Evolution as Computation: Integrating Self-Organization with - PDF document

Accepted 1/29/11 by the Journal of Institutional Economics for its Special Issue on Evolution and Institutions – uncorrected version Evolution as Computation: Integrating Self-Organization with Generalized Darwinism ERIC D. BEINHOCKER 1 McKinsey Global Institute, London, UK Abstract : Generalized Darwinism and self-organization have been positioned as competing frameworks for explaining processes of economic and institutional change. Proponents of each view question the ontological validity and explanatory power of the other. This paper argues that information theory, rooted in modern thermodynamics, offers the potential to integrate these two perspectives in a common and rigorous framework. Both evolution and self-organization can be generalized as computational processes that can be applied to human social phenomena. Under this view, evolution is a process of algorithmic search through a combinatorial design space, while self-organization is the result of non-zero sum gains from information aggregation. Evolution depends on the existence of self-organizing forces, and evolution acts on designs for self-organizing structures. The framework yields insights on the role of agency and the emergence of novelty. The paper concludes that information theory may provide a fundamental ontological basis for economic and institutional evolution. JEL: A12, B41, B52, D83 Keywords: institutional economics, evolutionary economics, generalized Darwinism, self-organization, information theory, computation, ontology, complex systems. 1 Email: eric.beinhocker@mckinsey.com. The author is grateful to the participants of the “Do Institutions Evolve?” workshop hosted by the Robert Schuman Centre for Advanced Studies, European University Institute, May 2009, in particular Sven Steinmo and David Sloan Wilson. Also Brian Arthur, Geoffrey Hodgson, and three anonymous referees for extensive constructive suggestions. All usual caveats apply. 1

Beinhocker, JOIE draft 19/1/11 1. Introduction By what processes do institutions and economies undergo spontaneous, discontinuous change? How does novelty in such systems arise? For well over a century, social theorists have debated two broad explanatory frameworks for these central questions. The first can be loosely characterized as the evolutionary framework, with historical roots in Veblen, an intellectual trajectory through Nelson and Winter (1982), and a modern incarnation in the work of ‘generalized Darwinists’ such as Hodgson and Knudsen (2006, 2010), Aldrich et. al. (2008), and Stoelhorst (2008). The second can be loosely characterized as the self-organization framework, with historical roots stretching back to Adam Smith, an intellectual trajectory through Hayek and Schumpeter, and a modern incarnation in the work of figures such as Foster (1997, 2000), Witt (1997, 2003), and Weise (1996). In recent years, these two frames have been viewed as in competition, with ongoing debates about the ontological validity and explanatory power of each stance. Geisendorf surveys the modern debate and summarizes (2009: 377): Advocates of such a ‘Universal Darwinism’, like Hodgson and Knudsen (2006), Aldrich et. al. (2008) or Stoelhorst (2008), argue that the mechanisms of variation, selection, and retention are general characteristics of open, complex systems, the economy being one among them. Critics, like Witt, disagree and claim that evolution in economic systems is fundamentally different from biological evolution because economic agents are able to change deliberately (Witt 1992, 2003). Or they claim, like Foster, that the driving-force behind economic evolution is not selection but a self-organized ‘continual, spontaneous generation of novelty’ (Foster 2000: 326) going back to Schumpeter’s ideas. Geisendorf ‘s assessment of this debate is that self-organization is a useful concept, but an incomplete model of institutional and economic change in important respects. The theory “helps to understand why there is an endogenously generated incentive to create novelty. And it describes how novelty might spread,” but “the process of novelty generation remains unclear” (2009: 383). She views Universal (or Generalized) Darwinism as a more fully specified model, acknowledges that care must be taken to avoid analogizing with biology, and attributes much criticism of the theory to misinterpretation. Crucially, she finds no fundamental ontological contradictions between the two stances. She cites Klaes’s (2004: 386) four ontological commitments shared by most evolutionary economists: “that there is change, that this change is caused, that there is a continuity in this change in 2

Evolution as Computation: Integrating Self-Organization and Generalized Darwinism the sense that it has to be explained how a state results from the one before, and that I takes place on several, interrelated levels.” She claims that both the generalized Darwinist and self-organization frames rely on these shared ontological commitments. While Geisendorf sees promise in both approaches, no basic contradictions at an ontological level, and several points of complementarity, she does not attempt to resolve the dispute or integrate the perspectives. This paper will undertake that challenge by introducing a new meta-frame – information theory, and specifically the notion that evolution is a form of computation. Information theory and related theories of computation are well suited to this task as they cut across both evolution and self-organization. As we will discuss, current evolutionary theory views evolution as a computational process – an algorithmic search through a combinatorial space of possibilities. Likewise, theories of self-organization are rooted in thermodynamics, which to modern physics is just another way of talking about information (and vice versa). Concepts such as complexity, order, emergence, and novelty are defined via information theory. One cannot speak about either evolution or self-organization without fundamentally relating back to information. Such an integrated explanatory framework is important to progress the institutional and evolutionary economics agenda. Neoclassical economics has a framework that, after a fashion, takes into account both evolution and self- organization. From Adam Smith’s pin factory, to Marshellian partial equilibrium, von Neumann and Morgenstern’s game theory, Arrow-Debreu general equilibrium, and Lucas’s rational expectations, neoclassical economics has argued that economic self-interest and price signals, mediated by rational agents, lead inexorability to self-organized optimality. And the process by which this self-organized optimality is achieved is the pseudo-evolutionary neoclassical account of market competition. Neoclassically inspired institutional economics shares this integration of self-organization and evolution. For example, transaction cost economics (Williamson 2000) is both a theory of self-organization (again, spontaneous cooperation and coordination via rational self-interest and price signals) and (pseudo) evolution via market competition. As Kingston and Caballero (2009: 161) note: “the process of institutional change envisaged [by transaction cost economics] is an evolutionary one in which competitive pressure weeds out inefficient forms of organization, as originally suggested by Alchian (1950), because those who choose efficient institutions will realize positive profits, and will therefore survive and be imitated.” Neoclassical theory has continued to dominate economics despite decades of evidence on its empirical failings, its lack of explanatory power, its 3