5.3.      Transformations of Tacit to Explicit Understanding

Definition of tacit and explicit. In formulating the central problem for computer support, it has been repeatedly stated that human understanding is at bottom tacit while computer representations are necessarily explicit. In this claim, the terms tacit and explicit have been tacitly assumed to mean something like “unverbalized” and “verbally expressed”, respectively. In order to address the problem of tacit and explicit understanding in computer support of interpretation, it is now important to make the usage of these terms more explicit.

The dictionary (Merriam-Webster, 1991) provides the following definitions:

tacit: expressed or carried on without words or speech; implied or indicated but not actually expressed.

explicit: fully revealed or expressed without vagueness, implication, or ambiguity; leaving no question as to meaning or intent; verbal plainness and distinctness such that there is no need for inference and no room for difficulty in understanding.

Comparing these definitions, it seems that there is a continuum of verbal expression, whose extremes are defined as tacit (not expressed) and explicit (fully expressed). The analysis of understanding as a result of the iterative hermeneutic circle suggests that understanding indeed progresses along such a continuum of gradual explication. The discussion of the hermeneutic as indicates that what becomes explicit in an individual step of interpretation is not a complete understanding of a whole state of affairs, but rather one particular aspect (the thing considered as such and such).

A taxonomy of tacit and explicit information. The interpretive movement from tacit to explicit is only the first of several possible transformations of understanding that Heidegger is interested in explaining. Ultimately, he wants to show how the formalized and codified scientific knowledge (which the rationalist tradition took as fundamental) is founded in tacit being-in-the-world. Section 4.3 above summarized Heidegger’s discussion of the role of language in expressing understandings. He uses the term discourse as the basis for verbal expression. Discourse does not necessarily mean that an understanding is spoken out loud, but simply that it is verbalized, if only in the mind of the person who understands. This qualifies as making explicit. Discourse makes the interpretive step from an understanding that has not been verbalized (but can be inferred from a person’s understanding of related things or from the person’s behavior) to one that is revealed to the person who has the understanding. So far, the discussion remains at the level of an individual person.

Discourse can be asserted: spoken out loud. This makes it available to other people. An assertion produces an externalized expression. According to Heidegger’s analysis, assertion can mean pointing out, predicating, or communicating. With assertion, shared knowledge is possible through one person pointing it out or communicating it to others. Furthermore, it is possible to codify knowledge in canonical forms through predication. This formalizes the structure of the knowledge and paves the way for preserving the knowledge in media of external memory, including representing it in a computer symbolism. Capturing the knowledge in a computer provides a stored representation of the knowledge. If the computer system is flexible, this captured knowledge can evolve through modification of the stored representations for use in computer modeling of innovative situations.

Figure 5-3. Successive transformations of knowledge.

The left-hand column lists consecutive forms of information. The right-hand column indicates the transformation processes from one form to another.

Figure 5-3 shows the sequence of possible transformations of understanding. Moving down the progression, the knowledge becomes increasingly explicit and formal. Through this sequence, Heidegger’s theory connects the grounding of knowledge in tacit preunderstanding with the potential for evolving computer representations of knowledge. This provides the epistemological foundation for a theory of computer support for interpretation.

Each transformation involves a reinterpretation of the informational content in a new medium of expression. This entails both gain and loss. Not only is there a gain in precision and clarity with the increasing explicitness, but new discoveries are made along the way. On the other hand, there is a loss of contact with the experiential grounding in the tacitly understood situation. For instance, when the lunar habitat designers first began to interpret privacy in their design, they began with a tacit feeling that they had discovered a problem in the adjacency of the bathroom to the ward room. This feeling was grounded in their personal experiences (e.g., Desi’s memory of the location of the bathroom at his office) or their imaginations of life in the habitat. The tacit preunderstanding of this problem was interpreted in the discourse of privacy. Then Desi and Archie made assertions about privacy in the habitat. This externalized their understanding in language so it could be communicated. If they wanted to preserve their interpretation, they could have predicated it as design rationale, using some semi-formal or formal method such as Ibis. Using a computer support system like Hermes, they could then proceed to capture their concern with privacy in a computer representation that could subsequently be evolved into a useful computer model of privacy for future design efforts.

