A batesonian view on the systemic nature of innovation

Gregory Bateson’s thinking (Bateson 2000, 2002) offers a system theoretical framework of particular relevance for analyzing systemic innovation in the making. In contrast to the systems thinking we found in innovation systems theory and system transition analysis in contemporary innovation studies, Bateson’s approach enables us to inquire the relational, dynamic and open-ended constitution of agency. Here we find

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no ground for developing a comprehensive innovation system model from which we may derive agency as a part-to-whole function. Rather, agency remains a relational effect and intertwined with multiple system dynamics. “The systemic nature of innovation” in a batesonian view has therefore nothing to do with the emergence of higher order entity-constructs like “innovation systems”. Viewing innovation as inherently systemic implies with Bateson that innovation processes are relationally determined in very diverse ways where actor-formations are created and rendered productive without any pre-determinable, functional agency as the structuring principle for interaction. To analyze processes of systemic innovation thus implies that we analyze interactions in the making and the relational dynamics evolving when new actor formations are constructed.

Bateson has recently been introduced to strategy theory (Chia and Holt 2009) and to institutional analysis (Zundell, Holt and Cornelissen 2012) and has been influential across a variety of scientific disciplines, including the work of Deleuze and Guattari where for example Bateson’s process-ontological concept of plateau (Bateson 2000:

113) is a key reference in their conceptualization of processes of becoming taking shape without any reference to an external order or final point of climax. Bateson uses the concept of plateau to designate such processes and Deleuze and Guattari use this in their attempt to conceptualize processes of becoming that follow own intrinsic values and their relational dynamics rather than subordinating processes to externally given references of order (Deleuze and Guattari 2002: 21-22, 158).

The point of departure in all Bateson’s work is the understanding of (the mixturing of) nature and society as inherently systemic and evolving according to system dynamics irreducible to entities. This means that no natural, social or individual phenomenon can be understood in isolation from the relational webs it is intertwined with. In other

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words, everything is a system, any entity is a community: An oak, a forest, a piece of desert, ecosystems, the human body, organizations, cities, etc. are all “communities of creatures” that “live together in a combination of competition and mutual dependency” (Bateson 2000: 434).

The combination of competition and mutual dependency is a key to understand Bateson’s system concept. Any system is living and dynamic in the sense that all of its elements each has a Malthusian capacity without which they would not survive: An inherent expansive capacity of all species or entities in a system. At the same time, all sorts of balancing solutions are at play so that the expansive nature of elements does not become self-destructive. Thus, while one entity in a system may have a strong capacity for expansion, this comes at the cost of other parts of a system which the expanding entity is directly or indirectly dependent on. This is the case for ecosystems in nature where balancing expansive capacities is a normal part of how nature sustains itself in its ecosystems, and it true also for society and social systems. They too live in an “uneasy balance of dependency and competition”. The uneasy balance of systems composed by multiple expansive forces requires a variety of coordination mechanisms – a well-known feature of well-functioning markets, but also a classical insight in organization studies. However, one of the significant challenges of sustaining system flexibility through coordination is the tendency of human endeavors to become still more specialized in problem-solving knowledge and methods (Bateson 2000: 432pp).

Bateson mentions the overall specialization and resulting fragmentation of scientific knowledge production and technological fields of expertise as one area where “system wisdom” gets lost in specialized and inherently partial problem-solving structures.

As an illustration hereof, he uses the example of modern medicine which is organized on the basis of increasingly partial problem-solving purposes (i.e. finding a cure to

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cancer, polio, etc.) which evolves into a systematized absence of knowledge of the body as a “systemically cybernetically organized self-corrective system.” (Bateson 2000: 437). Acknowledging that the discoveries of solutions to specific problems in medicine or any other field of science and technology are indeed extraordinary and valuable, Bateson sustains that they lack insight about the “total systems” especially the system dynamics whereby elements in systems interact and balance competition and dependency relations. The risk of this is that the ever-more specialized problem-solving capacities in science and technology (and in society at large) produce unintended system consequences without having nurtured a capacity to sustain system balances. This might generate all kinds of unintended run away patterns such as collapsing eco-systems during industrialization, reduction or collapsing of flexibility and balancing solutions in organizations when standardized management systems are introduced, and so forth.

Thus, Bateson distinguishes between the purposeful pursuit of solutions in response to specific problems and system wisdom, the latter being systematically excluded when e.g. scientific systems of knowledge production are arranged exclusively according to partial problem-solution purposes resulting in fragmentation and – in the end – a dangerous disturbance of the uneasy balances between the many interacting parts of eco-systems, bodies, and social systems (Batson 2000: 439). To introduce a concept like system wisdom is a challenge, Bateson admits, due to the “almost necessary blindness” that makes human activity possible. “On the one hand, we have the systemic nature of the individual human being, the systemic nature of the culture in which he lives, and the systemic nature of the biological, ecological system around him; and, on the other hand, the curious twist in the systemic nature of the individual man whereby consciousness is, almost of necessity, blinded to the systemic nature of man himself.” (Bateson 2000: 440). System wisdom, therefore, is not a ‘fix solution’

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we can design and implement trapped as we would be in our inevitable partial problem-responses, but rather a complex and systemic composition of balancing act where diverging forces are being incorporated in a variety of ways. To “system wisdom” belongs therefore terms such as complexity, flexibility, divergence, and, as Deleuze might say, multiplicity.

When introducing Bateson’s system thinking in a study of systemic innovation in the making we thus arrive at a fundamentally different system concept compared with the one we find in innovation studies. In a batesonian perspective, change and transitions in how systems work and what explains their evolution has to do with the intensification of patterns of interactions (increasing competition, strengthening of dependencies, etc.) which are systemic in nature and where “agency” is a relational effect that might change and take multiple directions of evolution simultaneously. In a batesonian perspective, the innovation systems framework commits the error of overdetermining patterns of interaction by means of introducing a functional delineation of agency as a parts-to-whole element in the overall “innovation system”.

In contrast to this, Bateson opens up for a more open-ended and dynamic understanding of how agency is relationally constituted over time through its intertwinement with varying system dynamics. In an innovation systems perspective this complexity gets lost due to its commitment to a belief in a higher order system structure which informs agency functions and their possible interactions. In a study of systemic innovation in the making it seems to be significantly more productive to explore a batesonian system perspective on processes of changing interaction patterns due to its complexity embracing framing of how systems work and how they undergo change.

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Having introduced some of the basic elements of Bateson’s system theory (a full introduction would go far beyond the scope of this study), I will in the following focus on his notion of complex systems of presuppositions and his ideas about responses to what he calls transcontextual complexity as a way to develop an understanding of cartographies as systematized habitual patterns of problem-response conventions which – when confronting a new complexity – becomes “stressed” and undergo change in order to solve a variety of relational problems and establish new interaction patterns.