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

Open innovation learning (OIL) advances towards application, building normative theory on ways that organizations succeed. Normative theory is "a statement of what causes the outcome of interest, not just what is correlated with it".285 Descriptive theory orients towards ‘is’ propositions; normative theory orients towards ‘ought’ propositions.286 There are multiple ways for organizations to succeed, and science based on historical data and analysis partially contributes towards that.287 A transition from building descriptive theory to building normative theory is depicted in Figure 9.1, extending the diagram originally shown in Figure 1.1.

Multiparadigm research: paradigm, theory, emerging cases)

Figure 9.1 Multiparadigm research: paradigm, theory, emerging cases)

Multiparadigm research builds on the insights from chapters 6, 7 and 8, where three descriptive theories alongside three emerging paradigms were proposed. The result is three new normative theories for OIL alongside a single new paradigm that may inform organizational decisions and activities in some emerging cases.

Building normative theory extends the boundaries of situations or circumstances under which understanding and prediction under which managers might apply the research.288 The relevance of findings here may be reapplied in studies approached by action research, mode 2 (engaged scholarship, collaborative research) or design research.289

Jumping forward from the 2001-2011 case studies, open sourcing while private sourcing (OSwPS) is one way in which OIL has become more commonplace by 2016. Commercial companies of the scale of Google, HP, Microsoft and Twitter all contribute to open source communities. IBM has expanded its open sourcing into cloud and cognitive computing strategies where there hadn’t been a presence 5 years earlier. Of 400,000 IBM employees, 62,000 have been certified290 to participate in open sourcing. Open sourcing has also extended more broadly. In 2014, Tesla had declared an open source patent pool291 on vehicle components, battery charging, energy storage and power optimization.

9.1 Emerging cases where open innovation learning is relevant

The salience of OSwPS research may be triggered by suggesting some circumstances under which scientific findings have relevance. In 2017-2020, guidance might be appreciated in newly rising situations.

(i) Innovation Learning with the rise of Polycentric Governance: Deglobalization is seen as a major shift in the world order, with Brexit and the election of Donald Trump as the U.S. president in 2016.292 The rise of globalization that had seen multinational organization design progress from ethnocentric to polycentric to geocentric could see a step back towards geocentrism.293 The normative theory based on OSwPS could be helpful in flowing learning in international innovation from the traditional alternative of (i) complete concentration towards (ii) core-periphery concentration, (iii) sequential dispersal, (iv) modularized dispersal, or (v) inclusive dispersal.294 Leaders should also be aware that OSwPS may be used in military as well as commercial ways, counter to prevailing interests.295

(ii) Innovation Learning with the rise of the Internet of Things: The Internet of Things (IoT) interweaves the physical world with actuators, sensors and computational element through network connectivity. IoT smart environments, categorized by application domain, include: smart cities; smart homes; smart grid; smart buildings; smart transportation; smart health; and smart industry.296 While the vision of small ubiquitous connected computers was described in 1993, the IoT was authentically seen as taking root in 2016, with the potential to increase 10-fold to 100-fold over the following 10 years with open peer-production, standards and common practices.297 With the rapid pace innovation coming from commercial businesses (many funded by venture capital), normative theory from OSwPS could provide some guidance for technology organizations.

(iii) Innovation Learning with the rise of Cognitive Computing: In late 2015, IBM declared the cognitive business as a new technological era beyond digital business.298 Computing has been characterized as an evolution from (i) the (mechanical) tabulating era (1900s-1940s), to the (ii) the (digital) programming era (1950s to the present); and (iii) the cognitive era (from 2011, with IBM Watson defeating previous champions on Jeopardy). The cognitive era follows from foresight by J.C.R. Licklider in 1960 of man-machine symbiosis in cooperative interaction.299 In the case of the Jeopardy demonstration, the data analytics and statistical reasoning of machines were combined with human qualities of self-directed goals, common sense and ethical values. In December 2015, OpenAI was founded as a non-profit research company by Elon Musk, Sam Altman and Greg Brockman to "create a new type of AI lab, one that would operate outside the control not only of Google, but anyone else".300 By December 2016, OpenAI and Deepmind Labs (a subsidiary of Google parent Alphabet) both open sourced their deep learning code.301 The Partnership on AI was founded by Amazon, DeepMind/Google, Facebook, IBM, and Microsoft in September 2016, with Apple joining in January 2017. Organization members will "conduct research, recommend best practices, and publish research under an open license in areas such as ethics, fairness, and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability, and robustness of the technology".302 Amidst rapidly advancing technologies, cognitive computing will see organizations actively OSwPS.

