Who Killed Creativity? How Can We Get Creativity Back?

How Creative People Use Non conscious Processes (white paper)


How Creative People Use Non conscious Processes to Their Advantage

Jason Gallate

The University of Sydney Business School

Cara Wong

School of Psychology, University of Sydney

Sophie Ellwood, R. W. Roring, and Allan Snyder

Centre for the Mind, University of Sydney

Publisher: Routledge
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,
37-41 Mortimer Street, London W1T 3JH, UK

Although contentious, there is evidence to suggest that non conscious processes contribute to creative output, particularly during refractory periods. However, no one has examined whether this break benefit differs as a function of creative ability. To address these issues, this investigation examined Wallas’s (1926) seminal theoretical framework of creativity. More specifically, the most controversial stage postulated by Wallas, the incubation phase, was empirically tested. A regression analysis demonstrated that productivity is significantly increased when creative people activate non conscious processes in off-task or incubation periods. There is ongoing debate about the cause(s) of this incubation effect. This research provides evidence that the incubation effect results, at least partially, from non conscious processing and that it provides greater benefit to more creative individuals. This suggests that highly creative people should be exposed to focus problems=challenges well in advance of objective deadlines, and have freedom to generate solutions outside of structured evaluation times.

Many of the most creative people have been prodigiously productive. Several factors contribute to this productivity at an individual level, and the study of cognitive abilities, expertise, and practice has yielded evidence demonstrating their importance to the quantity and quality of creative output (Ericsson, 2006; Patrick, 1986; Runco, 2004). However, one often overlooked potential contributor to innovation is non conscious processing. Despite widespread recognition of the importance of non conscious processing to creativity, it is underrepresented in research, at least partially because its contribution is inevitably difficult to isolate empirically. This article addresses this problem by investigating the crucial stage of Wallas’s (1926) theory of the creative process. The study reported herein attempted to increase non conscious processing by manipulating the incubation phase in an experimental group.

The authors wish to thank Juliane Conradt and Claire Chang for their help in preparing this article.
Correspondence should be sent to Jason Gallate, University of Sydney Business School, Room 111, Level 1, Economics and Business Building H69, University of Sydney, NSW 2006, Australia. E-mail:

WALLAS’S (1926) THEORY OF THE CREATIVE PROCESS
Wallas’s (1926) stage theory of creativity remains a seminal work despite a relative paucity of empirical verification (for an alternative four-phase model, see Rothenberg, 1996). It is the progenitor of theories of the process of creativity, an emphasis still evident in the work of Kristensson and Norlander (2003) and Smith (2005), among others. Arguably, Wallas was the first to formalize a theory of creativity, in his four-stage model that expounded nonconscious processing as a key contributor to creative output. The stages of his model can be summarized as: (a) preparation, (b) incubation—iia intimation, (d) illumination or insight, and (d) verification.

There are three stages in the model that describe relatively concrete and noncontroversial events: preparation – whereby a problem is isolated, organized, and targeted; illumination -where a solution enters into consciousness; and verification – where the solution is tested and applied. It is, however, the stage in between identifying and solving a problem – the incubation phase – where, according to the model, the real creative work is done. This phase, due to its inaccessible nature, has not been clearly elucidated, yet arguably it contributes more to problem solving than the other phases.

The primary implication of Wallas’s (1926) model is that a person who has identified (or been given a problem) should come up with candidate solutions after a period of time whether they consciously work on the problem or not (operationally—if given a break). In one sense, this is a rather obvious consequence of having been set a problem; one cannot solve a problem that one is not aware of (and solutions do come to problems somehow). However, it does not answer how or why a problem is solved. The interesting part of this implication is that problems are solved even when they are not consciously worked upon.

Anecdotal evidence suggests that incubation effects are almost universally experienced by people who leave work with no conscious intention of toiling on an unresolved problem (often precipitating pressure) and yet have a solution spring to mind apparently unbidden once at home. It has also been verified in the laboratory; of the approximately 50 studies that focus on incubation effects, more than 75% have shown evidence of solutions occurring in at least one of the experimental conditions (Ellwood, Pallier, Snyder, & Gallate, 2009). Interestingly, small groups produce a larger number of incubations (and show higher flexibility) than do individuals (Kristensson & Norlander, 2003).

