9. Open innovation learning, with a paradigm of co-responsive movement

9.3.1 Proto-learning is enskilling attentionality for selecting an alternative in context

Proto-learning focuses perception on repeatable context markers, that cumulatively builds on experience.³⁴³ With Learning I, choices are revised within an unchanging set of alternative, as shown in Figure 9.3.

Figure 9.3 Proto-learning (Learning I [for]

If a context is misperceived, selection from pre-established responses may result in an error, rather than an appropriate behaviour. A decision may be made initially based upon probabilistic considerations, and later found to be "wrong". When the same problem returns at a later time, a correct selection from the fixed set of alternatives can be made.

Innovation proto-learning is well suited to routinizing and automating: a recurring context is perceived, and an appropriate response is consistent. The context and set of responses are static and tightly coupled. Institutions that operate as machine bureaucracies, e.g. regulatory and justice systems, evolve slowly in ensuring coherence between perceptions and outcomes.

Open innovation learning that continually sweeps in new contexts and ways of responding chafes with proto-learning. Systems optimizing for proto-learning segment and stratify their incoming contexts, e.g. an inpatient clinic referring a case to the emergency room, or door-to-door mail delivery streaming large packages to be transported with a truck.

9.3.2 Deutero-learning is enskilling attentionality for changing the set or sequence of alternatives in contextual change

Deutero-learning focuses on first order changes of context, i.e. the perception of the context of the context. For Learning II, the set of alternatives from which a choice can be made is revised, as shown in Figure 9.4.

Figure 9.4 Deutero-learning (Learning II [for]

"The external event system contains details which might tell" the decision-maker that the set of alternatives from which to choose is insufficient and will lead to an error.³⁴⁴ With Learning II, the capability of learning to learn can be measured by the speed at which the decision maker adapts to the new contingency pattern. Learning II describes "changes in the manner in which the stream of action and experience are is segmented or punctuated into contexts together with the changes in use of the context markers".³⁴⁵

Deutero-learning has been described as including both single-loop learning and double-loop learning, when applied to individuals within an organization and the organization as a whole.³⁴⁶ Based on cybernetic feedback, the first order loop takes ordinary sensory input (e.g. eye, ear, joints) on changes in state, while the second order loop carries information about whether essential variables are or are not driven outside of normal limits (e.g. pain receptors) of changes in field.³⁴⁷ Memories are built, as the system develops.³⁴⁸

A theory of action perspective is not synonymous with deutero-learning. With single-loop learning, "members of the organization respond to changes in the internal and external environments of the organization by detecting errors which they then correct so as to maintain the central features of organizational theory-in-use".³⁴⁹ The name "double-loop learning" is given "to those sorts of organizational inquiry which resolve incompatible organizational norms by setting new priorities and weightings of norms, or by restructuring the norms themselves together with associated strategies and assumptions".³⁵⁰

From the mid-1960s into the 1970s, deutero-learning associated with a theory of action perspective framed the primary concern on organizational effectiveness as "is the organization able to manage change?".³⁵¹ In the 21^st century, aspects of the Argyris and Schon single- and double-loop learning framework have been criticized as "they neglect the aspects of adaptive behavior, context, and relationship that were central to Bateson’s original formulation" for deutero-learning.³⁵² To reset deutero-learning back to its ecological roots, aspects of organizational learning are proposed for relabelling as meta-learning and planned learning in order to escape from terminological ambiguities.³⁵³ The philosophical stance of knowledge distinct from action by Argyris and Schon contrasts to the ecological epistemology by Bateson. Batesonian deutero-learning "aims not so much to provide us with facts about the world as to enable us to be taught by it".³⁵⁴

Innovation deutero-learning introduces new responses as capabilities when a change in context is perceived. In comparison to proto-learning where "sticking with the script" is the standard operating procedure, deutero-learning should reward instances of innovating to correct errors of omission. Decision-makers are put into a double-bind between behavior proven successful in a prior context, and breaking "that pattern to deal with the class of such episodes".³⁵⁵ Customer-centered service should allow clients to not only select from the posted menu of popular choices available, but also to embrace variants within the capabilities of the organization.

Open innovation learning is entailed by deutero-learning as necessary, but not sufficient. A private sourcing organization shows the condition of necessity in exhibiting deutero-learning: it sees itself not satisfying the changing context of its stakeholders, and then adds a new response to its repertoire. The organization is able to perceive and operate within the contexts that have accumulated in its experience, but would be challenged to cocreate a distinctly different context for itself. Self-awareness of these limits might lead a successful organization to segment contexts for defined units that could spin off resources to pursue incompatible opportunities.

9.3.3 Trito-learning is enskilling attentionality for changing systems of alternatives in meta-contextual change

Trito-learning focuses on second order changes of context, i.e. the perception of the context of the context of the context. For Learning III, the system of sets of alternatives from which a choice can be made is revised, as shown in Figure 9.5.

Figure 9.5 Trito-learning (Learning III [for]

"Learning III is likely to be difficult and rare in human beings".³⁵⁶ Learning II occurs upon the improvements occurring with successive reversal of facts from prior Learning I (i.e. a double-bind).³⁵⁷ Learning III throws "unexamined premises open to question and change" by resolving contraries generated at level II.³⁵⁸ Trito-learning may therefore either collapse much of that which had previously been learned, or lead to schizophrenia or psychosis.