With present challenges such as these – and others where organizations cooperate to advance knowledge collectively, across commercial boundaries – an associated paradigm and theories have emerged.

9.2 Open innovation learning with a paradigm of co-responsive movement sees open sourcing alongside private sourcing

"Innovation learning" is a label that surfaces a normative challenge on the practicality of reaching an aspiration. If an organization is considering a direction of entrepreneurial innovation303, Schumpeterian innovation304, disruptive innovation305, social innovation306 or any other type of innovation, what is the evolutionary path for the behaviour of individuals as members, and the organization as whole? A direction towards innovation requires that a more than a leader merely declaring a strategy in a pattern of communicate-and-hope.307

Innovation in organizations requires changes both in practice and process.308 New knowledge may be best created in single communities of practice, but then formal organizational processes are generally needed to scale up inventions as viable innovations. Process innovation can be directed within an organization through top-down formal specifications of ways that work is coordinated.309 Innovation on practices typically occurs from bottom-up hands-on work communities, as shared knowledge and common identity coalesce organizational knowledge. Innovation learning has conventionally been focused on changes in behaviour within organizations. OIL complicates dynamics as changes in behaviour across organizations coevolve.

OIL is exemplified in OSwPS, in a paradigm drawn at the intersection of (i) ecological anthropology and (ii) material culture studies.

(i) Ecological anthropology studies the organism’s exploratory movement through the world.310 OIL can similarly see progress not just as an inwardly focused reflection, but also in ecological approach getting a grip on the larger world.

(ii) Material culture studies focuses on artifacts, that, beyond their physicality, have a history with the human beings with which it has associated.311 OIL not only appreciates individuals and organizations expanding their knowing in mental models and abstract concepts, but also in artifacts of today’s physical and digital world.

OSwPS grounds a paradigm of co-responsive movement along lines of becoming, for OIL. This dense description can be broken down, with foundations from ecological anthropology and material culture studies.

Movement along lines of becoming is associated with an animic ontology, where "beings do not propel themselves across a ready-made world but rather issue forth through a world-in-formation, along the lines of their relationships".312 This inverts conventional western thinking in (i) the relational constitution of being, and (ii) the primacy of movement.

(i) Instead of representing being at a point in time with an organism inside a circle, and the environment as everything outside, an animic ontology represents a being that is alive as a trail of movement or growth (e.g. a wavy vector over time).313

(ii) Instead of occupying the world in a static dwelling, an animic ontology has beings inhabiting the world, "in so doing – in threading their own paths through the meshwork – they contribute to its ever-evolving weave" [….] . And woven into their very texture are the lines of growth and movement of its inhabitants. Every such line, in short, is a way through rather than across". 314 Among the Inuit, a person or an animal is recognized as soon as he/she/it moves, becoming a line with a trail behind it. Something that doesn’t move is not alive.

This emphasis of movement and lines descends from the ecological approach to perception of J.J. Gibson in the concept of affordance, which works more generally for animals, as well as human beings.315 Interpreting Jakob von Uexküll’s subjective universe, human beings are unique as "capable of making their own life activity the object of their attention, and thus of seeing things as they are, as a condition for deliberating about the alternative uses to which they might be".316 Martin Heidegger was seen to admire von Uexküll in appreciating human beings as unique from other animals, but his world in a space of dwelling sees disclosing (opening up) in ways subtlely different from Gibson’s perception of objects.317 Gilles Deleuze counters Heidegger with an "openness of a life that will not be contained", yet living his along "lines of becoming" requires bringing back the environment so that his field is "not of interconnected points but of interwoven lines, not a network but a meshwork".318 Both anthropologist Gregory Bateson and cognitive scientist Andy Clark see the mind not limited by the body.319

Co-responsive movement is a joining with, in an ongoing sympathy of living things going along together. Joining with is an "interpenetration of lifelines in the mesh of social life … in a world where things are continually coming into being through processes of growth and movement" in a generative form when contrary forces of tension and friction are pulled tightly into a knot. This is in contrast with "joining up" as assemblies that can "be a readily decomposed as composed". "Untying the knot ... is not a disarticulation or decomposition. It does not break things into pieces. It is rather a casting off, whence lines once bound together go their separate ways".320

Co-responding "is the process by which beings or things literally answer to one another over time, for example in the exchange of letters or words in conversation, or of gifts, or indeed in holding hands"321. Members co-responding with each other carry on alongside one another over time, answering contrapuntally.322 A theory of co-responding was foreshadowed in John Dewey’s social view of communication, meaning "the attainment of a certain ‘like-mindedness’, enabling those with different experiences of life, both young and old, to carry on together".323 This sense of communication is "not about the exchange of information, as communication is often understood today; it is rather about forging a concordance".

