We propose a new model of knowledge creation in purposeful, loosely-coordinated, distributed systems, as an alternative to a firm-based one. Specifically, using the case of Linux kernel development project, we build a model of community-based, evolutionary knowledge creation to study how thousands of talented volunteers, dispersed across organizational and geographical boundaries, collaborate via the Internet to produce a knowledge-intensive, innovative product of high quality. By comparing and contrasting the Linux model with the traditional/commercial model of software development and firm-based knowledge creation efforts, we show how the proposed model of knowledge creation expands beyond the boundary of the firm. Our model suggests that the product development process can be effectively organized as an evolutionary process of learning driven by criticism and error correction. We conclude by offering some theoretical implications of our community-based model of knowledge creation for the literature of organizational learning, community life, and the uses of knowledge in society. Revision to #OS 00-1246RR I.

Victor Frankenstein sought to create an intelligent being imbued with the rules of civilized human conduct, who could further learn how to behave and possibly even evolve through successive generations into a more perfect form. Modern human composers similarly strive to create intelligent algorithmic music composition systems that can follow prespecified rules, learn appropriate patterns from a collection of melodies, or evolve to produce output more perfectly matched to some aesthetic criteria. Here we review recent efforts aimed at each of these three types of algorithmic composition. We focus particularly on evolutionary methods, and indicate how monstrous many of the results have been. We present a new method that uses coevolution to create linked artificial music critics and music composers, and describe how this method can attach the separate parts of rules, learning, and evolution together into one coherent body. "Invention, it must be humbly admitted, does not consist in creati...

Management research on diversity, heterogeneity, dissimilarity, and related concepts of within unit differences in organizations has proliferated in the past decade. However, few clear or consistent findings have emerged. We argue that the nature of these difference-based constructs requires closer examination. Using diversity as an overarching term, we contend that it has three distinctive types: separation, variety, or disparity. Failure to recognize the unique meaning, maximum shape, and assumptions underlying each type has held back theory development and contributed to mismatched operationalizations and research design. After presenting our diversity typology, we present guidelines for conceptualization, measurement, and theory testing, highlighting the special case of demographic diversity.

Selection theory requires multiple, distinct, simultaneously-actualized states. In cognition, each thought or cognitive state changes the `selection pressure' against which the next is evaluated; they are not simultaneously selected amongst. Creative thought is more a matter of honing in a vague idea through redescribing successive iterations of it from different real or imagined perspectives; in other words, actualizing potential through exposure to different contexts. It has been proven that the mathematical description of contextual change of state introduces a non-Kolmogorovian probability distribution, and a classical formalism such as selection theory cannot be used. This paper argues that creative thought evolves not through a Darwinian process, but a process of context-driven actualization of potential.

help with the logistics of this experiment, as well as Robert Klein and his team at Applied Marketing Science, Inc. for their cooperation and suggestions. Idea Generation, Creativity, and Incentives Idea generation (ideation) is critical to the design and marketing of new products, to mar-keting strategy, and to the creation of effective advertising copy. However, there has been rela-tively little formal research on the underlying incentives with which to encourage participants to focus their energies on relevant and novel ideas. Several problems have been identified with tra-ditional ideation methods. For example, participants often free ride on other participants ’ efforts because rewards are typically based on the group-level output of ideation sessions. This paper examines whether carefully tailored ideation incentives can improve creative output. I begin by studying the influence of incentives on idea generation using a formal model of the ideation process. This model illustrates the effect of rewarding participants for their impact on the group, and identifies a parameter that mediates this effect. I then develop a practical, web-based, asynchronous “ideation game, ” which allows the implementation and test of various in-centive schemes. Using this system, I run two experiments, which demonstrate that incentives do have the capability to improve idea generation, confirm the predictions from the theoretical analysis, and provide additional insight on the mechanisms of ideation.