In comparison with other conceptualizations of learning, four distinct features are highlighted in trito-learning: (i) skepticism about the instrumental pursuit of Learning III; (ii) emphasis of Learning III as beyond language; (iii) the recursive organization of the levels of learning (as depicted in a hierarchy redrawn at Figure 9.6) (Tosey, Visser, and Saunders 2012, 300), and (iv) the prevalence of risk in Learning III.

Figure 9.6 Bateson’s levels arranged as a recursive hierarchy [Tosey, Vissers and Saunders (2012)]

With recursive feedback loops between Learning I, Learning II and Learning III, the higher order levels are not necessarily more desirable than lower orders.³⁵⁹ Transformational learning introduces risks that could lead to breakdowns and unintended consequences.

Innovation trito-learning introduces new systems of sets of alternatives responses. A system of changing context X (i.e. ΔX) with the response set {x1, x2, x3} could have new alternatives added, while a contemporaneous system of changing context Y (i.e. ΔY) with response set {y1, y2, y3} adding alternatives, as well. Private sourcing can be seen as a system of context with a set of responses, while open sourcing is another system of a set of responses. Perceiving (i) private sourcing and (ii) open sourcing not as coupled but both independently changing can be handled as parallel deutero-learning, rather than trito-learning.

Open innovation learning is entailed by trito-learning as sufficient, but not necessary. Since the Batesonian model of learning is hierarchical (or recursive), attaining trito-learning requires the lower level of deutero-learning. Open sourcing while private sourcing requires, by definition, taking successive risks of trito-learning as a series of positive double-binds.³⁶⁰ Innovation learning could be ascribed to one-way flows (e.g. commercial ventures that privately extend research from public universities); open innovation learning more fully engages in two-way flows where an organization not only responds to changing contexts, but works towards changing those contexts (e.g. participating in advancing open standards while developing private sourcing implementations).

9.3.4 Hypothesizing for a theory of open innovation learning-for

A hypothesis for a normative theory for OIL within a paradigm of co-responsive movement can be constructed from the three learnings-for:

• Hypothesis: Open innovation learning-for layers enskilling attentionality for (iii) changing systems of alternatives in meta-contextual change (trito-learning), over (ii) changing the set or sequence of alternatives in contextual change (deutero-learning), and (i) selecting an alternative response in context (proto-learning).

Testing this normative theory for OIL could take place in the three emerging cases outlined earlier. The rise of (i) polycentric governance, (ii) the Internet of Things, and (iii) cognitive computing, each provide salient contexts to which enskilling attentionality on proto-learning, deutero-learning and trito-learning are combined and weighed against each other.

9.4.1 Learning-by-doing is weaving flows in form-giving in experiencing

Learning-by-doing has largely studied from two perspectives: organizational (sometimes extended to industry or nation), and personal (drawn from social psychology traditionally, and from anthropology more recently).

Organizational learning-by-doing has been researched in studies on the "improvement curve", including "learning curves", "progress curves" and "experience curves". The seed for this idea originates from an 1936 empirical report on labor production costs associated with producing the same model of aircraft in varying quantities. The factors from the original drawings are simplified in Figure 9.7. The declining number of labor-hours became central to cost planning in the U.S. Air Force during and after World War II.³⁷⁰

Figure 9.7 Labor cost percentages [Wright (1936)]

The label "learning-by-doing" was described by Kenneth Arrow in 1962, in dealing with the difficulty of measuring the quantity of knowledge, as it was obviously growing over time. This research attempted to formalize "an endogenous theory of the changes in knowledge which underlie intertemporal and international shifts in production functions".³⁷¹ Arrow established two points: (i) "Learning is the product of experience"; and (ii) "Learning can only take place through the attempt to solve a problem and therefore only takes place during activity". This ascribed technical change to the experience gained in the action of production.

Systematic studies of factors contributing to performance improvement associated with production experience are scarce. The major sources of improved efficiency have been proposed as (i) changed contexts of productions; (ii) embodied technical change; and (iii) improved organization and proficiency.³⁷²

Learning-by-doing, when defined as problem solving, includes trial-and-error – specifically, a process of trial, failure, learning, revision and re-trial. Ill-structured problems are solved by first generating one or more alternative solutions, testing against requirements and constraints, revising and refining into an acceptable result. Under stable use conditions, learning-without-doing is feasible. In changing use environments, learning-without-doing fails when unanticipated and unpredicted field issues arise.³⁷³

A learning curve where experience is gained in production assumes that knowledge acquired is cumulative and persists through time. Fostering learning (e.g. from one factory shift to another) has been modelled as knowledge acquisition, retention, carry forward (i.e. embedding) and transfer.³⁷⁴ Organizational forgetting "undoes" learning-by-doing leading to firms become more aggressive rather than less aggressive. A winning firm is able to build advantage by moving down its learning curve, setting up a rival to forget and slide back up its learning curve.³⁷⁵

Personal learning-by-doing has been a central concern in the fields of education and pedagogy. The book Experience and Education published by John Dewey in 1936 is recognized as a landmark, although the prescriptions for moving from subject matter organization to experiential learning have rarely become institutionalized.