Crucially, more solutions are produced after a break than working continuously on a problem (Fulgosi & Guilford, 1968). However, the application of this finding has not been systematically introduced to educational or corporate contexts, perhaps because of the negative implications of taking a break. Quantity of solutions is useful, but novelty of creative output is also of crucial importance (Smith, 2005). Therefore, it was fundamental to this experimental paradigm that participants produced novel solutions to a problem that they had already been exposed to after being given a break.

Hypothesis 1: A break from a problem should produce novel solutions when the task is resumed.

Causes of the Incubation Effect
The incubation effect as an observable phenomenon is generally, or at least conditionally, accepted. Its cause however, is highly contentious. Several competing theories explain the occurrence of spontaneous solutions during a refractory period following cessation of work on a problem (Posner, 1973).
One key point of contention between these theories is whether non conscious processes contribute to the effect. Opponents of non conscious processing predominantly argue that it can be explained by removal of functional fixedness or relief from neural fatigue ( Ochse, 1990; Woodworth & Schlosberg, 1954; see also Posner, 1973).

Duncker (1945) was the first to propose that functional fixedness could inhibit access to successful solutions and that time away from a problem could ameliorate this situation. In some variants of functional fixedness theories, such as the Attention Withdrawal Hypothesis (Segal, 2004), non conscious processing is explicitly denied. Segal claimed that in the incubation period, no further work is carried out, but the break offers relief from false organizing principles that previously inhibited solutions.
Alternatively, task specific fatigue or specific neural fatigue theories, initially proposed by Woodworth and Schlosberg (1954), argue that resources necessary for producing solutions in a task (for example, the action potentials of involved neurons) are exhaustible. Thus, a break can reinvigorate these resources, making them available once more to solve the problem at hand. Although we do not dispute the deleterious effects of functional fixedness (or neural fatigue) in problem solving, we hypothesize that non conscious processing also has an experimentally observable effect.

Theories of non conscious processing disagree as to the nature of non conscious processing and its primacy in the incubation effect (see, for example, Seifert et al., 1995; Yaniv & Meyer, 1987). Ellwood et al. (2009) demonstrated that different types of breaks in the incubation period had differential effects on later solutions. They argued that systematic effects beyond relief from functional fixedness or general fatigue are at play because both of these theories predict that a break, semi independent of its content, should be equally effective in producing an incubation effect. However, their study did not rule out the possibility that recovery from task specific (neural) fatigue, as opposed to non conscious processing, may account for the significant remaining variance in the incubation effect. In this article, it is hypothesized that non conscious processing is responsible for this variance and that highly creative people should, therefore, gain greater advantage from non conscious processing than less creative people. Consequently, we designed a test to hold conscious cognitive processes constant while varying the degree of non conscious processing of participants.

This study attempted to manipulate non conscious problem solving by making some participants aware that they would soon be returning to an unresolved problem (a divergent thinking task), thus increasing the likelihood of ongoing problem solving occurring. Other participants were unaware that they would be returning to the divergent thinking task. During the break period, all participants’ conscious attention was engaged on a distracting task, ensuring that any ongoing problem solving was not conscious, but non conscious. To maximize conscious engagement the detractor task was made highly cognitively demanding (placing a high demand on working memory) and an inclusion criterion of greater than 90% accuracy on the detractor task was employed. The participants were also asked if they consciously focused on the detractor problem for 100% of the allotted working=break time and also whether they had thought (even momentarily) about the initial problem during this period. The unaware group should not be aware of any outstanding problem and therefore should only minimally activate non conscious processes.

Hypothesis 2: Participants in the aware condition have higher post break creativity scores than those in the unaware condition, as a result of differential activation of non conscious processing.

Wallas’s (1926) theory is explicit that an incubation phase is a key component of the creative process. This suggests, at the least, that all people rely on non conscious processes for their innovative output to some degree. However, a further implication of the theory is that the most creative are distinguished by the way they utilize non conscious processing in the incubation phase. From this point of view, the degree to which the incubation phase is important to the creative process is consequently the degree to which it is important to the output of highly creative people.

Hypotheses 3: Creative participants benefit more from activating non conscious processes (in the aware condition) than less creative individuals.

