Should Everyone Be Creative?

It goes without saying that creativity is a good thing, and that everyone should be creative. Or does it? Sure, our capacity for self-expression, for finding practical solutions to problems of survival, and coming up with aesthetically pleasing objects that delight the senses, all stem from the creative power of the human mind. But there are drawbacks to creativity.

First, creative people tend to be more emotionally unstable and prone to affective disorders such as depression and bipolar disorder. They have a higher incidence of schizotypal leanings than other segments of the population. They are also more prone to abuse drugs and alcohol, and to commit suicide. Moreover, creative people often feel disconnected from others because they tend to defy the crowd and spend time alone working on creative projects. So there is a dark side to creativity (Cropley, Cropley, Kaufman, & Runco, 2010).

Second, a creative solution to one problem often generates other problems, or unexpected negative side effects that may only become apparent after much has been invested in the creative solution. There is a cultural version of what in biology is referred to as epistasis, where what is optimal with respect to one part depends on what is done with respect to another part. Once both parts of a problem have been solved in a mutually beneficial way, too much creativity can cause these ‘co-adapted' partial solutions to break down.

Perhaps most importantly, in a group of interacting individuals, only a fraction of them need be creative for the benefits of creativity to be felt throughout the group. Uncreative people can reap the benefits of the ideas of ‘creative types' without having to withstand the ‘dark side' of creativity by simply imitating, or admiring them. Few of us know how to build a computer, or write a symphony, or a novel, but they are nonetheless ours to use and enjoy when we please. An excess of creative types all completely absorbed in their own creative process might effectively insulate themselves and block the rapid diffusion of the best ideas.

This opens up some interesting questions. Would it be good for the society as a whole if everyone were highly creative? In order for a culture to evolve optimally, what is the ideal ratio of creators to imitators? And how creative should the 'creative types' be?

My colleagues and I are investigating these questions using a computer model of cultural evolution. The current model's predecessor, Meme and Variations, or MAV (Gabora, 1995), was the earliest computer program to model culture as an evolutionary process in its own right. MAV was inspired by the genetic algorithm, a search technique used by computer scientists to find solutions to complex problems inspired by natural selection. It works by generating a 'population' of candidate solutions (through processes akin to mutation and recombination), selecting the best, and repeating until a satisfactory solution is found.

MAV works using not biological mechanisms but cultural mechanisms. It consists of an artificial society of agents in a two-dimensional grid-cell world. Agents consist of (1) a neural network, which encodes ideas for actions and detects trends in what constitutes an effective action, and (2) a body, which implements their ideas as actions. The agents can do two things: (1) they can invent ideas for new actions, and (2) they can imitate the actions of their neighbors. The computer model enables us to investigate what happens to the diversity and effectiveness of actions generated in the artificial society over the course of successive rounds (called ‘iterations') of imitation and invention. Evolution in the biological sense is not taking place; the agents neither die nor have offspring. But evolution in the cultural sense is taking place through the generating and sharing of ideas for actions amongst agents, which over time leads to more effective actions.

A TYPICAL RUN
Each iteration, every agent has the opportunity to (1) acquire an idea for a new action, either by imitation, copying a neighbor, or by invention, creating one anew, (2) update their knowledge about what constitutes an effective action, and (3) implement a new action. Effectiveness of actions starts out low because initially all agents are just standing still doing nothing. Soon some agent invents an action that has a higher effectiveness than doing nothing, and this action gets imitated, so effectiveness increases. Effectiveness increases further as other ideas get invented, assessed, implemented as actions, and spread through imitation. The diversity of actions initially increases due to the proliferation of new ideas, and then decreases as agents hone in on the fittest actions. Thus MAV successfully models how 'descent with modification' can occur in a cultural context.

EXPERIMENTS
In the earliest version of this computer model (MAV), all agents were equally capable of both inventing and imitating (Gabora, 1995). It was possible to vary the probability that, in a given iteration, they would invent versus imitate. The agents are too rudimentary to suffer from depression or commit suicide, so it is just the other detrimental aspects of creativity listed above that we thought might play a role in these experiments.

What the results showed was that if they all imitated each other all the time, nothing happened at all: everyone watched everyone else and no one did anything. If they all invented all the time, the progress of ideas was slow because they weren't taking advantage of each other's hard work. The optimal ratio of inventing to imitating was about 2:1. Of course, these results hold for just this little idealized world, and they may or may not be generalizable to the world at large. But they do ring true for many people, who say they spend about 2/3 of their time alone in their studio or office immersed in their work, and about 1/3 of their time talking or reading about or studying things related to their creative project.

Creativity Essential Reads

The Myth That Stifles Your Creativity

How to Foster Creative Insight When You Have No Time

We now have a new version of the computer model, called EVOC for EVOlution of Culture. With EVOC we have been looking at how patterns of cultural evolution are affected by things like population density, the presence or absence of leadership, barriers to the free trade of ideas, and (the focus of this blog) how numerous and creative the creative agents are. We conducted experiment that varied, not just the ratio of creators or ‘creative types' to imitators, but also the creativeness of creative types (Leijnen & Gabora, 2009). Each agent could be a pure imitator, a pure creator, or something in between. The pure imitators never invented; they simply copied the successful innovations of the creative agents. The creators were able to invent as well as well as imitate. The percentage of iterations in which they invented varied up to 100%.

The results are provocative. We find that cultural diversity - that is, the number of different actions in the artificial society -- is positively correlated with both the percentage of creators, and their level of creativity. But for cultural fitness or effectiveness, the situation is more complex. So long as the creative types aren't THAT creative, the more of them there are, the better. But when the creative types are HIGHLY creative, the mean fitness of ideas across the society is higher if there are fewer of them. Thus our results suggest that the more creative the creators are, the less numerous they should be. We later conducted a more extensive investigation of these questions employing more detailed and sophisticated analytical methods, and the same trends emerged. (The picture accompanying this blog is a graph from a paper showing the mean effectiveness of ideas across the artificial society is affected by the creator to imitator ratio, and the creator innovation probability.)

Our computer model differs substantially from the real world, so any attempt to extrapolate these results should be taken with a grain of salt. But they do provide food for thought. They support the hypothesis too much creativity causes ‘co-adapted' partial solutions to problems to break down (the ‘don't fix it if it ain't broke' phenomenon). They also support the hypothesis that creative types, while they are a necessary source of novelty, constitute pinholes in the fabric of culture that block the spread of ideas. An iteration spent inventing is an iteration not spent imitating, and imitation is extremely valuable. It's not just a form of free-riding, nor just ‘the greatest compliment', but an indispensable social mechanism that serves everyone. By simply copying the successful innovations of the creative types, imitators serve as a 'memory' for preserving the fittest configurations. So, contrary to popular belief, it might not be best for the society as a whole if everyone were creative.

To find out more about the computer model see https://people.ok.ubc.ca/lgabora/research.htm or check out the references below.

References

Cropley, A., Cropley, D., Kaufman, J. & Runco, M. Eds. (2010). The Dark Side of Creativity (pp. 277-296). Cambridge UK: Cambridge University Press.

Gabora, L. (1995). Meme and variations: A computer model of cultural evolution. In (L. Nadel & D. Stein, Eds.) 1993 Lectures in Complex Systems, Addison-Wesley, 471-486.

Gabora, L., Leijnen, S. & von Ghyczy, T. (in press). The relationship between creativity, imitation, and cultural diversity. International Journal of Software and Informatics.

Leijnen, S. & Gabora, L. (2009). How creative should creators be to optimize the evolution of ideas? A computational model. Electronic Proceedings in Theoretical Computer Science, 9, 108-11.