From a cognitive science foundation, Roger Schank writes: "Learning is the accumulation and indexing of cases and thinking is the finding and consideration of an old case to use for decision-making about a new case. Critical to all this is the process of expectation failure and explanation. To make thinking beings, we must encourage explanation, exploration, generalization, and case accumulation".³⁷⁶ Learning-by-doing has human beings deciding what to do (and understanding what others do) through "scripts … intended to account for the human ability to understand more than was being referred to explicitly in a sentence by explaining the organization of implicit knowledge of the world that one inhabits".³⁷⁷ Skills are sets of micro-scripts for situations, in which actions culminate in a desired conclusion. In addition to scripts, productive members of societies will have learned three universal processes of (i) communications, (ii) human relations, and (iii) reasoning. "Learning by doing, when one is talking about processes, means inventing for oneself strategies that work within the processes that one is involved in". Scripts may fail when a new situation is encountered, leading to the potential for acquisition of a new case. "People acquire new cases because the old script they were using didn't work all that well".³⁷⁸

For the applied behavioral analysis community, learning-by-doing is a scientific principle.³⁷⁹ "Learning by doing means learning from experiences resulting directly from one’s own actions, as contrasted with learning from watching others perform, reading others’ instructions or descriptions, or listening to others’ instructions or lectures".³⁸⁰ In contrast with classical psychology where "direct experience" mean mental contact with mental phenomena by introspection, behavioral analysis means "sensory contact with the results of doing". Everyday life show discovery preferred over instruction, with trial-and-error often preferred over reading a user’s manual, and learning-by-training (doing until the subject exhibits stimulus equivalence) yielding more correct responses than learning-by-instruction. The Renaissance saw practical experience preferred over book learning from the Scholastic era, particularly in politics (following Rousseau), language acquisition, and facilitating the asking of good question. Practice means "doing", not repetition, in the practice-theory-practice dialectic advocated by Karl Marx, Lev Vygotsky and Mao Zedong. Effective practitioners (e.g. medical professionals) bridge the gap between practice and theory by basing their procedures not only on direct experience, but also on theoretical principles.³⁸¹ The test of truth through proof upon practice (or "the proof is in the pudding" challenges scientist with doing concepts operationally, rather than just getting a mechanistic agreement.

The organizational and personal aspects of learning-by-doing have been brought together in the literature on communities of practice. Learning-by-doing has been developed into a larger theory of situated learning, developed through studies of craft apprenticeship with historical and culturally specific realizations. Legitimate peripheral participation sees "learning as an integral and inseparable part of social practice", more incompassing than "conventional notions of ‘learning in situ’ or ‘learning by doing’ for which it was used as a rough equivalent".³⁸² A social learning theory of learning was further developed through study of an insurance claim processors, formalizing concepts on meaning, community, locality and identity.³⁸³

Innovation learning-by-doing appreciates the accumulation of experience in both the organizational and personal senses. Trial-and-error with innovating has to be experienced first-hand; watching and copying an innovator may replicate behaviours after the fact, but is unlikely to lead to innovation mastery. Innovating is learned through "understanding in practice" rather through a "culture of acquisition".³⁸⁴

Open innovation learning-by-doing opens up the situatedness of practices to a world beyond the bounds of a single organization. This allows individuals to "grow into knowledge" rather than having it handed down to us".³⁸⁵ The role of the facilitator or educational leader should be "to establish the contexts or situations in which we can discover for ourselves much of what they already know, and also perhaps much that they do not". A community of practice should collectively have members with anticipatory foresight to guide the less-experienced towards a path of success.³⁸⁶

9.4.2 Learning-by-making is weaving flows in form-giving in constructing

Learning-by-making is associated with the constructionism of Seymour Papert, "building relationships between old and new knowledge, in interaction with others, while creating artifacts of social relevance".³⁸⁷ Research into constructionism in the 1980s and 1990s focused on instructional environments (e.g. assembling LEGO kits, building microworlds with the Logo programming language).

In recent years, the field of critical making has emerged with the rise of digital technologies combined with physical microcontrollers (e.g. Arduino). ³⁸⁸ The importance of actually making things draws on three aspects of constructionism: (i) incorporating the emotional dimension of learning, as new understanding is endowed with a positive, affective tone; (ii) using transitional objects to connect body knowledge to more abstract understandings; and (iii) encouraging "messing about" in order to overcome a rigid style of work, and allow new perspectives to emerge. Critical making aims "to make concepts more apprehendable, to bring them in ways to the body, not only the brain, and to leverage student and researchers personal experiences to make new connections between the lived space of the body and the conceptual space of scholarly knowledge.

Learning-by-making and creativity can be coupled as sociomaterial creativity.³⁸⁹ This a break from the dominant individual-oriented creativity models in psychology where creativity either (i) originates from an individual’s internals sources, or (ii) represents a rebellion against present and existing social structures. A living theory of creativity is based on three sociomaterial conditions: (i) creativity is an everyday phenomenon resulting in continual processes of ‘‘making the world", rather than reserved for unique geniuses or historic personalities; (ii) human beings and material tools change constantly "in the making" with constant improvisation, rather than reserving creativity for an intellectual moment, and (iii) we work in contact with, and resistance from the materials in a relational creativity. Sociomaterial creativity sees a generative renewal in improvisation that can be collective, where materialized starts from tradition with emotion and anticipation of the new.

