Reframing Convergent and Divergent Thought for the 21st Century

Convergent thought is defined and measured in terms of the ability to perform on tasks where there is a single correct solution, and divergent thought is defined and measured in terms of the ability to generate multiple different solutions. However, this characterization of them presents inconsistencies, and despite that they are promoted as key constructs of creativity, they do not capture the capacity to reiteratively modify an idea in light of new perspectives arising out of an overarching conceptual framework. Research on formal models of concepts and their interactions suggests that different creative outputs may be projections of the same underlying idea at different phases of this kind of 'honing' process. This leads us to redefine convergent thought as thought in which the relevant concepts are considered from conventional contexts, and divergent thought as thought in which they are considered from unconventional contexts. Implications for the assessment of creativity are discussed.Comment: 7 pages; 2 figures

Cultural Evolution as Distributed Computation

The speed and transformative power of human cultural evolution is evident from the change it has wrought on our planet. This chapter proposes a human computation program aimed at (1) distinguishing algorithmic from non-algorithmic components of cultural evolution, (2) computationally modeling the algorithmic components, and amassing human solutions to the non-algorithmic (generally, creative) components, and (3) combining them to develop human-machine hybrids with previously unforeseen computational power that can be used to solve real problems. Drawing on recent insights into the origins of evolutionary processes from biology and complexity theory, human minds are modeled as self-organizing, interacting, autopoietic networks that evolve through a Lamarckian (non-Darwinian) process of communal exchange. Existing computational models as well as directions for future research are discussed.Comment: 13 pages Gabora, L. (2013). Cultural evolution as distributed human computation. In P. Michelucci (Ed.) Handbook of Human Computation. Berlin: Springe

A model of the emergence and evolution of integrated worldviews

It \ud is proposed that the ability of humans to flourish in diverse \ud environments and evolve complex cultures reflects the following two \ud underlying cognitive transitions. The transition from the \ud coarse-grained associative memory of Homo habilis to the \ud fine-grained memory of Homo erectus enabled limited \ud representational redescription of perceptually similar episodes, \ud abstraction, and analytic thought, the last of which is modeled as \ud the formation of states and of lattices of properties and contexts \ud for concepts. The transition to the modern mind of Homo \ud sapiens is proposed to have resulted from onset of the capacity to \ud spontaneously and temporarily shift to an associative mode of thought \ud conducive to interaction amongst seemingly disparate concepts, \ud modeled as the forging of conjunctions resulting in states of \ud entanglement. The fruits of associative thought became ingredients \ud for analytic thought, and vice versa. The ratio of \ud associative pathways to concepts surpassed a percolation threshold \ud resulting in the emergence of a self-modifying, integrated internal \ud model of the world, or worldview

The neural and cognitive mechanisms underlying creative thinking

The ability to generate creative ideas and novel solutions is a defining feature of human cognition. However, the cognitive and neural mechanisms that underlie creative cognition are poorly understood. While recent research has highlighted the roles of distinct associative and controlled processes in creative cognition, supported by the default mode and executive control networks, respectively, it remains unclear how exactly creative ideas are produced by the interactions of these processes and networks, or how creative cognition relates to more fundamental processes like executive functions and working memory (WM). The present thesis aims to examine the neurocognitive basis of creative thinking using a combination of behavioral and fMRI experiments. The need for greater computational modeling in neurocognitive creativity research (NCR) is also discussed. The first study examines how the default mode and executive control networks contribute to creative cognition over time. Results are broadly suggestive of distinct generative and evaluative phases in creative thought. A second study explores relationships between multiple forms of creative thinking and multiple forms of inhibition, finding that divergent thinking is related to cognitive inhibition. In a third study, relationships between creative cognition and control over WM are examined, using measures of executive functions. While no relationships were found between divergent thinking and executive functions, a positive relationship was found between WM updating and convergent thinking and verbal fluency. In a review chapter, the case for greater computational modeling in NCR is made. Previous models of creative cognition, and how these might be improved upon, are discussed, with some examples of the model development process. In a final study, relationships are explored between personality measures and evaluations of the novelty, usefulness, and creativity of ideas. A closing chapter summarizes all findings and discusses avenues for future research