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Ignoring the role of reiterative processing and worldview transformation leads to exaggeration of the role of curiosity in creativity

Published online by Cambridge University Press:  21 May 2024

Liane Gabora*
Affiliation:
Department of Psychology, University of British Columbia Okanagan Campus, Fipke Centre for Innovative Research, University Way Kelowna BC, Canada [email protected] [email protected] [email protected] https://gabora-psych.ok.ubc.ca
Kirthana Ganesh
Affiliation:
Department of Psychology, University of British Columbia Okanagan Campus, Fipke Centre for Innovative Research, University Way Kelowna BC, Canada [email protected] [email protected] [email protected] https://gabora-psych.ok.ubc.ca
Iana Bashmakova
Affiliation:
Department of Psychology, University of British Columbia Okanagan Campus, Fipke Centre for Innovative Research, University Way Kelowna BC, Canada [email protected] [email protected] [email protected] https://gabora-psych.ok.ubc.ca
*
*Corresponding author.

Abstract

The Novelty-Seeking Model does not address the iterative nature of creativity, and how it restructures one's worldview, resulting in overemphasis on the role of curiosity, and underemphasis on inspiration and perseverance. It overemphasizes the product; creators often seek merely to express themselves or figure out or come to terms with something. We point to inconsistencies regarding divergent and convergent thought.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

The Novelty-Seeking Model (NSM) linking creativity and curiosity is useful in broad terms, but it downplays the complexity of creativity in ways that lead to overemphasis on the impact of curiosity, and underemphasis on inspiration, reiterative processing, cognitive flexibility, and perseverance. This oversimplification comes through in phrasing such as “increasing the repertoire of possible responses, thus enhancing novel thoughts and actions” (p. 24), which implies that creativity is merely a matter of having a large repertoire of available knowledge (raw ingredients). It's what you do with that knowledge (how you turn the raw ingredients into a cake) that makes you creative (Gabora, Reference Gabora, Bentley and Corne2002). It is true that creativity “utilizes stored representations in memory to generate novel ones,” but there may be thousands of intermediate steps between the stored representations and the novel outcome. These intermediate steps involve recursive reflection on a question or problem by viewing it from different perspectives, a process that has been referred to as honing (Gabora, Reference Gabora2017; see also Piffer, Reference Piffer2012). Referring to creativity as “search” implies that the creative idea already exists and is waiting to be found, but due to the reconstructive nature of memory, and the emergence of new properties when concepts interact, the fruits of creative thought may be different from anything ever stored in memory (Gabora, Reference Gabora and Ascott2000, Reference Gabora, Bentley and Corne2002, Reference Gabora2010, Reference Gabora, Vartanian and Jung2018; Gabora & Ranjan, Reference Gabora, Ranjan, Bristol, Vartanian and Kaufman2013).

The article misleadingly implies that the sole goal of creativity is to obtain a novel product. Creators often merely seek to express themselves, or figure out or come to terms with something; this is why creativity can be therapeutic, and accompanied by a sense of release (Barron, Reference Barron1963; Forgeard, Reference Forgeard2013). The outputs of creative thinking are sometimes discarded, the rationale for this being, “it's the journey that matters.” The authors' emphasis on outputs stems from their chosen definition of creativity in terms of the ability to generate new and useful outputs. Elsewhere a process is defined as creative to the extent that it recalibrates a cognitive model (Gabora & Bach, Reference Gabora and Bach2023). Creative thinking may result in a fresh perspective or outlook that doesn't directly manifest as any particular output but has indirect long-term impacts. By defining creativity in terms of internal change, the proposed framework would be able to explain the above-mentioned therapeutic benefits of creativity, and conversely, why psychotherapy itself can be viewed as a creative process (Ganesh & Gabora, Reference Ganesh and Gabora2022).

In the NSM framework, generative activation and evaluation are presented as distinct phases. We argue that throughout the creative process, one is reiteratively both generating (by reflecting on something from a new perspective) and evaluating the result (of that particular reflection), for if evaluation were avoided until a later phase, any early misstep could render every sequence of subsequent steps useless. We suspect that (contrary to the article), evaluation may be as spontaneous as generation. The separation of generative activation and evaluation in NSM stems from adopting the view that creators generate as many solutions as possible and then choose the best, a view that is inconsistent with the results of studies of analogy making and artmaking (Carbert, Gabora, Schwartz, & Ranjan, Reference Carbert, Gabora, Schwartz, Ranjan, Kozbelt, Locher and Tinio2014; Gabora & Saab, Reference Gabora and Saab2011; Scotney, Schwartz, Carbert, Adam Saab, & Gabora, Reference Scotney, Schwartz, Carbert, Adam Saab and Gabora2020). Even when a creator generates multiple possibilities (e.g., multiple sketches for a painting) and chooses one, these seemingly distinct possibilities may be just different ways of expressing a single underlying idea that the creator is wrestling with (Gabora, Reference Gabora2019; Gabora & Steel, Reference Gabora and Steel2022), and in so doing, forging their personal creative style (Gabora, O'Connor, & Ranjan, Reference Gabora, O'Connor and Ranjan2012). These different possible expressions of an ill-defined idea have been modeled as different projections of a superposition state (Gabora, Reference Gabora2017; Gabora & Carbert, Reference Gabora and Carbert2015).