Maker-centered learning has recently been encouraged with the advent of makerspaces. These venues share an ethos of multidisciplinary engagement and innovation.³⁹⁰ Learning arrangements were hybrids of participatory culture with pedagogical structures found in more formal studio-based settings. Learning is embedded in the experience of making. "These spaces value the process involved in making—in tinkering, in figuring things out, in playing with materials and tools".

Innovation learning-by-making emphases the two-sidedness of materiality: (i) the artifactual construction of things, and (ii) human life projects that give an artifact its meaning. ³⁹¹ Making a novel product or process can be labelled as an inventing; making a change in predisposed practices defines the adopting of an innovation. With improvisation seen as an everyday phenomenon, learning-by-making relies partially on the knowledge gained through experience, and partially on discovery at hand of the materials in the process of form-giving.

Open innovation learning-by-making creates novel understanding amongst members of a community of practice, often transcending organizational boundaries. Unencumbered access to materials and knowledge unchains accumulating collective experience in making.³⁹² An open learning-by-making community coalesces creativity through (i) unimpeded acceptance in joining an interest; (ii) tolerance of a variety of styles and approaches; and (iii) hands-on advancement of skills working with materials.³⁹³

9.4.3 Learning-by-trying is weaving flows in form-giving in co-configuring

Learning-by-trying appears in the struggle to get configurational technology assembled into a working system: "improvements and modifications have to be made to the constituent components before the configuration can work as an integrated entity".³⁹⁴ Trying combinations of components involves micro-processes akin to "evolutionary models of speciation", rather than the epidemiological models of population growth where the "diffusion of the same technological entity in essentially unchanged form across a sector or the economy as a whole".³⁹⁵ Success requires generic knowledge embodied in skills and practices gradually formed over a period of time, plus local practical knowledge contingent onto the particulars at hand. Users "constitute the only available repository of the local knowledge component which might be essential for achieving successful implementation". Studies of such new technology implementations (e.g. customizing a specific instance of software) reports high failure rates.

Co-configuration of products and services reorients learning-by-trying less on technology and more on ongoing social interactions. "The work of co-configuration involves building and sustaining a fully-integrated system that can sense, respond and adapt to the individual experience of the customer".³⁹⁶ A product or service provider is able to reconfigure its organization to respond to customer requests through a mass customization design of dynamic product change and stable process change.³⁹⁷ Mass customization requires designing a product at least once for each customer.³⁹⁸ Co-configuration "never results in a ‘finished’ product, but instead develops a living, growing network between customer, product and company. The capability for a product to continuously adapt reliability to customer needs requires continual learning.³⁹⁹

Learning-by-trying can be differentiated as an exploration for new knowledge.⁴⁰⁰ Learning constructs (i) architectural knowledge in a context of experimentation, with incremental exploration of a given nature of an object and given activity to be mastered; or (ii) dialogical configuration knowledge in a context of transformation, with radical exploration of a newly emerging nature of an object and a new activity to be mastered.⁴⁰¹ The incremental exploration of Engeström lines up with the mass customization of Victor and Boynton; the radical exploration (also labelled as expansive learning) lines up with co-configuration. Learning-by-trying has two challenges: (i) learning the co-configuration work itself on collaboration and infrastructures; and (ii) learning constantly in ongoing interactions between the user, product/service and producers.⁴⁰² Professional practices for multi-agency working are characterized by distributed expertise where "coming to know the potential networks or ‘trails’ of colleagues" may be a necessary precursor to success.⁴⁰³

Learning-by-trying occurs in an episodic manner within windows of opportunity, triggered either by discrepant events or by new discoveries on the part of users.⁴⁰⁴ This spiky timing of learning contrasts to depictions of the learning curve as continuously improving.⁴⁰⁵ Learning-by-trying can be applied to ill-structured problems with problem-solving including "trial and error (or more precisely, trial, failure, learning, revision and re-trial) as a prominent feature".⁴⁰⁶ Taking advantage of a disruption, experimentation is "more likely to occur and significant changes more apt to be implemented immediately following introduction than at any later time, despite ongoing problems or additional in sights that might be gained over time".⁴⁰⁷ Problem discovery, particularly identified by operators in the field at deployment of new technology into the field, has been recognized as a specific form of learning in pattern recognition called either interference finding and templating. ⁴⁰⁸ Both interference finding and templating are described as "a form of pattern recognition".⁴⁰⁹ Templating is related to "a means for characterizing the fit between form and context", which Christopher Alexander labelled as "configuration".⁴¹⁰ Learning-by-trying may not only result issues of fit when a design is deployed in the field, but may also surface pre-existing conditions not originally perceived from a system that has been functioning for some time. Renovators say that "you never know what’s behind a wall until you break through".⁴¹¹

Innovation learning-by-trying raises the importance of the situated nature of adaptive learning.⁴¹² Physical setting is important in four ways: (i) technical experts and users tend to see different thing in any given setting; (ii) skills that expert problem solvers can apply to a problem depend on where they stand, and the resources available there; (iii) the physical setting affects unwritten rules and assumptions guiding behaviour, including interactions with others; and (iv) problem solvers learn not only in physical settings, but also through alternation between different physical settings. Innovation programs that are hands-on will have the episodic opportunity to more rapidly pivot direction on learning.

