Computational Artefacts
- The modern computer is a hierarchically organized system of computational artefacts.
- Hierarchical organization is a means of managing the complexity of an entity.
- Computational artefacts are made things; they process symbol structures signifying information, data, or knowledge (depending on one’s point of view and context).
- There are three classes of computational artefacts.
- One class is material. These artefacts, like all material objects encountered through history, obey the physical laws of nature. e.g. all kinds of computer hardware.
- Some computational artefacts, however, are entirely abstract. They not only process symbol structures, they themselves are symbol structures and are intrinsically devoid of any physicality. So physico-chemical laws do not apply to them. They neither occupy physical space nor do they consume physical time. e.g. algorithms, methodologies, languages, turing machines.
- The third class of computational artefacts are the ones that most lend strangeness to computer science. These are abstract and material. To be more precise, they are themselves symbol structures, and in this sense they are abstract; yet their operations cause changes in the material world; moreover, their actions depend on an underlying material agent to execute the actions. Because of this nature, this class is called liminal (meaning a state of ambiguity, of between and betwixt). e.g. computer programs or software is one vast class of liminal computational artefacts.
- Computer science is the science of computational artefacts.
- Herbert Simon called all the sciences concerned with artefacts (abstract, liminal, or material) the sciences of the artificial. They stand apart from the natural sciences because they must take into account goals and purposes. A natural object has no purpose.
- The sciences of the artificial entail the study of the relationship between means and ends: the goals or needs for which an artefact is intended, and the artefact made to satisfy the needs. The ‘science’ in computer science is, thus, a science of means and ends. It asks: given a human need, goal, or purpose, how can a computational artefact demonstrably achieve such a purpose? That is, how can one demonstrate, by reason or observation or experiment that the computational artefact satisfies that purpose?
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