The authors claim that both divergent thought (DT) and convergent thought (CT) are necessary to produce novel ideas but, according to the definitions for CT and DT in the target article, the best-known creativity tests require only one or the other, for example, the Alternate Uses Task (AUT) (Christensen, Guilford, Merrifield, & Wilson, Reference Christensen, Guilford, Merrifield and Wilson1960) requires only DT, and the Remote Associates Test (RAT) (Mednick, Reference Mednick1968) requires only CT. The authors could defend their claim by specifying that only big-C creativity require both modes of thought, and indeed there is evidence for this (Beersma & De Dreu, Reference Beersma and De Dreu2005; Gibson, Folley, & Park, Reference Gibson, Folley and Park2009; Kerr & Murthy, Reference Kerr and Murthy2004). However, defining CT and DT in terms of the number of correct solutions (as in the article) still makes no sense; a problem either has one correct solution or it has multiple correct solutions. In addition, it is often noted that earlier responses on DT tasks are less creative than latter ones (Beaty & Silvia, Reference Beaty and Silvia2012), but if DT is characterized in terms of the number of responses, this is the opposite of what one should expect, because with each response one gives, the number of remaining viable responses decreases by one. Thus, the definitions of DT and CT adopted here would predict that, as creative thought proceeds, one starts thinking more convergently, not more divergently.

These problems can be avoided by defining CT as honing in which concepts are considered from conventional contexts, and DT as honing in which concepts are considered from unconventional contexts (Gabora, Reference Gabora2019). In this view, the underlying cognitive process is the same in both; that is, in both one is looking at something in a different context. However, the unconventional contexts considered in DT result in widely different conceptions (which get counted as different ideas), while the similar contexts considered in CT result in similar conceptions (which get counted as refinements of the same idea) (Gabora, Reference Gabora2019; Gabora & Steel, Reference Gabora and Steel2022; Scotney et al., Reference Scotney, Schwartz, Carbert, Adam Saab and Gabora2020). (A useful analogy is: DT is like shining light on an object from very different angles, producing differently shaped shadows, while CT is like shining the light from similar angles, producing similar-shaped shadows.) This way of defining CT and DT is consistent with findings that creativity is linked to performance on not just DT tests (Plucker & Renzulli, Reference Plucker, Renzulli and Sternberg1999; Runco, Reference Runco2014), but also CT tests (Benedek & Neubauer, Reference Benedek and Neubauer2013); creators simply excel at considering things from different, relevant perspectives.

Financial support

L.G. acknowledges funding from Grant GR026749 from the Natural Sciences and Engineering Research Council of Canada, and from private donors, Susan and Jacques LeBlanc.

Competing interests

The authors declare that they have no competing interests. The funders had no role in the writing of the manuscript, or in the decision to publish the results.