 

METHODS

Participants
Eighty younger adults participated in the experiment (28 women, 52 men; M age ¼21.2 years, age range ¼ 18–31 years, SD ¼ 9.3 years). All were first-year psychology students at the University of Sydney, recruited internally as a course requirement for which they received credit. They were naive to the hypotheses. The experiment was conducted in accordance with the Declaration of Helsinki and was approved by the University of Sydney Human Research Ethics Committee.

Tasks and Procedure
Participants performed Guilford’s (1967) Alterative Uses Task (an established measure of divergent creativity) for 2 minutes. The Alternate Uses Task involves divergent thinking, and requires participants to come up with as many uses for a familiar object – in this case a piece of paper – as they can.

Immediately following Guilford’s (1967) task, participants were required to complete an arithmetic task, involving 40 conceptually simple but taxing arithmetic problems (e.g., 2231þ2231), for 5 minutes. Instructions to participants emphasized both speed and accuracy. All participants were completely engaged on the arithmetic task: All scored greater than 90% accuracy (an a priori inclusion criterion).

Immediately after the arithmetic task finished, participants were asked to return to the Alternate Uses Task for another 2 minutes. Participants were randomly allocated into two conditions: aware and unaware. The aware group was instructed that they would return to the divergent thinking task after the arithmetic. The unaware group was not told and were visibly surprised when asked to do the divergent thinking task again.

Although there are several dimensions upon which responses can be scored (e.g., flexibility, originality), the simplest scoring method was selected: ideational fluency (Carroll, 1993), or the number of ideas. Only new answers were counted, as these better exemplify creativity than duplicates.

The most highly creative individuals were considered to be those that scored the most highly on the continuum of unique responses. This continuum was also used as data for the linear regression analysis.

RESULTS
A regression analysis was conducted (data normalized to z-scores) to examine the separate and interactive effects of awareness and baseline creativity level on post incubation performance. The overall regression equation accounted for a large portion of the variance (adjusted R2¼.69, Cohen’s f2¼2.19). Unique contributions of baseline creativity (b¼.57, p<0.001, prep>.99), and awareness (b¼.43, p<0.001, prep>.99), as well as an interaction of creativity and awareness (b¼.42, p<0.001, prep>.99) were found, showing that more creative individuals benefited the most from being aware (see Figure 1). An independent samples t-test was conducted to examine the main effect of being aware versus unaware

Initial Creativity

FIGURE 1 Performance after incubation (number of ideas) for aware and unaware participants as a function of initial creativity level.

on post break creativity scores. This was found to be highly significant, t(1,38)¼3.7, Cohen’s d¼1.02 (p<0.001, prep>.99). This supports the hypothesis that informing a group that they will be doing a task again, before a break, has a beneficial effect on their productivity compared to a group that is unaware.

Notably, no participant thought about the Alternate Uses Task while solving the arithmetic (based on self report). Further supporting this, arithmetic accuracy was near ceiling among all participants and no correlation between post-scores and arithmetic accuracy was found, supporting the contention that all participants were consciously engaged during this period.

DISCUSSION
The results of this study indicate that many novel solutions were generated after a break irrespective of group, supporting a general incubation effect. However, participants in the aware condition produced significantly higher post break creativity scores than those in the unaware condition. Further, the significant interaction effect in the regression analysis is due to more creative participants deriving greater benefit from the incubation period when they were aware that they would be tested again.

This suggests that more creative participants can better utilize non conscious processes, and that the activation of such processes is greatest when a future task is anticipated (or considered important for other reasons). Orlet (2008) has recently emphasized the importance of motivation in incubation effects. One practical implication of this potential synergy (between motivation and incubation) is that presenting people with tasks that have intrinsic (and possibly nonmonetary extrinsic) rewards, well in advance of the time when results will be required, will elicit valuable creative solutions.

This study was informed by Fulgosi and Guilford (1968), who administered a consequences task with a number series incubation phase. They found no significant effect of awareness (with knowledge), possibly owing to a lack of sensitivity in their design, because they used originality as their measure, or alternatively because it was relatively more difficult for participants to generate consequences for abstract hypothetical situations. Notably, their study did not examine the moderating effect of creative ability.