OIL can be seen as opening up communications, sharing artifacts in common and learning in a larger community.324 This takes up "an approach that understood how time, movement, and growth were together generative of the forms of living things rather than merely ancillary to their expression".325

A paradigm of co-responsive movement along lines of becoming is a foundation for normative theory building on OIL. The theories include:

These three theories aim to advance three primary intellectual virtues: (i) episteme (i.e. science as epistemology), (ii) techne (i.e. craft and technique), and (iii) phronesis (i.e. prudence and common sense).326 This paradigm complements an ecological perspective on learning "reconceptualised as a process entailing mutually constitutive, epistemic, social and affective relations in which knowledge, identity and agency become collective achievements of whole ecosystems … [implying] that learning involves a trans-contextual and multimodal process, in which both learners and their social and material environments change".327

9.3 Innovation learning [enskilling attentionality] for (episteme)

Innovation learning-for centers on enskilling attentionality. This orientation emphases ecological epistemology.328

Attentionality comes habitually, as intentionality comes volitionally: "if going for a walk is volitional, walking itself is habitual".329 Distraction doesn’t pull a pedestrian away from intention along the route, as much as drawing attention towards a manoeuvre to circumvent a potential hazard.330 Learning, as generating and regenerating knowing331 both in individuals and in groups, should not be seen as a transmission of representations, but instead as the educating of attention. Passing along knowledge from one generation to another is more than writing a recipe into a cookbook to be copied as images into a mind. Novices are guided by tutors not to imitate, but to discover for themselves and improvise, towards becoming skilled practitioners in situated and attentive engagement.332 While an novice can get thrown off by a minor unanticipated variation, the experienced craftsman couples perception and action that attunes movement to the task at hand at that moment.333

Enskilling is an embodying of capacities of awareness and response by environmentally situated agents334. In a world of work practices, a task335 is an any practical operation carried out by a skilled agent in an environment. A taskscape336 relates tasks to each other, in series and in parallel with other human beings inhabiting technical and social activities. Individually, the lines of our lives337 assemble our movements, each of us (i) wayfaring on personal trails, (ii) mapping journeys that we can re-enact, and (iii) relating storylines as paths of lived experience. In shared environments, our lines of lives, growths and movements entangle in meshworks338 of interaction.

Deskilling, through new affordances in technology that mechanize and automate tasks, is a common response by employers challenged to find workers qualified and experienced with a craft. Industrialization routinizes work activities to reduce the variability in outputs, with a consequence of inhibiting enskilment as opportunities to progress learning are reduced.339 Standardization displaces learning through situated practice that progresses novices into mastery, and the ability to deal with the ambiguous is reduced. Hands-on experience, where novices peripherally participate in communities of practice that include experts, can raise the level of skills for all.

Learning "denotes change of some kind. To say what kind of change in a delicate matter".340 The simplest type of learning has been called Learning Zero, where "an entity shows minimal change in its response to a repeated item of sensory input".341 In this sense, there is a category of innovation learning zero, where discovery of an error contributes nothing to future skill.342 Logical categories of learning [for] are depicted in Figure 9.2.

Logical categories of learning [for])

Figure 9.2 Logical categories of learning [for])

A response that leads to an error can provide information to an organism to change a response when a similar event occurs in the future. Learning Zero would continue to repeat the same error. Proto-learning (Learning I), deutero-learning (Learning II) and trito-learning (Learning III), as described in detail in the sections that follow, correct for errors in different ways. For normative theory in anticipation of frame-breaking world changes (e.g. polycentric governance, the Internet of Things, cognitive computing), the Learning Zero path of not responding to changes in context reduces the likelihood of viability.

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.

Proto-learning (Learning I [for]

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.

Deutero-learning (Learning II [for]

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 21st 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.

Trito-learning (Learning III [for]

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.

