An Agent-based Simulation of the Effectiveness of Creative Leadership - eScholarship

Reference: Leijnen, S. & Gabora, L. (2010). An agent-based simulation of the effectiveness of creative leadership. Proceedings of the Annual Meeting of the Cognitive Science Society, August 11-14, 2010, Portland, Oregon. An Agent-based Simulation of the Effectiveness of Creative Leadership Stefan Leijnen (stefan.leijnen@ubc.ca) Liane Gabora (liane.gabora@ubc.ca) Department of Psychology University of British Columbia Okanagan campus, 3333 University Way Kelowna BC, V1V 1V7, Canada Department of Psychology University of British Columbia Okanagan campus, 3333 University Way Kelowna BC, V1V 1V7, Canada Abstract artificial society is highest when creators dedicate themselves fully to invention. However, as the proportion of creators increases, for optimal results, creators should spend more time imitating. Creative agents amounted to ‘puncture points’ in the fabric of society that interfered with the dissemination of proven effective ideas. In the current investigation we focused exclusively on the extent to which creativity is desirable in a leader, where leadership is equated with having substantial influence over others. Previous results indicated that the presence of a leader accelerates convergence on optimal ideas, but does so at the cost of consistently reducing the diversity of ideas (Gabora, 2008b,c). In these previous simulations, the leader was no more nor less creative than the rest of the agents, referred to here as followers. The goal of the work reported here was to investigate how creative versus uncreative leadership affects the group as a whole. This paper investigates the effectiveness of creative versus uncreative leadership using EVOC, an agent-based model of cultural evolution. Each iteration, each agent in the artificial society invents a new action, or imitates a neighbor’s action. Only the leader’s actions can be imitated by all other agents, referred to as followers. Two measures of creativity were used: (1) invention-to-imitation ratio, i Leader , which measures how often an agent invents, and (2) rate of conceptual change, c Leader , which measures how creative an invention is. High i Leader increased mean fitness of ideas, but only when creativity of followers was low. High i Leader was associated with greater diversity of ideas in the early stage of idea generation only. High c Leader increased mean fitness of ideas in the early stage of idea generation; in the later stage it decreased idea fitness. Reasons for these findings and tentative implications for creative leadership in human society are discussed. Keywords: agent based modeling; broadcasting; creativity; culture; cultural evolution; imitation; leadership. The Modeling Platform Our investigation was carried out using an agent-based simulation referred to as ‘EVOlution of Culture’, abbreviated EVOC (Gabora, 2008b, 2008c). EVOC is an elaboration of Meme and Variations, or MAV (Gabora, 1994, 1995), the earliest computer program to model culture as an evolutionary process in its own right (as opposed to modeling the interplay of cultural and biological evolution). The approach was inspired by Holland’s (1975) genetic algorithm, or GA. The GA is a search technique that finds solutions to complex problems 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. The goal here was to distil the underlying logic of not biological evolution but cultural evolution, i.e. the process by which ideas adapt and build on one another in the minds of interacting individuals. EVOC (as did MAV) uses neural network based agents that could (1) invent new ideas by modifying previously learned ones, (2) evaluate ideas, (3) implement ideas as actions, and (4) imitate ideas implemented by neighbors. Agents do not evolve in a biological sense—they neither die nor have offspring—but do in a cultural sense, by generating and sharing ideas for actions. EVOC (like MAV) successfully models how ‘descent with modification’ occurs in a cultural context. The approach can thus be contrasted with computer Introduction It is widely assumed that effective leaders are creative (Basadur, 2004; Bellows, 1959; Puccio, Murdock, & Mance, 2006; Simon, 1988; Sternberg, Kaufman & Pretz, 2003). Creativity, however, has drawbacks (Cropley, Cropley, Kaufman, & Runco, 2010). For example, a creative solution to one problem may generate other problems, and similarly, a creative solution to one element of a situation may have unexpected negative consequences with respect to other elements. Moreover, time spent creatively finding a solution for oneself is time not spent imitating and passing on solutions already found by others. Previous investigations of the pros and cons of creativity using an agent-based simulation approach addressed the question: in an ideal society, what proportion of individuals should be ‘creative types’ (Leijnen & Gabora, 2009; Gabora, Leijnen & Ghyczy, in press)? The rationale was that 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. The rest can reap the benefits of the creator’s ideas by simply copying, using, or admiring them. After all, few of us know how to build a computer, or write a symphony or novel, but they are nonetheless ours to use and enjoy. Numerical simulations showed that if the proportion of creators is low, the mean fitness of ideas in the

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