David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Computer science only became established as a field in the 1950s, growing out of theoretical and practical research begun in the previous two decades. The field has exhibited immense creativity, ranging from innovative hardware such as the early mainframes to software breakthroughs such as programming languages and the Internet. Martin Gardner worried that "it would be a sad day if human beings, adjusting to the Computer Revolution, became so intellectually lazy that they lost their power of creative thinking" (Gardner, 1978, p. vi-viii). On the contrary, computers and the theory of computation have provided great opportunities for creative work. This chapter examines several key aspects of creativity in computer science, beginning with the question of how problems arise in computer science. We then discuss the use of analogies in solving key problems in the history of computer science. Our discussion in these sections is based on historical examples, but the following sections discuss the nature of creativity using information from a contemporary source, a set of interviews with practicing computer scientists collected by the Association of Computing Machinery’s on-line student magazine, Crossroads. We then provide a general comparison of creativity in computer science and in the natural sciences.
|Keywords||No keywords specified (fix it)|
No categories specified
(categorize this paper)
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library||
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Izabela Bondecka-Krzykowska (2010). O związkach informatyki z matematyką. Filozofia Nauki 1.
Graeme Ritchie (2007). Some Empirical Criteria for Attributing Creativity to a Computer Program. Minds and Machines 17 (1):67-99.
Stefan Gruner (2011). Problems for a Philosophy of Software Engineering. Minds and Machines 21 (2):275-299.
Michael J. Quinn (2006). On Teaching Computer Ethics Within a Computer Science Department. Science and Engineering Ethics 12 (2):335-343.
Timothy Colburn & Gary Shute (2011). Decoupling as a Fundamental Value of Computer Science. Minds and Machines 21 (2):241-259.
Justin Solomon (2009). Programmers, Professors, and Parasites: Credit and Co-Authorship in Computer Science. Science and Engineering Ethics 15 (4):467-489.
Antonio Marturano & Ruth Chadwick (2004). How the Role of Computing is Driving New Genetics' Public Policy. Ethics and Information Technology 6 (1):43-53.
William J. Rapaport (2005). Philosophy of Computer Science. Teaching Philosophy 28 (4):319-341.
Paul Thagard & Terrence C. Stewart (2011). The AHA! Experience: Creativity Through Emergent Binding in Neural Networks. Cognitive Science 35 (1):1-33.
Timothy Colburn & Gary Shute (2007). Abstraction in Computer Science. Minds and Machines 17 (2):169-184.
Oron Shagrir (1999). What is Computer Science About? The Monist 82 (1):131-149.
Allen Newell & Herbert A. Simon (1981). Computer Science as Empirical Inquiry: Symbols and Search. Communications of the Association for Computing Machinery 19:113-26.
Klaus R. Scherer, Tanja Bänziger & Etienne Roesch (eds.) (2010). A Blueprint for Affective Computing: A Sourcebook and Manual. OUP Oxford.
Amnon Eden (2011). Some Philosophical Issues in Computer Science. Minds and Machines 21 (2):123-133.
Krystyna Gorniak-Kocikowska (1996). The Computer Revolution and the Problem of Global Ethics. Science and Engineering Ethics 2 (2):177-190.
Added to index2010-12-22
Total downloads5 ( #224,380 of 1,098,973 )
Recent downloads (6 months)1 ( #287,052 of 1,098,973 )
How can I increase my downloads?