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

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 Innovation learning [weaving flows in form-giving] by (techne)

Innovation learning-by centers on weaving in processes of formation as the flows and transformation of materials in form-giving. Techne is ‘know how’ – particularly in a collective sense of methods oriented towards productions.361

Flows in form-giving gives primacy to making in a social-material-temporal taskscape.362 This overthrows Aristotle’s emphasis on the end product in the creation of form. "Form is the end, death", wrote painter Paul Klee. "Form-giving is life".363

Weaving values a textility in making, where "the tactile and sensuous knowledge of line and surface that had guided practitioners through their varied and heterogeneous materials, like wayfarers through the terrain".364 Skilled practice is "a question not of imposing preconceived forms on inert matter but of intervening in the fields of force and currents of material wherein forms are generated".365 The architectonics of pure form elevates technology into "a system of operational principles". The form of a woven basket "assumes a rigid form, precisely because of its tensile structure".366 The textility of building encounters "matter in movement, in flux, in variation", leading to a rule of thumb: follow the materials.367 Building is "a process of working with materials and not just doing to them, and of bringing form into being rather than merely translating from the virtual to the actual". As building is to dwelling, so making is to weaving".368

Learning-by connects learning and practice in the literature of communities of practice, including the development of skills without formal learning or school through participatory work and apprenticeship. Distinctions can then be made between:

This perspective follows an anthropological paradigm of practice-based learning, with situated learning and distributed cognition.369

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

Labor cost percentages [Wright (1936)]

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 Innovation learning [agencing strands] alongside (phronesis)

Innovation learning-alongside respects two (or more) (life)lines as agencing strands alongside each other. Phronesis is ‘know when, know where, know whom’, appropriately demonstrating an appreciation of the situation at hand, a possible implicit weight of values, and the setting for an appreciative system.414

Strands are characteristic of social lives, where animals have a togetherness in moving, encountering and resting in the open. Lives "are social not because they are framed but because they are entwined. All life is social in this sense, since it is fundamentally multistranded, an intertwining of many lines running concurrently".415 This lineal view sees inhabitants threading themselves through their worlds, each tying up his or her strand with other strands, interweaving their paths in knots.

Agencing is "the potential of undergoing reflexively to transform the doer".416 A doer generally acts out of habit, but encounters interstitial differentiations where experience of the interval departs from the habit. The agent "is inside the process of his or her action", not separate from it. Agencing in-between two strands is a becoming. This is akin to seeing a swimmer in the current of a swift river, and joining that swimmer in the midstream, not interacting with the opposite banks of the river, but going along longitudinally.417 The parties co-respond to each other, rather than being bounded by the ends set in advance by each.

Learning-alongside couples multiple agents in the joining together in their movements. For deeper insight into what is going on in-between, inquiry can be constructed in a dialectic with positions in opposition to each other. Such an approach extends the technique described with the systems approach and its enemies.

To me, these enemies provide a powerful way of learning about the systems approach, because they enable the rational mind to step outside itself and observe itself (from the vantage point of the enemies) (Churchman 1979, 24).

The enemies of the systems approach were characterized as (i) politics; (ii) morality; (iii) religion; and (iv) aesthetics. Here, in the interest of dialogic inquiry, we can make dialectical distinctions between:

This perspective builds on an ecological anthropological theory of human co-responding.418

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.

Table 9.1 Polyrhythmia entangling eurhythmia
Learning alongside
Polyrhythmia -- Eurhythmia

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.

Table 9.2 Regenerating entangling preserving
Learning alongside
Regenerating -- Preserving

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.

Table 9.3: Kinds of materiality and implications in formation
# Kinds of materiality (part of nature) Distinctions in production
1 Wholly untouched by human activity Wild
2 Changed on account of the presence of humans Wild [hunting, gathering, nurturing animals (wild pigs)]
3 Intentionally transformed by human beings and that depends upon their attention and energy for its reproduction Cultivation of domesticated [growing, gardening, raising animals (midwifing births), artificial selection]
4 Materials that have been fashioned into instruments such as tools and weapons Making [tools, services]
5 The built environment Making [products]

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 19th 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.

Table 9.4 Less-leading-to-more entangling more-leading-to-more
Learning alongside
Less-leading-to-more -- More-leading-to-more

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.

9.6 Philosophy of alternative stable states: teleonomy meets teleology

Building a normative theory of OIL portends becoming in nature, in the way that child-rearing attempts to be place young learners on the right path: enfolding seeds for development may or may not later unfold as fruit. Becoming preceding being. Philosophically, there’s an opportunity for teleonomy to learn from teleology. A larger context in which to consider these philosophies is in the science of alternative stable states, from ecology, shown in Table 9.5.

Table 9.5 Teleonomy learns from teleology
environmental change,
somatic change,
genotypic change


Alternative stable states:
panarchy, resilience, regime shifts

Teleology is the branch of philosophy that explains natural phenomena by their end or purpose. Of Aristotle’s four causes480, it emphasizes final cause. Human systems can be described at teleological481, with purposeful systems as ideal-seeking and purposive systems as goal-seeking, recognizing human will. In the study of organizations as systems, choices can be made on different outcomes on a variety of time horizons482: (i) a goal is a preferred outcome within a specified time period; (ii) an objective is a preferred outcome obtainable in a longer time period; and (iii) an ideal cannot be obtained within any time period, but is worth pursuing. From the perspective of living systems, however, teleology has been criticized483 for an inference that the end design of an organism at some future time can be foreseen in advance.