Open innovation learning-by-trying as co-configuration requires not only architectural modularity, but also dialogical integration. Trying multiple alternative assemblies presumes access both the physical parts and knowledge networks. Much of commercial business (as well as government-provided services) is designed an asymmetric "Read/Only" culture where production is professionalized and concentrated.⁴¹³ A remix culture has "Read/Write" privileges, where multiple parties can engage in co-configuration. That engagement could lead to open standards for cases where interests of a majority of partners are shared, and forked directions for parties with specialized needs.

9.4.4 Hypothesizing for a theory of open innovation learning-by

A hypothesis for a normative theory for OIL with a paradigm of co-responsive movement can be constructed from the three learnings-by:

• Hypothesis: Open innovation learning-by layers weaving flows in form-giving through (iii) learning-by-trying, over (ii) learning-by- making, and (i) learning-by-doing

Testing this normative theory for OIL could take place in the three emerging cases outlined earlier. The rise of (i) polycentric governance, (ii) the Internet of Things, and (iii) cognitive computing, each provide salient contexts to which weaving flows in form giving through learning-by-doing, learning-by-making and learning-by-trying are combined and weighed against each other.

9.5.1 Learning-alongside is agencing strands of polyrhythmia entangling eurhythmia

Polyrhythmia and eurhythmia are appreciated by living beings founded on the experience and knowledge of the living body, depicted in Table 9.1.

Polyrhythmia is an alignment of multiple organic repetitions in time and space, beyond metrics of mechanical regularity. Within polyrhythmia are three fundamental concepts:

• isorhythmia, the equality of rhythms, in an identity of temporalities;
• eurhythmia, an association of heterogeneous rhythms, as normal in a healthy living body; and
• arrhythmia, a breaking apart of rhythms, altering and bypassing synchronization.

Isorhythmia is present in symphonic and orchestral music⁴¹⁹, but otherwise is rare. Eurhythmia is present in living bodies as diverse rhythms in a metastable equilibrium⁴²⁰ unified with the environment. Arrhythmia appears as functional disruption than can manifest into illness and progress into morbid and fatal disorder.

Rhythm is “a pattern of movement, characterized by the recurrence at a regular frequency of some pulse in a process or system”⁴²¹. Rhythm exists in the natural world⁴²², and perceiving rhythms are fundamental to the human experience. The sciences and the arts can both engage with rhythm⁴²³, in a unity of the perception of immediate experiences, and in symbolic form that can be internalized by others. Live creatures experiencing rhythm enjoy the order of repetition, but also demand variety as a stimulus⁴²⁴. Rhythm is present both in experiencing music (i.e. in time) and in experiencing colours (in space)⁴²⁵.

Philosophically, rhythm can be a foundation for moving from the dyadic (i.e. two terms) to the triadic⁴²⁶ (i.e. three terms). In a dialectical analysis of music as melody-harmony-rhythm, rhythm has been de-emphasized⁴²⁷. Rhythm is understood within the body of any human (or creature) and in music, and has been proposed for an understanding of space-time-energy⁴²⁸. Where there is a place, a time, and an expenditure of energy, rhythm provides an inductive framework⁴²⁹ with (i) repetition; (ii) linear and cyclical processes; and (iii) birth-to-end life cycles.

In 2016, an essay in The Philosophers’ Magazine asked “Why do philosophers have no rhythm?”⁴³⁰, pointing out that the western classical canon emphasizes the tonal over the rhythmic. An edited volume on “The Aesthetics of Rhythm” based on a 2014 workshop supported by the British Society of Aesthetics is forthcoming.⁴³¹

Eurhythmia may include higher order rhythms that dynamically adapt a system to naturally change with its environment, and/or interventions that will enfold health.⁴³² In wellness, the diverse rhythms can normalize each other towards an everyday state of health.⁴³³

Polyrhythmia is demonstrated socially in the music of the rock band, The Police. The renowned trio of drummer Stewart Copeland, bassist Sting and guitarist formed in 1977, and stopped touring after an exhausting 1983-1984 Synchronicity world tour.⁴³⁴ For the 2007-2008 world tour, the band reformed as a trio with greater maturity, making history both musically and economically.⁴³⁵

The Police fused progressive rock styles with reggae beats, playing in sophisticated rhythms that neither punk bands nor rock bands find natural. Most groups struggle to be isorhythmic and coherent on a unified pulse. The 1978 hit song “Roxanne” originally written as a bossa nova⁴³⁶ became a hybrid of tango and reggae in a rhythmic ambiguity. The Police were able to mesh in rhythm, seeking a groove that is “in the pocket”⁴³⁷. Simultaneously dealing with a variety rhythms surfaces metric conflict⁴³⁸. Sophisticated rhythmic interplay⁴³⁹ is uncommon in garage bands, however, and requires a higher level of expertise.

Any amateur musicians who attempt to replicate the feeling and technique of The Police readily discover how intricate and difficult the arrangements really are. The polyrhythmia of a band playing a bass behind the beat (i.e. microtiming as late) as drums are ahead of the beat (i.e. microtiming as early) with guitar and vocals are layered generally leads to rushing or dragging perceived as arrhythmia⁴⁴⁰

Innovation learning of polyrhythmia alongside eurhymthia challenges the balancing of "what is inside the head" with "what the head is inside".⁴⁴¹ Philosophical perspectives on time contrast event time (as subjective) with clock time (as objective), and alternatively more formally as chronos and kairos.⁴⁴² Progress includes the unfolding of life both inwardly and outwardly.⁴⁴³

Open innovation learning of polyrhythmia alongside eurhythmia characterizes open sourcing while private sourcing is a rhythmic construction⁴⁴⁴ that was new in 2001, becoming commonplace as a style by 2011. Open sourcing operates with a rhythm that is different from private sourcing. The organization that is successfully open sourcing while private sourcing has to maintain a polyrhythmic proficiency. This appreciation of polyrhythmia could be a promising first step on a trajectory from the science sciences towards an aesthetics for systems.