References

Barron, F. (1963). Creativity and psychological health. Van Nostrand.Google Scholar
Beaty, R., & Silvia, P. (2012). Why do ideas get more creative across time? An executive interpretation of the serial order effect in DT tasks. Psychology of Aesthetics, Creativity, and the Arts, 6, 309319. https://doi.org/10.1037/a0029171CrossRefGoogle Scholar
Beersma, B., & De Dreu, C. (2005). Conflict's consequences: Effects of social motives on post-negotiation creative and convergent group functioning and performance. Journal of Personality and Social Psychology, 89, 358374. https://doi.org/10.1037/0022-3514.89.3.358CrossRefGoogle Scholar
Benedek, M., & Neubauer, A. (2013). Revisiting Mednick's model on creativity-related differences in associative hierarchies. Evidence for a common path to uncommon thought. The Journal of Creative Behavior, 47, 273289. https://doi.org/10.1002/jocb.35CrossRefGoogle Scholar
Carbert, N., Gabora, L., Schwartz, J., & Ranjan, A. (2014). Cognitive states of potentiality in art-making. In Kozbelt, A., Locher, P. & Tinio, P. (Eds.), Proceedings of IAEA congress on empirical aesthetics (pp. 121126). International Association of Empirical Aesthetics Press.Google Scholar
Christensen, P., Guilford, J., Merrifield, P., & Wilson, R. (1960). Alternate uses. Sheridan.Google Scholar
Forgeard, M. (2013). Perceiving benefits after adversity: The relationship between self-reported post-traumatic growth and creativity. Psychology of Aesthetics, Creativity, and the Arts, 7, 245264. https://doi.org/10.1037/a0031223CrossRefGoogle Scholar
Gabora, L. (2000). Toward a theory of creative inklings. In Ascott, R. (Ed.), Art, technology, and consciousness (pp. 159164). Intellect Press.CrossRefGoogle Scholar
Gabora, L. (2002). The beer can theory of creativity. In Bentley, P. & Corne, D. (Eds.), Creative evolutionary systems (pp. 147161). Morgan Kauffman.CrossRefGoogle Scholar
Gabora, L. (2010). Revenge of the ‘neurds': Characterizing creative thought in terms of the structure and dynamics of human memory. Creativity Research Journal, 22(1), 113.CrossRefGoogle Scholar
Gabora, L. (2017). Honing theory: A complex systems framework for creativity. Nonlinear Dynamics, Psychology, and Life Sciences, 21(1), 3588. https://doi.org/10.48550/arXiv.1610.02484Google ScholarPubMed
Gabora, L. (2018). The neural basis and evolution of divergent and convergent thought. In Vartanian, O. & Jung, R. (Eds.), The Cambridge handbook of the neuroscience of creativity (pp. 5870). Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
Gabora, L. (2019). Reframing convergent and divergent thought for the 21st century. In A. Goel, C. Seifert, & C. Freska (Eds.) Proceedings of the 2019 Annual Meeting of the Cognitive Science Society, (pp. 1794-1800). Austin TX: Cognitive Science Society.Google Scholar
Gabora, L., & Bach, J. (2023). The path to generative artificial selves. In Proceedings of the 22 nd Portuguese Conference on Artificial Intelligence. (Held Sept 5–8, 2023, Faial Island, Azores, Portugal.) To be published in Lecture Notes in Artificial Intelligence (LNAI), Springer.CrossRefGoogle Scholar
Gabora, L., & Carbert, N. (2015). Cross-domain influences on creative innovation: Preliminary investigations. In R. Dale, C. Jennings, P. Maglio, T. Matlock, D. Noelle, A. Warlaumont & J. Yashimi (Eds.), Proceedings of the 37th annual meeting of the Cognitive Science Society (pp. 758–763). Austin TX: Cognitive Science Society.Google Scholar
Gabora, L., O'Connor, B., & Ranjan, A. (2012). The recognizability of individual creative styles within and across domains. Psychology of Aesthetics, Creativity, and the Arts, 6(4), 351360.CrossRefGoogle Scholar
Gabora, L., & Ranjan, A. (2013). How insight emerges in distributed, content-addressable memory. In Bristol, A., Vartanian, O. & Kaufman, J. (Eds.), The neuroscience of creativity (pp. 1943). MIT Press.CrossRefGoogle Scholar
Gabora, L., & Saab, A. (2011). Creative interference and states of potentiality in analogy problem solving. In L. Carlson, C. Hőlscher & T. F. Shipley (Eds.), Proceedings of the 33rd Annual Meeting of the Cognitive Science Society (pp. 3506–3511). Austin TX: Cognitive Science Society.Google Scholar
Gabora, L., & Steel, M. (2022). From uncertainty to insight: An autocatalytic framework. In Uncertainty: A catalyst for creativity, learning and development (pp. 125156). Springer International Publishing.CrossRefGoogle Scholar
Ganesh, K., & Gabora, L. (2022). A dynamic autocatalytic network model of therapeutic change. Entropy, 24(4), 547. https://doi.org/10.3390/e24040547CrossRefGoogle ScholarPubMed
Gibson, C., Folley, B., & Park, S. (2009). Enhanced DT and creativity in musicians: A behavioral and near-infrared spectroscopy study. Brain and Cognition, 69, 162169. https://doi.org/10.1016/j.bandc.2008.07.009Google Scholar
Kerr, D., & Murthy, U. (2004). Divergent and convergent idea generation in teams: A comparison of computer-mediated and face-to-face communication. Group Decision and Negotiation, 13, 381399. https://doi.org/10.1023/B:GRUP.0000042960.38411.52Google Scholar
Mednick, S. (1968). The remote associates test. Journal of Creative Behavior, 2, 213214. https://doi.org/10.1002/j.2162-6057.1968.tb00104.xGoogle Scholar
Piffer, D. (2012). Can creativity be measured? An attempt to clarify the notion of creativity and general directions for future research. Thinking Skills and Creativity, 7, 258264. https://doi.org/10.1016/j.tsc.2012.04.009CrossRefGoogle Scholar
Plucker, J., & Renzulli, J. (1999). Psychometric approaches to the study of human creativity. In Sternberg, R. (Ed.), Handbook of creativity (pp. 3561). Cambridge University Press.Google Scholar
Runco, M. (2014). Creativity theories and themes: Research, development, and practice. Elsevier.Google Scholar
Scotney, V., Schwartz, J., Carbert, C., Adam Saab, A., & Gabora, L. (2020). The form of a “half-baked” creative idea: Empirical explorations into the structure of ill-defined mental representations. Acta Psychologica, 202, 102983. https://doi.org/10.1016/j.actpsy.2019.102981Google Scholar