Subrata Dasgupta

Is creativity a Darwinian process

Abstract: In 1960, the psychologist Donald Campbell advanced a Darwinian model of how new knowledge comes into being. This would later come to be known as “evolutionary epistemology”;. For some psychologists and historians of science interested in creativity in science and technology, the Darwinian perspective was irresistible. Thus, in 1988, the psychologist Dean Keith Simonton proposed a Darwinian model of the psychology of scientific discovery by refining Campbells model. Recently, in 1999, Simonton has devoted an entire book to “Darwinian Perspectives on Creativity.”; In this article, I challenge the Darwinian perspective by examining three episodes taken from the histories of natural science, technology and art, respectively.

Multidisciplinary creativity: the case of Herbert A. Simon

In the twentieth century, no person epitomized more dramatically the “Renaissance mind” than Herbert A. Simon (1916–2001). In a working life spanning over 60 years, Simon made seminal contributions to administrative theory, axiomatic foundations of physics, economics, sociology, econometrics, cognitive psychology, logic of scientific discovery, and artificial intelligence. Simon’s life of the mind, thus, affords nothing less than a “laboratory” in which to observe and examine at close quarters the phenomenon of multidisciplinary creativity. In this paper, we attempt to shed some light on the nature of Simon’s creativity and the nature of his particular Renaissance mind. In particular, we have attempted here to articulate the cognitive styleunderlyingSimon’smultidisciplinary creativity.

Contesting (Simonton's) Blind Variation, Selective Retention Theory of Creativity

Over the 50 years since Donald Campbell advanced his Darwinian theory of creative thought, now better known as the blind variation, selective retention (BVSR) theory of creativity, a considerable literature has evolved, involving both support and opposition to the theory. The most prolific support of BVSR theory is due to Dean Keith Simonton. In response to a detailed exposition by Simonton of BVSR theory, a set of cognitive-historical case studies to refute it was presented by Dasgupta; this, in turn, had elicited a response from Simonton. Very recently, Simonton presented an updated version of the theory, which will be called here Simontons BVSR theory. This article offers two detailed cognitive-historical case studies of actual episodes of technological creativity to challenge and contest BVSR theory as a general theory of creativity.

Innovation in the Social Sciences: Herbert A. Simon and the Birth of a Research Tradition

Abstract: Innovation presumes creativity, but creativity does not necessarily entail innovation. The latter involves both the cognitive process of creation and the social-historical process by which the created product is assimilated into a milieu. My concern in this essay is with innovation in the social sciences. In particular, I examine how the American polymath Herbert Simon was led to a model of human decision-making that gave birth to a new research tradition in the human sciences. For his role in the creation of this research tradition, Simon received the 1978 Nobel Prize in Economics.

On the blind-mindedness of creative thought: comment on "Creative thought as blind-variation and selective-retention: combinatorial models of exceptional creativity" by Dean Keith Simonton.

In an earlier work, basing his arguments on Campbell’s blind-variation and selective-retention theory (BVSR) [1], Simonton asserted that “Darwinism offers the most powerful and distinctive perspective on creativity” [2, p. 248], a proposition which has since been opposed [3,4]. In this current paper Simonton no longer claims that BVSR is Darwinian (p. 2). Instead he has offered a new proposition: “Nothing about creativity can be comprehended except in the light of BVSR” (p. 19). At the heart of his argument is his definition of blindness (p. 4). This definition assumes, implicitly, that creative processes (I) involves the generation of at least two complete ‘ideas’ as variations on which selection can work; and (II) the variations are distinct from one another with their distinct independent probabilities of occurrence and survivability. These assumptions may well be true for the kind of examples Simonton cites, e.g., when a scientist proposes two distinct explanatory hypotheses, and which one is correct can only be ascertained by specific experiments. But there are many instances from the actual history of creative thought where these assumptions do not hold. Here I offer merely one such instance: the process by which Robert Stephenson arrived at his design of the Britannia Bridge in the 1840s [5,6]. Here, neither of the assumptions (I) and (II) holds. At first Stephenson generated two possible designs for the bridge (the suspension bridge and arch bridge forms) and then rejected both; he then returned to one of these original ideas (the suspension bridge form) and the rest of his long ideational process involved a succession of modifications and refinements to this one form such that the final idea (a tubular, wrought-iron form) had no resemblance whatsoever to the original suspension bridge form. To suggest that Stephenson’s ideational process entailed the generation of blind variations (according to Simonton’s definition of blindness) on which selective retention occurred is patently absurd. This is just one example that falsifies Simonton’s claim of the universality of BVSR.

Shedding Computational Light on Human Creativity

Ever since 1956 when details of the Logic Theorist were published by Newell and Simon, a large literature has accumulated on computational models and theories of the creative process, especially in science, invention and design. But what exactly do these computational models/theories tell us about the way that humans have actually conducted acts of creation in the past? What light has computation shed on our understanding of the creative process? Addressing these questions, we put forth three propositions: (I) Computational models of the creative process are fundamentally flawed as theories of human creativity. Rather, the universal power of computational models lies elsewhere: (II) Computational models of particular acts of creation can serve as effective experiments to test universal hypotheses about creative processes and mechanisms; and (III) Computation-based architectures of the creative mind provide metaphorical frameworks that, like all good metaphors, can serve as rich sources of insight into aspects of the creative process. In this paper, we provide evidence for these three propositions by drawing upon some particular episodes in the cognitive history of science, technology, and art.

Automatic belief revision in a plausibility-driven design environment

Truth maintenance systems (TMSs) offer the most elaborate approach to the belief revision problem and are thus ideal candidates for automating belief revision during the course of plausibility-driven design evolution. However, the theory of plausible design (TPD) necessitates multivalued belief propagation while conventional TMSs are two-valued (IN/OUT) systems. Due to this mismatch, the encoding of constraint dependency graphs (CDGs) in conventional TMSs requires an exponential number of justifications. A belief revision system for TPD called the theory of plausible design belief revision system (TPD-BRS) is proposed. TPD-BRS uses a modified version of the assumption-based TMS label propagation algorithm in conjunction with a label interpreter to support automated belief revision in TPD efficiently. >

Epistemic Complexity and the Sciences of the Artificial

In 1962 Herbert Simon articulated the nature of complexity of both natural and artificial systems. A system, he said, is complex if it is composed of a large number of components that interact in nontrivial ways. I will label Simon’s notion as systemic complexity. However, in the case of artifacts – things produced or conceived in response to some need or desire – there is another type of complexity which is especially relevant. This is the richness of the knowledge embedded in an artifact. I call this epistemic complexity. It comprises of the knowledge that both contributes to the creation of an artifact and the knowledge generated as a result of that creation.