These findings provide evidence that creativity is facilitated by non conscious processes. In our earlier work (Ellwood, Pallier, Snyder, & Gallate, 2009), we provided evidence that breaking functional fixedness and relief from general fatigue could not fully explain incubation. However, we could not distinguish recovery from specific neural fatigue from non conscious processing as the cause of incubation.
This experiment discriminates between these two theories. Both aware and unaware participants performed identical tasks, so should have performed equivalently if recovery from specific neural fatigue was the cause of the incubation effect. That performance was better in the aware group supports non conscious processing as a better explanation. Although the aware group was not consciously working on the problem, it is argued that their knowledge that they would return to the task activated non conscious incubation of further solutions.

The finding that creative people are better able to utilize non conscious processes also accords well with the anecdotal literature on eureka moments. There are many reports of people experiencing highly creative solutions to seemingly intractable problems unexpectedly in periods when they were not explicitly working (for example, Steve Wozniak’s three major breakthroughs in the creation of the Apple II computer; see Livingston, 2007; and many of the outstanding achievements of the physicist Richard Feynman; see Gleick, 1992).

Not only are there numerous accounts of major innovations having resulted from eureka moments, but there is much evidence to suggest that prodigiously creative people appear to be spontaneous (in that they produce solutions at unexpected times and seemingly out of nowhere; Seifert, Meyer, Davidson, Patalano, & Yaniv, 1995). This spontaneity might not be the result of creation ex nihilo, or of innate superior talent, but actually the result of the prodigiously creative person working on outstanding problems consistently at a level below consciousness awareness (Gruber, 1988). One important implication of this phenomenon is that creativity takes time and potentially unconscious work, and that people who wish to be more productively creative should expose themselves to problems but not expect to solve them immediately; rather, they should be comfortable with unresolved problems and open to unexpected = divergent solutions.

Accordance With the Theoretical Literature
Opportunistic Assimilation Theory (Seifert et al., 1995) is also capable of explaining anecdotal accounts of eureka moments. The theory states that reaching an impasse on problems will encode failure indexes in memory that will trigger the problem if the person later opportunistically encounters information that is relevant to solving the problem. Thus, spontaneous cuing from the environment during time away from the problem would produce the same phenomenological experience as a eureka moment. One implication of this theory is to create environments where human networks are creatively stimulating and diverse. Opportunistic Assimilation theory cannot, however, explain the current experimental results. It is improbable that the aware group encountered more environmental cues that led to solutions than the unaware group, as participants were in the same controlled environment of the laboratory.

The other major class of theories of the incubation effect – relief from functional fixedness – cannot account for eureka moments, as, generally, they argue against the existence of non conscious processes. Although unhelpful information or processes may be spontaneously forgotten, the only way that solutions can be arrived at, according to these theories, is by conscious work on the problem. This theoretical approach appears incapable of explaining the current experimental results: Both groups should have forgotten unhelpful information and processes. Indeed, if anything, the aware group should have been more functionally fixed because they knew they would be doing the problem again, diminishing, rather than improving, their post break productivity.

The purpose of this article was not to argue against other explanatory theories, rather, it is argued that, in addition to breaking functional fixedness, recovery from fatigue and possibly complementarily with opportunistic assimilation, non conscious processing provides measurable increases in creative solutions and this effect is experimentally manipulable by factors such as awareness.

Limitations
Despite these contributions, this study is not without limitations. First, the conclusions are circumspect; it has not been proven that non conscious processes are the exclusive cause of the incubation effect; rather, there is added weight to the evidence that it plays a causal role. Similarly, it is not certain that the manipulation increased non conscious processing. It is strongly argued that it is the best explanation of the data, but non conscious processes, by definition (given current technology), are largely unobservable except by their effects, even intra-individually.

Conclusions
Creativity is being increasingly valued across different sectors. Uncovering ways in which creativity can be enhanced may contribute to social, cultural, and economic productivity. Researchers have argued that creativity is becoming an economic imperative (Robinson, 2001), and have provided evidence that it enhances organizational success (e.g., Amabile, 1996; Woodman, Sawyer, & Griffin, 1993), and is a key factor in sustaining competitive advantage (Kim, Min, & Cha, 1999). However, despite the value of creativity to individuals, organizations, and institutions, it has proven difficult to systematically increase. For example, recent research suggests that monetary incentives actually decrease performance on creativity tasks under a range of different conditions and across cultures (Ariely, Gneezy, Loewenstein, & Mazar, 2009).
Programs where time is dedicated to creative gestation have already been successfully initiated (Amabile & Khaire, 2008). These findings suggest that increasing the opportunities for people to non consciously process problems may be a simple yet pragmatic way to increase creativity.

