Divergent thinking (DT) is an important constituent of creativity that captures aspects of fluency and originality. The literature lacks multivariate studies that report relationships between DT and its aspects with relevant covariates, such as cognitive abilities, personality traits (e.g. openness), and insight. In two multivariate studies (N = 152 and N = 298), we evaluate competing measurement models for a variety of DT tests and examine the relationship between DT and established cognitive abilities, personality traits, and insight. A nested factor model with a general DT and a nested originality factor described the data well. In Study 1, DT was moderately related with working memory, fluid intelligence, crystallized intelligence, and mental speed. In Study 2, we replicate these results and add insight, openness, extraversion, and honesty–humility as covariates. DT was associated with insight, extraversion, and honesty–humility, whereas crystallized intelligence mediated the relationship between openness and DT. In contrast, the nested originality factor (i.e. the specificity of originality tasks beyond other DT tasks) had low variance and was not meaningfully related with any other constructs in the nomological net. We highlight avenues for future research by discussing issues of measurement and scoring.

Flexibility (i.e., the number of categorically different ideas), fluency (i.e., the answer quantity), and originality (i.e., the quality of ideas) are essential aspects of the ability to think divergently. Theoretically, fluency and ideational flexibility tasks are akin to one another. However, flexibility was also considered to be uniquely related to working memory capacity due to the task requirements involved in generating diverse answers (e.g., self-monitoring, suppression, and category generation). Given that the role of working memory is strengthened in flexibility tasks relative to fluency and originality tasks, flexibility should be more strongly related with working memory. Additionally, mental speed should show a similar pattern of results because mental speed has been previously related to task complexity. Based on a sample of N = 409 adults (M_age = 24.01 years), we found in latent variable models that fluency/originality strongly predicts flexibility and accounts for 61% of its variance. Creative flexibility was unrelated to working memory and mental speed after controlling for fluency/originality. Additionally, the residual of a latent flexibility factor was unrelated to self-reported creative activities. We concluded that flexibility, as measured here, can be deemed primarily a method factor that did not show value over and above fluency/originality as assessed in traditional fluency and originality tasks. We discussed perspectives for disentangling trait and method variance in flexibility tasks.

Intelligence has been declared as a necessary but not sufficient condition for creativity, which was subsequently (erroneously) translated into the so-called threshold hypothesis. This hypothesis predicts a change in the correlation between creativity and intelligence at around 1.33 standard deviations above the population mean. A closer inspection of previous inconclusive results suggests that the heterogeneity is mostly due to the use of suboptimal data analytical procedures. Herein, we applied and compared three methods that allowed us to handle intelligence as a continuous variable. In more detail, we examined the threshold of the creativity-intelligence relation with (a) scatterplots and heteroscedasticity analysis, (b) segmented regression analysis, and (c) local structural equation models in two multivariate studies (N₁ = 456; N₂ = 438). We found no evidence for the threshold hypothesis of creativity across different analytical procedures in both studies. Given the problematic history of the threshold hypothesis and its unequivocal rejection with appropriate multivariate methods, we recommend the total abandonment of the threshold.

Data from self-report tools cannot be readily compared between cultures due to culturally specific ways of using a response scale. As such, anchoring vignettes have been proposed as a suitable methodology for correcting against this difference. We developed anchoring vignettes for the Big Five Inventory-44 (BFI-44) to supplement its Likert-type response options. Based on two samples (Rwanda: n = 423; Philippines: n = 143), we evaluated the psychometric properties of the measure both before and after applying the anchoring vignette adjustment. Results show that adjusted scores had better measurement properties, including improved reliability and a more orthogonal correlational structure, relative to scores based on the original Likert scale. Correlations of the Big Five Personality Factors with life satisfaction were essentially unchanged after the vignette-adjustment while correlations with counterproductive were noticeably lower. Overall, these changed findings suggest that the use of anchoring vignette methodology improves the cross-cultural comparability of self-reported personality, a finding of potential interest to the field of global workforce research and development as well as educational policymakers.

Creativity is the primary driver of our cultural evolution. The astonishing potential of artificial intelligence (AI) and its possible application in the creative process poses an urgent and dramatic challenge for humanity; how can we maximize the benefits of AI while minimizing the associated risks? In this article, we identify all forms of human–AI collaboration in this realm as cyber-creativity. We introduce the following two forward-looking scenarios: a utopian vision for cyber-creativity, in which AI serves to enhance and not replace human creativity, and a dystopian view associated with the pre-emption of all human creative agency caused by the rise of AI. In our view, the scientific community is called to bring its contribution, however small, to help humanity make steps towards the utopian scenario, while avoiding the dystopian one. Here, we present a decalogue of research challenges identified for this purpose, touching upon the following dimensions: (1) the theoretical framework for cyber-creativity; (2) sociocultural perspectives; (3) the cyber-creative process; (4) the creative agent; (5) the co-creative team; (6) cyber-creative products; (7) cyber-creative domains; (8) cyber-creative education; (9) ethical aspects; and (10) the dark side of cyber-creativity. For each dimension, a brief review of the state-of-the-art is provided, followed by the identification of a main research challenge, then specified into a list of research questions. Whereas there is no claim that this decalogue of research challenges represents an exhaustive classification, which would be an impossible objective, it still should serve as a valid starting point for future (but urgent) research endeavors, with the ambition to provide a significant contribution to the understanding, development, and alignment of AI to human values the realm of creativity.