Figure 5-4 presents a vocabulary of different forms of information for the theory of computer support. All the forms of understanding or knowledge discussed above may be considered forms of information. These are divided into the forms of human knowledge (which are hermeneutically grounded in the intentional presence of the understood situation) and forms of computer representation (formal symbol systems). The taxonomy moves from information forms that are appropriate to individuals to those that form data for computer manipulations. In the middle are forms of shared knowledge. They can be shared by several human designers, or by designers and a computer system.

Figure 5-4. A taxonomy of classes of information.

This taxonomy is meant to provide a vocabulary for discussing a theory of computer support founded on the analysis of interpretation as the transformation of tacit understanding to increasingly explicit knowledge. A taxonomy draws conceptual distinctions. In practice, the categories may be blurred and inter-mixed. A designer dealing with privacy while using Hermes with privacy critics already represented may be working with an understanding of privacy that synthesizes all these forms of information.

The taxonomy is laid out along the dimension of explicitness. This is not the same as formality. Formal information is structural (syntactic); it may be processed by computer. Explicitness is a precondition of such formality, not its equivalent. Consider for instance the semi-formal information of design rationale in an Ibis format. An issue, stated in English text, may have an answer, also in English. The structural relationship between the issue and its answer may be formal in the sense that computers can process this information algorithmically. At the same time, the semantics of the texts of the issue and answer are informal: they cannot be processed by the computer, but require human interpretation. Nevertheless, all the design rationale information has been stated explicitly in order to be entered into the computer.

Figure 5-5. Successive transformations of information.

Successive transformations of tacit and explicit information. Figure 5-5 expands the model of interpretation in design (Figure 5-2) to include Heidegger’s three-fold analysis of assertion. At the end of Chapter 6 (Figure 6-2), it will be further expanded to include the transformations of knowledge capture and representational evolution. This will provide a model of the theory of computer support for interpretation in design.

Here, the subsequent transformations of assertion have been included in the diagram: (i) communicating, (ii) pointing out, and (iii) predicating:

(i) The externalized expression that has been asserted can be used for communication with other people. This makes possible the shared knowledge that forms the basis for collaboration in activities like designing. Understandings that have been made explicit in the process of interpretation can affect the tacit understanding that enters into future activity, either directly as part of the individual’s understanding or indirectly as a social process involving a change in the shared knowledge of a communicating community.

(ii) Alternatively, the externalized expression can serve as a pointing out of the object of the underlying intentionality. When something is put into words there is a potential that it will become reified and lose its semantic grounding; but the act of assertion can be used to counteract this tendency.

(iii) Moreover, the assertion can take the form of predication, in which the reference to the meaning is subsumed in a syntactic formulation. The loss of personal relatedness to that which is understood is traded for an increase in the intersubjective availability. Predication leads to the multiple advantages of codified knowledge:

*    An increase in the explicitness of the knowledge.

*    A standardization of the formulation in a more canonical form.

*    An increase in the formality of the expression, so that it can more easily be syntactically manipulated.

*    An increased ability to preserve the knowledge in external media.   

These characteristics are essential for the development of scientific knowledge.

The codified knowledge can be transformed into the logical calculi of formal science. Heidegger was interested in this transformation because it allowed him to tie scientific knowledge to tacit, commonsense, background knowledge in a way that shows that the formal knowledge is only possible on the basis of the tacit. This, of course, counters the rationalist assumption that one should analyze tacit knowledge as a partial and faulty expression of underlying formal, precise, symbolic, intersubjective, or objective scientific knowledge. For Heidegger, the successive transformations of understanding from tacit knowledge to explicit, externalized, codified, and formalized knowledge is an ontological transformation. Tacit knowledge has to do with our understanding of artifacts-in-use. As the knowledge is transformed through explicit interpretation, externalized assertion, codified predication, and formalized calculi, the artifact becomes a physically-present-object, something observed from an objective status rather than used transparently. With this ontological transformation, the artifact/object becomes decontextualized.

Codified knowledge can also open the opportunity for computer representations. The transformations from tacit preunderstanding to successively explicit forms of information provides a basis for the theory of computer support in the following chapter.

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