffe, 1984) for innovative domains. Rather than endorsing systems that automate the decision making process, they call for systems that provide media in which people can exercise their design skills while benefiting from computational supports. Unfortunately, these writings have proposed little in the way of detailed proposals for alternative software techniques to support situated interpretation in design.

Dreyfus (1972), for instance, makes some high-level suggestions about designing software to augment human understanding. But Dreyfus is a philosopher and not a computer scientist, so he does not propose any software prototypes. Similarly, Schön (1992) is not a programmer and can, in the end, merely hope that better work will be put into building “designer assistant” programs than has been in the past, rather than into expert systems. The architects Coyne and Snodgrass (1991) propose a hermeneutic philosophic basis for AI, and they too make general recommendations along the lines of Dreyfus and Schön.

Suchman (1987) emphasizes the contrast between rationalist plans and situated action. She also stresses the role of language in constituting human interpretation of situations. But she is concerned with human-computer communication in which the computer must understand and act (produce Xerox copies), rather than with the computer as external memory or as a medium for shared human cognition. Instead of proposing an alternative programming approach, she fine-tunes traditional programs with more hardware sensors of the human situation and with more situated testing of the human-computer communication.

Another forceful critique of expert-system style AI from a Heideggerian perspective is presented by Winograd and Flores (1986), who call for a new approach to software design. They note that the computer is ultimately a structured dynamic communication medium and they stress the central role of language in coordinated action. They propose the Coordinator program as an example of new software as a medium for Computer Supported Cooperative Work. They note its limitation: "In many contexts this kind of explicitness is not called for, and may even be detrimental" because language is ultimately an "open-ended domain of interpretation." Despite this recognition, they propose software that initially failed to be accepted in many social settings because it imposed a rigid, explicit, public structure where people often want to remain implicit. In such cases it did not empower personal interpretations because it misjudged the balance between tacit and explicit.

Participatory design, as described by Ehn (1988), is a method for developing software in partnership with the end-users, so it can be designed to support skillful work and democratic workplace relations, in contrast to traditional automation approaches like those reported by Noble (1984). The idea is to design computer tools for experts that support and extend their situated skills, including their tacit know-how. As an example, the Utopia project worked with graphic layout professionals to pioneer a desktop publishing toolkit, as an alternative to the automated systems that were putting graphics professionals out of work. This toolkit approach may have been innovative at the time, but is now considered mainstream. Participatory design proposes alternative approaches to design, but offers little in the way of recommended software functionality for supporting interpretation.

The situated cognition literature has not made it clear what kinds of differences the alternative theory makes at the level of software techniques. Therefore, this chapter must look elsewhere and define its own answer to this question. It will do this by turning for ideas to two traditions of system building in AI that do provide alternatives to expert systems. While these traditions have not produced adequate systems for supporting interpretation, they have prototyped mechanisms for supporting either tacit or explicit understanding. The traditions to be considered are: design environments and knowledge representations. These “traditions” will be caricatured here as distinct and contrasting approaches, although there are significant cross-influences and confluences.

To represent the tradition of design environments, a series of systems developed during the past several years at the University of Colorado will be reviewed: especially Janus (Fischer et al., 1989) and Phidias (McCall, et al., 1990a). These systems provide tools for designers to construct design artifacts and to reflect upon them. Phidias and Janus serve as the particular focus because the development of the Hermes system was intimately influenced by them. The tradition of knowledge representations will be taken to include a series of knowledge representation languages and a series of design rationale capture systems. The knowledge representation languages include Planner (Hewitt, 1971), Conniver (Sussman & McDermott, 1972), Krl (Boborow & Winograd, 1977), and Pie (Boborow & Goldstein, 1980a). The design rationale capture systems include Ibis (Kunz & Rittel, 1970), Phibis (McCall, 1987), gIbis (Conklin & Begeman, 1988), and Drl (Lee & Lai, 1991).

The caricature of these two traditions consists in taking the design environments as systems that support tacit designing and the knowledge representation languages as systems for supporting explicit documentation of argumentation. This is an exaggeration, because the design environments include explicit knowledge structures and the knowledge representation systems have made efforts to support tacit usage. Nevertheless, the major thrusts of these traditions (at least as they are distinguished in principle) is usefully characterized this way. Moreover, the real question is not simply whether some mixing of tacit and explicit understanding is supported, but precisely how that mixture is defined. That is, the previous chapter called for support of the movement between tacit and explicit understanding based on the particular sequence of transformations of understanding that are outlined in the analysis of human interpretation and in the corresponding theory of computer support. The question is how to take the two traditions’ ideas for supporting tacit and explicit understanding respectively and to “apply” them in an integral approach to supporting interpretation.

This chapter will argue that the traditions of design environments and knowledge representation languages call for the following functionality to support interpretation in innovative design:

*    an external medium for design (Section 7.1);

*    perspectives for deliberation (Section 7.2);

*    a language for human problem-domain communication (Section 7.3).

Each of these realms of functionality should support the designer’s movement back and forth between tacit and explicit understandings of the design artifact.

While design environments strive to provide tools for doing the design work, knowledge representation systems focus on tools for explicating the knowledge—e.g., as formalized design rationale. They both overlook the importance of the dynamic interpretive cycle. Developers of design environments claim that their knowledge bases capture rules of the domain, and the design rationale system developers ignore the grounding of arguments in human understanding. In this way, both groups of systems understate the role of human interpretation. However, together they provide mechanisms that can be integrated into systems for supporting interpretation. This integration is prototyped in Hermes, as described in Part III. Systems that properly merge the ideas of the two traditions have the potential to be both expressive and usable by exploiting the synergy of tacit and explicit, human and computer.

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