9.5.2 Learning alongside is agencing strands of regenerating entangling preserving

Regenerating and preserving are concerns of continuity in the natural and artifactual material world that may be influenced by human activity,⁴⁴⁵ depicted in Table 9.2.

In both living and non-living contexts, the distinctions may be more precisely described as regenerating as nature and preserving of form. These concerns can be related to evolution of philosophy from (i) the wilderness preservation of Ralph Waldo Emerson and Henry David Thoreau, popularized by John Muir; (ii) resource management articulated by Gifford Pinchot with private conservation organizations such as the Sierra Club, and (iii) the ecosystem management and sustainable development of Aldo Leopold.⁴⁴⁶ Muir advocated preservation, writing of the beauty, the physical and mental promotion, and spiritual redemption associated with lengthy wilderness sojourns.⁴⁴⁷ Pinchot criticised preservationists as "locking up" resources, and led conservationists take a scientific approach to the development of natural resources, and a fair distribution of benefits through regulated markets.⁴⁴⁸ Leopold saw conservation as "harmony-with-nature" in sustainable development with "the initiation of human economic activity that does not significantly compromise ecological health and integrity; and ideally economic activity that might positively enhance it".⁴⁴⁹ In order for wilderness area to remain viable, ecosystem management may require invasive procedures (e.g. prescribed burns) to maintain the mix of species that compose them.

Preserving of form in the global world order – across natural systems and human systems – requires maintaining relations in governance of amplifiers of choice associated with the market economy and development of technology.⁴⁵⁰ When governance fails to maintain a system within some critical limits with stability, enablements and constraints can spin off into an irreversible change towards disorder. In a bureaucratic organization, preservation of form sees "the protection or preservation of the premises of decision, including those supporting the control of the decision system, and not simply to the preservation of the organization’s structural arrangements, although these are interrelated".⁴⁵¹ The appearance of rationality amongst decision makers as symbolic use rather than instrumental use supports bureaucratic control with risk aversion.

Regenerating as nature is related to distinctions between making and growing. Human beings "produce society in order to live – and in doing so, ‘create history’".⁴⁵² Five kind of materiality can be distinguished, "depending upon the manner and extent to which human beings are implicated in their formation", as shown in Table 9.3.

The five kinds of materiality include: (i) that part of nature which is wholly untouched by human activity; (ii) the part that has been changed on account of the presence of humans, but indirectly and unintentionally; (iii) the part that has been intentionally transformed by human beings and that depends upon their attention and energy for its reproduction; (iv) the part that comprises materials that have been fashioned into instruments such as tools and weapons; and (v) the part we conventionally call the "built environment" (e.g. houses, monuments).

In the middle kinds of materiality, two themes emerge. Firstly, people do not "literally make plants and animals, but rather establishes the environmental conditions for their growth and development". Secondly, "growing plants and raising animals are not so different, in principle, from bringing up children". The difference between growing plants, raiding animals and bringing up children is in the relative scope of human involvement in establishing the conditions for growth. There is a "temporal interlocking of the life-cycles of humans, animals and plants, and their relative durations".⁴⁵³ While the orthodox Western view extends making from inanimate things to animate beings, growing can be extended in the reverse direction from animate to inanimate.

The temporal interlocking of life-cycles between human beings and nature shows up in the "second life of trees" in the traditional regenerative practices of foresters in a mountainous region of Japan.⁴⁵⁴

The traditional practice was this — that the forester would plant, and grow, and look after the trees for generations. Something like 30 years went from the conifers, so you planted the tree, you attended, you looked after it to make sure things well with it. And once a suitable period had elapsed you would cut it down. And then having cut it down, you would use those trees to make timbers for your house. And then, so, during the first 30 years of the growth of the tree, you’re looking after the tree. In the next 30 years the tree has become a house timber and it’s looking after you. You and your family living inside the house. And they call this the second life of trees.

So, the first life is when the tree is growing in the ground, and when and you’re looking after it. The second life is when the tree is in your house and it’s looking after you. That also lasts about 30 years during which time you’ve planted a new set of trees. They’ll be harvested and they’ll replace the old timbers as they begin to go rotten.

Perhaps, by that stage — and so that way — you’ve got a perfect interlocking of tree lasting and human lasting — that is, tree life cycles, and human life cycles — that are kind of in phase with one another, and carrying on indefinitely through time.

That was all fine, until the conservationists came along and said you can’t cut those trees! These trees are part of nature! We need to preserve nature! So they denied the trees the possibility of their second life. They just stood there getting older and older in the ground, until they eventually drew out, as conifers do, sort of died down. They died on their legs, and died in their roots, and became dead trees standing in the ground.

And the foresters didn’t have the raw materials to build and restore their houses. So what happens now is we have ancient trees and concrete houses, in the name of preservation, and thinking of sustainability in terms of the preservation of form, rather than the continuation of life cycles. (Ingold 2016, sec. 35m55s-38m12s)

A challenge in sustainability (and conservation, more precisely) is an orientation towards steady states, rather than with movement. Conservationists often think more in terms of projecting the past into the future, whereas an alternative way of thinking about the future is anticipating the regenerating of nature.