Theories of biological evolution recognize three types of change484: (i) environmental change; (ii) somatic (cellular) change; and (iii) genotypic change. recognizes both generational and adaptive change in response to the environment. These three types are illustrated in an example of a person accustomed to sea level atmospheres being moved up to high altitudes, resulting in an elevated heart rate and panting. An environmental change would see the person descending from altitude, so that symptoms of stress would immediately reverse. A somatic change would see the person’s body acclimatizing to the thinner atmosphere, with multiple organs attaining homoeostasis by responding to or increasing the overall flexibility of the organism. A genotypic change could occur over generations of people485 living at high altitudes, where natural selection assimilates acquired characteristics.

Teleonomy has been defined specifically for goal-directed processes in organisms. A teleonomic process or behavior is one which owes its goal-directedness to the operation of a program486. Goal direction is implied, but with a dynamic process rather than a static condition. The program may originate through lucky macromutation, a slow process of gradual selection, or even through individual learning or condition as in open programs. A program might be defined as coded or prearranged information that controls a process (or behavior) leading it toward a given end487. Teleonomic processes can be controlled by closed programs (e.g. in the DNA of the genotype) or open programs (e.g. incorporating additional information acquired through learning, conditioning, or experiences).

A theory of alternative stable states has been developed in ecology, from two heritage research streams488. Ecologists often take advantage of studying lakes that are geographically proximate: one lake may have settled into a flourishing stable state with a vigourous population of fish and vegetation, while another lake nearby has settled into a dead stable state in a poverty trap of low oxygen (i.e. hypoxia) and hypertrophication (e.g. oversupply of phosphates or sewage). Stable states are commonly depicted with ball-in-cup diagrams, where (at least) two basins are available in which the ball can rest. A small perturbation may move the ball within the basin, retaining its current stable state. A large perturbation may move the ball out into another basin, into a new stable state. Having become stable in the new state, a reverse perturbation may or may not result in a return to the original stable state.

The research stream from community ecology focuses on changes in state variables (e.g. population densities). As an example in fish population, there may be one stable state where harvesting is supported by a high birth rate, and then an alternative stable state where harvesting is not supported due to the dominant death rate. There’s a boundary middle ground where the state is not stable. In another example where there are multiple species in a lake, there may be one stable state where two species coexist, and then another stable state where one population outcompetes the other. In a ball-in-cup depiction, the community moves from one basin to another, with intermediate positions leading the ball away from that middle ground.

The research stream from ecosystem ecology has focused on changes to the parameters governing interactions within an ecosystem. As an example in Africa, both woodlands and grassy open savannahs are stable states489. Woodlands are not eliminated by herbivore grazers, but can be destroyed by humans and/or high densities of elephants, leading to an almost irreversible loss of forests. The landscape (as the environment) is considered to be constant, and parameters of the living biota change (e.g. birth rates, death rates, carrying capacity). In a ball-in-cup depiction, the landscape on which the ball sits alters, so the ball moves.

The theory of alternative stable states is a foundation for panarchy and resilience science. In panarchy, social ecological systems exist and function at multiple scales of time, space and social organization in nested hierarchies. Resilience science is associated with adaptive capacity in the ecosystem to deal (or not deal) with changes in the environment. With alternative stable states, research into regime shifts – as large, abrupt, persistent changes in the structure and function of system – is being conducted on a wide variety of domains.

Private sourcing can be seen as the dominant regime for business in the 20th century, with a variety of organizations competing to establish primacy in one of many stable states. Open sourcing rose only in the late 1990s, as a regime initially independent of commercial interests, operating in a stable state with a relatively low level of energy. OSwPS in the first decade of the 21st century created a new landscape with injections of enterprise-scale resources, that organizations could choose to embrace or to reject.

The nature in teleonomy battles with human interventions in teleology. OSwPS may have been most prominent with IBM as a pioneer, but after 2011 has become a not-uncommon way of working. Timing is everything. More formally, the ancient Greek poet Hesiod, wrote490 “Observe due measure, for right timing is in all things the most important factor”. Organizations may choose to extend their heritage of private sourcing only (PSo), or to include open sourcing in their practices by its associated changes in governance. Leaders and policy makers can choose between protecting the past from the future491, or protecting the future from the past.

Chapter 8

Appendix A

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