
The aim of this paper is to briefly explore creative thinking in computer science, and compare it to natural sciences, mathematics or engineering. It is also meant as polemics with some theses of the pioneer work under the same title by Daniel Saunders and Paul Thagard because I point to important motivations in computer science the authors do not mention, and give examples of the origins of problems they explicitly deny. Computer science is a very specific field for it relates the abstract, theoretical discipline – mathematics, on the one hand, and engineering, often concerned with very practical tasks of building computers, on the other. It is like engineering in that it is concerned with solving practical problems or implementing solutions, often with strongly financial reasons, e.g. increasing a company’s income. It is like mathematics in that is deals with abstract symbols, logical relations, algorithms, computability problems, etc. Saunders and Thagard analyse rich experimental material from historical and contemporary work in computer science and argue that, as opposed to natural sciences, computer science is not concerned with describing and explaining natural phenomena. Now, I argue that there is a field of research in artificial intelligence (which, in turn, is a branch of computer science), called machine discovery, where explanation of natural phenomena, finding experimental laws and explanatory models is the primary goal. This goal is achieved by constructing computer systems whose job is to simulate various processes involved in scientific discovery done by human researchers, and help them in making new discoveries. On the other hand, motivations that give rise to ingenious projects in computer science can be very strange and include curiosity, fun or attempts to be famous out of boring, stable life of a successful programmer in a big corporation. A good example is the phenomenon of open-source software, especially the development of the Linux operating system and its applications when, from economical point of view, Microsoft absolutely dominated the software market of personal computers.
creative society, H1-99, computer science, artificial intelligence, Social sciences (General), communication analogy, technology, automated discovery systems, natural sciences, creativity
creative society, H1-99, computer science, artificial intelligence, Social sciences (General), communication analogy, technology, automated discovery systems, natural sciences, creativity
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