Innovation learning of regenerating alongside preserving leads to the cross-appropriation of understandings of the world across domains. Preserving our civilization dates back to ancient times, with enduring built environments displacing nomadic shelters, and the industrial revolution of the 19^th century advancing technologies to augment manual labour. Regenerating underlies much of biomimcry as "innovation inspired by nature", where the biology of living things is mimed by human beings.⁴⁵⁵

Open innovation learning of regenerating alongside preserving appreciates that some phenomena have life cycles with circularity, while others are rare or singular anomalies that serendipitously emerge. Open sourcing projects that welcome the injection of capital and resources from commercial partners can gain produce the critical mass of vitality. Private sourcing derivatives and forks may eventually lapse into neglect due to unfavourable revenue-cost trends, yet open sourcing projects may see new generations through self-sustaining community interests.

9.5.3 Learning alongside is agencing strands of less-leading-to-more entangling more-leading-to-more

Less-leading-to-more entangling more-leading-to-moreare two prospective mindsets for moving an innovation forward, as depicted in Table 9.4.

The emphasis of "leading-to" adds a dimension of foresight in time. A layman might describe less-leading-to-more as "working smarter", as compared to "more-leading-to-more" that "builds on success" through linear scaling.

The more popular "less-is-more” phrase comes from two related fields: rhetoric, and architecture.

From rhetoric in the 16th century, meiosis⁴⁵⁶ has been an understatement, frequently ironic, a figure of speech by which something is intentionally presented as smaller or less important than it really is. As meiosis in 1855, less is more was published in a Robert Browning poem “Andrea del Sarto (called The Faultless Painter)”⁴⁵⁷, a monologue from a technically gifted artist to his unfaithful wife. Andrea produced paintings with “no sketches first, no studies” to support her lifestyle, while dreaming of ascending to “the heaven” of superior contemporaries Raphael, Michelangelo and Leonardo DaVinci. Andrea recognized ”there burns a truer light of God in them”.

In architecture, the original inspiration for less-is-more came to Mies van der Rohe under the supervision of Peter Behrens⁴⁵⁸ during the construction of the AEG Turbine Factory in 1907-1910. In contrast to his early work in the decorative arts focused on organic allusions, uniqueness, craft and patronage by the elite, Behrens moved into a style of architecture and design⁴⁵⁹ that could be generalized for the middle class and modernized into industrial manufacturing. Form was simplified in shapes of spheres, cubes, cylinders and hexagons, exploiting the attributes of the new industrial materials of glass, steel and reinforced concrete. When Mies designed the west courtyard elevation of the Turbine Factory, he created drawings of what could be done. Behrens said “less is more”, so that Mies contributed little beyond the determinants of the technical form. Mies eventually reappropriated the phrase⁴⁶⁰ to emphasize a style where features beyond essential functions were eliminated. From 1904 to 1924, Mies was shaped by the philosophy of critical realism of Alois Riehl⁴⁶¹, for whom Mies had designed an ascetic country home in 1907. Mies’ quest for “great form” gradually departed from the style of Behrens⁴⁶², embracing nature on the site, and three-dimensionality. Mies returned in 1911 to work with Behrens, and then left in 1912 as a competitor in architecting the Kröller-Müller Villa. Siting a house in front of, rather than in, the woods, the studies of Karl Friedrich Schinkel⁴⁶³ and Frank Lloyd Wright⁴⁶⁴ were a larger influence. In 1912, Mies saw the Stock Exchange in Amsterdam architected by Hendrik Petrus Berlage⁴⁶⁵ with the attributes of “monumental form”.

Less-is-more, manifested as modernism, has been criticized as choosing simplification over unity⁴⁶⁶ through the exclusion of parts. Complexities in architecture include⁴⁶⁷ the variety of goals, and ambiguity of experiences. A “difficult whole”⁴⁶⁸ embraces a multiplicity of parts that are inconsistent, and potentially in exploits or resolves duality in a whole, in a way that simplification does not. Contradictions include (i) “both-and” phenomena (e.g. closed yet open, simple outside yet complex inside); (ii) double-functioning elements (e.g. multifunctional buildings or rooms with generic purpose rather than separation and specialization at all scales); and (iii) accommodation of inconsistencies in the order (e.g. breaking up orderliness as a strength, rather than a weakness); and (iv) adapting to contradictions (e.g. compromising in disintegration of a prototype). Modernism maintains consistency in order, in points, lines and planes.

More-is-more implicitly opposes the polemic of “less is more”. To move the dialectic positions forward, the pursuit of “more” – as an increase in the quantity of output or in the quality that is valued – may be correlated with changes in scale (i.e. larger or smaller), scope (i.e. broader or narrower) and/or speed (i.e. faster or slower, with potentially higher order acceleration or deceleration). The effects of these changes are not monotonically linear (i.e. a relation that can be graphed as a straight line continuously rising or falling). The effects may not only be nonlinear, and could also change as the mix of conditions change. In a highly interconnected and complex world, the convention wisdom that “bigger is better”⁴⁶⁹ may mislead. Seeing a system as generative, there are conditions when more-leads-to-more, and conditions when more-leads-to-less.