This is especially true for creative people, who stand to benefit from being exposed to a diverse range of unsolved problems and given time to incubate solutions. Relatedly, important problems should be exposed widely to all people, regardless of specialty, because this may trigger non conscious processes that provide surprising and yet crucial solutions.

 

REFERENCES
Amabile, T. M. (1996). Creativity in context. Boulder, CO: Westview.
Amabile, T. M., & Khaire, M. (2008). Creativity and the role of the leader. Harvard Business Review, 86, 100–109.
Ariely, D., Gneezy, U., Loewenstein, G., & Mazar, N. (2009). Large stakes and big mistakes. Review of Economic Studies, 75, 1–19.
Carroll, J. B. (1993). Human cognitive abilities: A survey of factor analytic studies. Cambridge, UK: Cambridge University Press.
Duncker, K. (1945). On problems solving. Psychological Monographs, 58(5), 270.
Ellwood, S., Pallier, G., Snyder, A., & Gallate, J. (2009). The incubation effect: Hatching a solution? Creativity Research Journal, 21, 6–14.
Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In K. A. Ericsson, N. Charness, P. Feltovich & R. R. Hoffman (Eds.),Cambridge handbook of expertise and expert performance (pp. 685 – 706). Cambridge, UK: Cambridge University Press.
Fulgosi, A., & Guilford, J. P. (1968). Short-term incubation in divergent production. American Journal of Psychology, 81, 241–246.
Gleick, J. (1992). Genius: The life and science of Richard Feynman. New York, NY: Pantheon.
Gruber, H. E. (1988). The evolving systems approach to creative work. Creativity Research Journal, 1, 27–51.
Guilford, J. P. (1967). The nature of human intelligence. New York, NY: McGraw Hill.
Kim, Y., Min, B., & Cha, J. (1999). The roles of R&D team leaders in Korea: A contingent approach. R&D Management, 29, 153–166.
Kristensson, P., & Norlander, T. (2003). The creative product and the creative processes in virtual environments. Creativity and Innovation Management, 12, 32–40.
Livingston, J. (2007). Founders at work: Stories of startups’ early days. New York, NY: Apress.
Ochse, R. (1990). Before the gates of excellence: The determinants of creative genius. Cambridge, UK: Cambridge University Press.
Orlet, S. (2008). An expanding view on incubation. Creativity Research Journal, 20, 297–308.
Patrick, A. S. (1986). The role of ability in creative ‘‘incubation.’’ Personality and Individual Differences, 7, 169–174.
Posner, M. I. (1973). Cognition: An introduction. Glenview, IL: Scott Foresman.
Robinson, K. (2001). Out of our minds. Learning to be creative. Oxford, UK: Capstone.
Rothenberg, A. (1996). The Janusian process in scientific creativity. Creativity Research Journal, 9, 207–231.
Runco, M. A. (2004). Creativity. Annual Review of Psychology, 55, 657–687.
Segal, E. (2004). Incubation in insight problem solving. Creativity Research Journal, 16, 141–148.
Seifert, C. M., Meyer, D. E., Davidson, N., Patalano, A. L., & Yaniv, I. (1995). Demystification of cognitive insight: Opportunistic assimilation and the prepared-mind perspective. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight, pp. 65–124. Cambridge, MA: MIT Press.
Smith, G. J. W. (2005). How should creativity be defined? Creativity Research Journal, 17, 293–295.
Wallas, G. (1926). The art of thought. New York, NY: Harcourt Brace.
Woodman, R. W., Sawyer, J. E., & Griffin, R. W. (1993). Toward a theory of organizational creativity. Academy of Management Review, 18, 293–332.
Woodworth, R., & Schlosberg, H. (1954). Experimental psychology (2nd ed.). New York, NY: Holt Rinehart & Winston.
Yaniv, I., & Meyer, D. E. (1987). Metacognition of inaccessible stored information: Bases for incubation effects in problem solving. Journal of Experimental Psychology: Learning, Memory and Cognition, 13, 187–205.