22 September 2009

Mental Models and Metaphors: Creative Thinking

The human mind is built upon models and metaphor. This is true from the pre-natal moment that enough nerve cells come together to co-oscillate, and it is true for the most advanced explorations into the cutting edge of science and technology. Cognitive scientist Nancy J. Nersessian has discovered the importance of model building in science:
Designing, building, and experimenting with physical simulation models are central problem-solving practices in the engineering sciences. Model-based simulation is an epistemic activity that includes exploration, generation and testing of hypotheses, explanation, and inference. This paper argues that to interpret and understand how these simulation models function in creating knowledge and technologies requires construing problem solving as accomplished by a researcher–artifact system. It draws on and further develops the framework of "distributed cognition"... _TopicsCognitiveScience
More from Nersessian:
To develop an understanding of the system under investigation, scientists build real-world models and make predictions with them. The models are tentative at first, but over time they are revised and refined, and can lead the community to novel problem solutions. Models, thus, play a big role in the creative thinking processes of scientists. _SD
This is a very basic understanding of the work of invention and creativity at the borders of science and technology. But what Nersessian is doing is to make the process more explicit, in order to bring creativity to a wider range of activities -- including the classroom.

Model-building and metaphor is basic to the thinking process. But as the domain of thinking and creativity grows more complex -- as at the cutting edge of science and engineering -- the models and metaphors used will grow more intricate.

Einstein made wonderful use of mental models in his pursuit of new science, as did Feynman and other great scientists. As better methods of building physical and computing models are developed, the creative process is augmented by a form of "distributed cognition", as Nersessian terms it. Once the model exits the mind of the scientist and exists in the outer world, other minds can grasp it and tweak it -- making the tool of cognition distributed.

Models are only tools to help discover reality, however. They are not the reality. That is the error that climate scientists too often make: they forsake scientific observation and data confirmation and pursue computer models as if the models were the reality.

Models sit at the crux between data and theory. Without data, theory is mere confabulation. But without theory, data is simply noise. The human mind is always attempting to create order out of chaos, model out of data. This process is unconscious, and begins to occur long before the mind acquires language. It leads to optical illusions, common delusions, and mass confusion when conclusions are jumped to without adequately testing the models ("carbon climate catastrophe").

But since it is how we think, we need to know how to make the most of it -- while also keeping things "real."More: The above image is a computer mapping of shipping traffic near Rotterdam. The human mind is capable of creating similar maps mentally, but as a phenomenon grows more complex, computer mappings and visualisations become more helpful

A map (or complex visualisation) is similar to a model, in that the map takes a large mass of data, and connects the data in such a way that the mind can grasp it more easily -- in all its complexity.

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