When more-leading-to-more precedes more-leading-to-less over time – a curve that seems like a frown when drawn – the nonlinearity is concave⁴⁷⁰. When more-leading-to-less precedes more-leading-to-more over time – a curve that seems like a smile when drawn – the nonlinearity is convex. These can both be labelled as convexity effects, with the shape of a “smile” as positive convexity effects and the shape of a “frown” as negative convexity effects. In human exchanges, convexity effects⁴⁷¹ lead to some parties gaining, and some parties losing. If a party invests in a variation with positive convexity, there is more upside than downside. A variation with negative convexity is hurt more by “Black Swan events”⁴⁷² due to the occurrence of unexpected outcome that comes with great harm.

Diminishing returns to resources⁴⁷³ that are well understood in economics can be cross-appropriated to understanding systems more generally. Changes in an ecology⁴⁷⁴ may manifest as (i) increasing complicatedness or (ii) increasing complexity. Increasing complicatedness is a replication of parts within an existing level, as an elaboration of structure. Increasing complexity is a change in type, as an elaboration of organization with a deeper hierarchy. Choosing to deepen the hierarchy can lead to greater efficiencies, but requires resources (i) to fuel the reorganization, and (ii) maintain the overhead of that new level of organization. Decomplexifying a hierarchy into a flatter structure more responsive to local variety is often a challenge, as (i) resources are again required to fuel the reorganization, and (ii) a decentralized or distributed organization may not be viable against a global competitor. Complexified organizations can benefit from high gain resources if they are available,⁴⁷⁵ but complicatified (i.e. decomplexified) organizations may enjoy greater sustainability by falling back on low gain resources available locally.

More-leading-to-more is generally associated with a transforming to, and the maintaining of, complexification. When a system becomes unsustainable or is headed towards collapse, continuing on the prior more-leading-to-more trajectory fails with a more-leading-to-less taking over.⁴⁷⁶ The alternative choice of less-leading-to-more may come with a transitional cost associated with reorganization, for the potential sustainability at a lower level of overhead in the longer term. Efficiency is a siren’s call on a shorter horizon for complexifying; sustainability is a disciplinary foresight on a longer horizon for complicatifying.

Complexity is full of contradictions and paradoxes. Switching from a more-leading-to-more history in favour of a less-leading-to-more future depends on the context. Three approaches suggest different contexts: (i) schismogenesis; (ii) messes (also known as problematiques); and (iii) wicked problems.

Schismogenesis⁴⁷⁷ was originally observed as regenerative or “vicious” circles amongst a community where parties acted in two groups, each one stimulating the other. Schismogenic sequences were classified as (i) symmetrical schismogenesis, where mutually promoting actions of each group were essentially similar (e.g. in competition or rivalry); or (ii) complementary schismogenesis, where mutually promoting actions of each group were dissimilar but mutually appropriate (e.g. dominant-submissive, exhibitionist-spectator). Modeling interactions as a Von Neumannian game (i.e. competitive game theory) was found to be inappropriate, as (i) players learn and incorporate rules in their character; (ii) value scales are neither simple nor monotone; (iii) games are infinite, and not a tabula rasa at each play; and (iv) players could exit by economic death or boredom. Describing the system qualitatively would look to follow the regenerative (more-leading-to-more) and degenerative (more-leading-to-less) causal loops of processes and acts.

Managing a mess⁴⁷⁸ (i.e. a problematique, as a system of problem) could lead to an intervention where problems are resolved (satisficing), solving (optimizing) or dissolving (removing the problem, in the environment). An approach of less-leading-to-more would most likely be associated with dissolving a mess.

A wicked problem⁴⁷⁹, by definition, can not be solved, just re-solved over and over again. An approach of less-leading-to-more could be implemented, that could be linked to another issue or consequence at a later time.

Innovation learning of less-leading-to-more alongside more-leading-to-more weighs the risks gains and costs associated with reorganizing. If the current design orientation is more-leading-to-more, a rearchitecting to less-leading-to-more could incur short-term transition vagaries with an infrastructural shift. The option of "don’t mess with success" may rub against a reality where alternatives and competitors don’t feel constrained by legacy systems.

Open innovation learning of less-leading-to-more alongside more-leading-to-more expands the field of possible reorganizations to collaborations with other organizations. With regulations deterring undisclosed collusions, participating in open sourcing projects can constructively elevate the quality of resources available to all, while enabling each party to capitalize on private sourcing for specific customer sets or stakeholders. Foundations and committees enabling the crossover from open sourcing to private sourcing are minimally skeletal to maintain low overhead.

9.5.4 Hypothesizing for a theory of open innovation learning-alongside

A hypothesis for a normative theory for OIL with a paradigm of co-responsive movement can be constructed from the three learnings-alongside:

• Hypothesis: Open innovation learning-alongside couples agencing strands of (i) polyrhythmia entangling eurhythmia, over (ii) regenerating entangling preserving, and (i) less-leading-to-more entangling more-leading-to-more.

Testing this normative theory for OIL could take place in the three emerging cases outlined earlier. The rise of (i) polycentric governance, (ii) the Internet of Things, and (iii) cognitive computing, each provide salient contexts to which agencing strands of polyrhythmia entangling eurhythmia, regenerating entangling preserving, and less-leading-to-more entangling more-leading-to-more are combined and weighed against each other.