While natural selection is often viewed as synonymous with evolution, it is widely felt to be inadequate as a theory of biological evolution; moreover, historically the concept of evolution has not been limited to biology. We propose an integrative framework for characterizing how entities evolve, in which evolution is viewed as a process of context-driven actualization of potential (CAP). Processes of change differ according to the degree of nondeterminism, and the degree to which they are sensitive to, internalize, and depend upon a particular environment or context. The approach enables us to embed phenomena across multiple disciplines into a broader conceptual framework. It suggests that the dynamical evolution of a quantum entity as described by the Schrödinger equation is not fundamentally different from change provoked by a measurement often referred to as collapse but a limiting case, with only one way to collapse. The biological transition to coded replication is seen as a means of preserving structure in the face of context, and sexual replication as a means of increasing potentiality thus enhancing diversity through interaction with context. The integrative framework sheds light on biological concepts like selection and fitness, reveals how exceptional Darwinian evolution is as a means of ‘change of state’, and clarifies in what sense culture (and the creative process underlying it) is and is not Darwinian.

The motivation for this project is derived from my amazement that changes in human knowledge have been so little analyzed in the economic history literature. For most relevant problems, we tend to assume that knowledge is given and should be regarded, insofar that it is considered at all, a constraint on the maximization problem to be solved. In that approach,

Knowledge and the communication of knowledge are critical for self-sustaining organizations comprised of people and the tools and machines that extend peoples ’ physical and cognitive capacities. Humberto Maturana and Francisco Varela proposed the concept of autopoiesis (“self ” + “production”) as a definition of life in the 1970s. Nicklas Luhmann extended this concept to establish a theory of social systems, where intangible human social systems were formed by recursive networks of communications. We show here that Luhmann fundamentally misunderstood Maturana and Varela’s autopoiesis by thinking that the self-observation necessary for self-maintenance formed a paradoxically vicious circle. Luhmann tried to resolve this apparent paradox by placing the communication networks on an imaginary plane orthogonal to the networked people. However, Karl Popper’s evolutionary epistemology and the theory of hierarchically complex systems turns what Luhmann thought was a vicious circle into a virtuous spiral of organizational learning and knowledge. There is no closed circle that needs to be explained via Luhmann’s extraordinarily paradoxical linguistic contortions.

Cultural psychology, and other social sciences (e.g. cultural anthropology, sociology), seek to document cultural variation, yet have difficulty providing strong empirical tests of explanations for that variation. It is argued here that an effective means of testing hypotheses regarding the origin of, and persistence and change in, cultural variation is by simulating cultural transmission in the lab using certain methods from experimental social psychology. Three experimental methods are reviewed: the transmission chain method, the replacement method, and the constant-group method. Although very few studies have explicitly simulated specific cross-cultural patterns, much potential exists for future investigations. This integration of small-scale experimental simulations and largescale observational or historical data is facilitated by an evolutionary framework for the study of culture, and has a precedent in the biological sciences, where experiments are used to simulate and explain the processes of biological evolution.

this paper, we will describe three main ways of building artificial life models whose inhabitants create music not only for their human listeners, but in some cases for each other as well: converting non-musical behavior into sound, evolving songs to meet some external critic's desires, and letting artificial musicians and their audiences co-evolve in their ersatz world, creating their own musical culture as they go. Using artificial life systems to create music can address a number of goals for people interested in musical creativity. First, for music psychologists and musicologists, it offers a framework within which models of human musical cognition and behavior can be built and tested in a simulated social setting, allowing the exploration of how melody, harmony, and rhythm may emerge through 3 interactions between listening and performing individuals, and of how musical cultures can be built up through repeated such interactions over extended periods of time. Second, it can enable biologists to explore the evolution of the underpinnings of musical behavior in populations of agents (whether simulated humans or other animals) facing a variety of adaptive challenges. Third, for creators of musical tools it provides a new approach to computer-assisted creativity that can produce open-ended variety (and can be connected with compelling images as well). And finally, for musicians it can yield a rich new source of naturally-inspired complexity to draw upon in making their own creative musical pieces. In this chapter we will present examples of musical artificial life systems applied to a number of these goals; others await development by further inspired individuals. 2. Approaches to using Alife models of interacting agents in music To help lay out the space of possibili...