Our HCI Seminar concluded another section last week, during which we were asked to read selected articles, find something relevant for comparison, and then, well, compare it. All in all, it turned out to be a great way to analyze and personalize the literature. Now is a chance to reflect on the weekly reflections.
When I examined all the previous essays, the central theme was one of dynamics. Related to that is a distinction between knowing and understanding.
My concept of fuzzy determinism is a rejection of precision in favor of the forces acting in a system. Rather than accounting for changes in every component, trust that the collective ebb and flow that emerges from their interactions is the more important information. This is exemplified in the discussion about accountability. Understanding how a complex system moves about through time and space is not practical or predictive by measuring the parts. Similarly, in evolving Csikszentmihalyi’s Flow Diagram into one of critical flow, the emphasis changes from a kind of measurement of perception to the dynamics between skill and challenge.
I believe there is a paradigm shift that has to occur for the dynamics to become the focus in design. Namely, it is vital to examine objects in relation to other objects. Context matters in recent HCI literature, but largely such discussion is satisfied in concluding the meaning of the objects are changed. It is still very much an objective perspective, rather than a relational one. Possibly Suchman’s idea of how activity is created is the closest to true relational design.
Knowing and Understanding
In design, it is less important to know than it is to understand. (As Albert Einstein said, “Any fool can know. The point is to understand.”) What’s the difference? I’ve got my ideas, but first let’s see what some physicists think. I pulled this list from a 2004 forum discussion on the topic:
Knowing
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Understanding
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Clearly, there is some difference in terminology between knowing and knowledge, which we at Informatics might say is the difference between data and knowledge, or knowledge and information.
I compare this to the first essay I wrote in the master’s program at the IU School of Informatics (). That came from the Intro to Informatics course and a two-week discussion about ontology and epistemology. I described the former as a top-down quantification of a concept, moving from an abstract notion to evidence supporting that abstraction. The latter is a bottom-up process that turns data into knowledge by giving it meaning, by identifying the existence of something that data signifies. In that debate, knowledge is differentiated from unformed data with understanding implied to be the process of moving between the two. In other words, knowledge becomes an endpoint on a journey of understanding.
For me, the distinction is a difference in precision. Knowledge is precise and detailed. Understanding is approximate and to some extent generalized. Knowledge is about the object, and understanding deals with the relationship. Knowledge is measurement. Understanding is dynamics.
