What is creativity? One new idea may be creative, whereas another is merely new: What's the difference? And how is creativity possible? These questions about human creativity can be answered, at least in outline, using computational concepts. There are two broad types of creativity, improbabilist and impossibilist. Improbabilist creativity involves novel combinations of familiar ideas. A deeper type involves METCS: the mapping, exploration, and transformation of conceptual spaces. It is impossibilist, in that ideas may be generated which – with respect (...) to the particular conceptual space concerned – could not have been generated before. The more clearly conceptual spaces can be defined, the better we can identify creative ideas. Defining conceptual spaces is done by musicologists, literary critics, and historians of art and science. Humanist studies, rich in intuitive subtleties, can be complemented by the comparative rigour of a computational approach. Computational modelling can help to define a space, and to show how it may be mapped, explored, and transformed. Impossibilist creativity can be thought of in “classical” Al terms, whereas connectionism illuminates improbabilist creativity. Most Al models of creativity can only explore spaces, not transform them, because they have no self-reflexive maps enabling them to change their own rules. A few, however, can do so. A scientific understanding of creativity does not destroy our wonder at it, nor does it make creative ideas predictable. Demystification does not imply dehumanization. (shrink)

Tomasello, Kruger & Ratner deserve congratulations for their well-reasoned ideas on the development of cultural learning. Their arguments are generally convincing, perhaps because their distinctions and developmental relations among types of cultural learning and agency mirror concepts of my own.

Industrial melanism, according to the traditional explanation, amounts to niche construction since it involves changes in predation pressure. Indeed, it would be difficult to imagine selection without niche construction. This cannot be what Laland, Odling-Smee & Feldman mean. They offer convincing examples, but they should provide a better definition of “niche construction” to indicate how their view supplements traditional evolutionary biology.

This target article presents a theory of human cultural learning. Cultural learning is identified with those instances of social learning in which intersubjectivity or perspective-taking plays a vital role, both in the original learning process and in the resulting cognitive product. Cultural learning manifests itself in three forms during human ontogeny: imitative learning, instructed learning, and collaborative learning – in that order. Evidence is provided that this progression arises from the developmental ordering of the underlying social-cognitive concepts and processes involved. (...) Imitative learning relies on a concept of intentional agent and involves simple perspective-taking. Instructed learning relies on a concept of mental agent and involves alternating/coordinated perspective-taking (intersubjectivity). Collaborative learning relies on a concept of reflective agent and involves integrated perspective-taking (reflective intersubjectivity). A comparison of normal children, autistic children and wild and enculturated chimpanzees provides further evidence for these correlations between social cognition and cultural learning. Cultural learning is a uniquely human form of social learning that allows for a fidelity of transmission of behaviors and information among conspecifics not possible in other forms of social learning, thereby providing the psychological basis for cultural evolution. (shrink)

Tomasello, Kruger & Ratner relate the evolution of social cognition – the understanding of others' minds – to the evolution of culture. Tomasello et al. conceive of the accumulation of culture as the product of cultural learning, a kind of learning dependent upon recognizing others' intentionality. They distinguish three levels of this recognition: of intention (what isxtrying to do), of beliefs (what doesxthink aboutp), and of beliefs about beliefs (what doesxthinkythinks aboutp). They then tie these levels to three discrete forms (...) of cultural learning – imitative, instructed, and collaborative – which children become capable of when they are 9 months, 4 years, and 6 years old respectively, at least in Western culture where relevant data are available. (shrink)

Tomasello, Kruger & Ratner make the very interesting and valid point that the transmission of culture must depend on understanding others' minds. Culture is shared among a people and is passed on to progeny. The sharing of culture implies that the purpose of (and therefore the meaning behind) any given cultural element (behavioral tradition, word, or artifact) is understood. Because meaning or purpose emanates from minds, something about others' minds must be understood in order to truly learn some element of (...) a culture. It thus makes sense that cultural learning should depend on social-cognitive skills. But what exactly is cultural learning?There are two rival interpretations of the term cultural learning. In the first, one would define a given type of cultural learning by the type of social-cognitive skill it entails. For example, imitative learning would be defined as any learning of a cultural element in which another's goals or intentions are taken into account. This definition of cultural learning, however, would force Tomasello et al.'s argument into a circle: Imitative learning relies on this social-cognitive skill because imitative learning is defined as learning that relies on this social-cognitive skill. Such a circular definition does not do their argument justice. (shrink)

This piece is a commentary on a precis of Maggie Boden's book "The creative mind" published in Behavioral and Brain Sciences.

This paper uses autocatalytic networks to model discontinuous cultural transitions involving cross-domain transfer, using as an illustrative example, artworks inspired by the oldest-known uncontested example of figurative art: the carving of the Hohlenstein-Stadel Löwenmensch, or lion-human. Autocatalytic networks provide a general modeling setting in which nodes are not just passive transmitters of activation; they actively galvanize, or “catalyze” the synthesis of novel nodes from existing ones This makes them uniquely suited to model how new structure grows out of earlier structure, (...) i.e., cumulative, generative network growth. They have been used to model the origin and early evolution of biological life, and the emergence of cognitive structures capable of undergoing cultural evolution. We conducted a study in which six individual creators and one group generated music, prose, poetry, and visual art inspired by the Hohlenstein-Stadel Löwenmensch, and answered questions about the process. The data revealed four through-lines by which they expressed the Löwenmensch in an alternative art form: lion-human hybrid, subtracting from the whole to reveal the form within, deterioration, and waiting to be found with a story to tell. Autocatalytic networks were used to model how these four spontaneously derived through-lines form a cultural lineage from Löwenmensch to artist to audience. We used the resulting data from three creators to model the cross-domain transfer from inspirational source to creative product. These four spontaneously-generated threads of cultural continuity formed the backbone of this Löwenmensch-inspired cultural lineage, enabling culture to evolve even in the face of discontinuity at the level conventional categories or domains. We know of no other theory of cultural evolution that accommodates cross-domain transfer or other forms of discontinuity. The approach paves the way for a broad scientific framework for the origins of evolutionary processes. (shrink)

This paper reviews and clarifies five misunderstandings about cultural evolution identified by Henrich et al.. First, cultural representations are neither discrete nor continuous; they are distributed across neurons that respond to microfeatures. This enables associations to be made, and cultural change to be generated. Second, ‘replicator dynamics’ do not ensure natural selection. The replicator notion does not capture the distinction between actively interpreted self-assembly code and passively copied self-description, which leads to a fundamental principle of natural selection: inherited information is (...) transmitted, whereas acquired information is not. Third, this principle is violated in culture by the ubiquity of acquired change. Moreover, biased transmission is less important to culture than the creative processes by which novelty is generated. Fourth, there is no objective basis for determining cultural fitness. Fifth, the necessity of randomness is discussed. It is concluded that natural selection inappropriate is an explanatory framework for culture. (shrink)