In the preceding section we focused on two complexity concepts: self-organization and implicate order, which we consider essential to improve our understanding of adaptive and generative learning processes within organizations. In this section we extend our analysis by exploring the contribution of these ideas to understanding or rethinking these two types of learning and OL process.
In order to explain the different processes of adaptive and generative learning within organizations, we propose the distinction between complex “adaptive” systems and complex “generative” systems. While complex adaptive systems are associated with self-organization (Anderson, 1999), complex generative systems are related to self-transcendence (Jantsch, 1980), which implies a process that drives agents toward the implicate order.
One of the chief complexity ideas is the concept of “edge of chaos” or “bounded instability”, which allows a system to initiate change. Organizational systems may present three types of states: stability, chaos and edge of chaos. When the system is stable and chaotic, effective complexity is low: either because it operates in an environment that is highly stable, in the sense that its component systems behave in a perfectly regular manner or because there is a high level of disorder. In both situations little learning may take place (Stacey, 1996: 96). However, at the edge of chaos, the system is very complex, and finds itself in the transition phase between stability and chaos. In this situation, generated through interconnectivity and diversity, (adaptive or generative) learning may emerge (Gell-Mann, 1994): self-organization or self-transcendence processes may occur. Neither process can be controlled nor managed and results cannot be determined in advance, although certain factors or conditions might catalyze self-organizing and self-transcendence processes. Below, we will analyze these conditions and describe the processes.
Adaptive learning is considered by the OL literature as the refinement and improvement of existing competences, technologies and paradigms without necessarily examining or challenging our underlying beliefs and assumptions. Complexity literature understands that complex “adaptive” systems have the capacity to adjust to changes in the environment without endangering their essential organization. Figure 1 describes the process of adaptive learning mainly based on ideas from complex adaptive systems.
Insert Figure 1 about here
Explicate order, as referred to by Bohm (1980), is the manifested world, which is represented through knowledge, schemas, rules, mental models, paradigms etc. Adaptive learning involves any improvement or development of the explicate order through a process of self-organization, which is attained when the system is at the edge of chaos. Self-organization is a self-referential process that aims to improve or increase the complexity of the explicate order without being guided or managed by an outside source.
Generative learning implies being able to see beyond the situation and questioning operating norms (Argyris and Schön, 1974). Senge’s (1990) concept of metanoia describes it as a profound shift of mind. As we mentioned previously, generative learning might be associated with complex “generative” systems, which self-transcend (Jantsch, 1980) to develop a completely new order. This process aims to approach the implicated order and to attain this; an unconditioned act of perception is required (Bohm, 1980; Bohm and Peat, 2000). Figure 2 describes the generative learning process.
Insert Figure 2 about here
The process of self-transcendence (Jantsch, 1980) implies going beyond a certain state or any possible knowledge (explicate order) and approaching the implicate order (Bohm, 1980). According to Krishnamurti (1994), learning brings (new) order. Order is not synonymous with stability, but is rather a holistic perception of reality or a new perceptive path where previously there was only poor or null sensibility. Similar concepts may include Maslow’s (1971) notion of “peak experience”, or the term “alignment” as used by Senge (1990). Maslow (1971) defines peak experiences as sudden feelings of intense happiness and well-being, and possibly the awareness of ultimate truth and the unity of all things. In sum, all these terms are grounded on the assumption that parts often derive their nature and purpose from the whole and cannot be understood separately from it. Moreover, systemically, merely summing individual elements cannot account for the whole. This is why we also consider that the process of self-transcendence is a process of “holo-organization”. Within the implicate order everything is connected, everything is in everything else. Thus, we could say that Maslow’s peak experience is the subjective, personal and factual “experience” of Bohm’s holomovement, his implicit and seamless order revealed to the human conscience.
As we noted above, self-organization and self-transcendence might emerge when certain conditions are in place. In order to determine these conditions for both learning types, we will establish three dimensions or levels: individual, social, and impersonal. These dimensions are based on Wilber (2000) and Kofman (2006), who understand that every organization has three dimensions or realms: the personal or individual realm comprises psychological or behavioral aspects (personal values, thinking); the social or interpersonal realm comprises relational aspects (relationships, shared values); and finally the impersonal realm comprises technical aspects (tasks, aims).
Insert Table 1 about here
Adaptive learning is a self-organizational process that might happen when individuals and groups within organizations mainly exercise logic or deductive reasoning, concentrate, discuss, and focus on improving any mental model, knowledge, process etc. (explicate order). In contrast, generative learning is a self-transcendence process that might take place when individuals and groups within organizations mainly use intuition, attention, dialogue and aim to question any explicate order or knowledge.
Reasoning is the mental process of looking for reasons for beliefs. Logical deductive reasoning is the type of reasoning that proceeds from general principles or premises and, based on those ideas, derives particular information or deduces the truth about each individual part of the whole. Premises upon which we base our logical reasoning are accepted because they are “self-evident truths”, which implies that there is no need to question or inquire. Therefore, it implies taking explicate order for granted, and improving it by reasoning.
Intuition is defined as a quick and ready insight, a process of coming to direct knowledge without reasoning or inferring. It is a way of knowing the truth without explanations. Bohm (1980) explains that to approach the implicate order, an unconditioned act of perception or intuition is required. Bergson (1946) considers intuition as a simple, indivisible experience of sympathy through which one is moved into the inner being of an object to grasp what is unique and ineffable within it. Bohm (1980) explains intuition as a flash of understanding, in which one sees the irrelevance of one’s whole way of thinking about the problem, along with a different approach; such a flash is essentially an act of perception.
Generative learning also requires attention, which is different from concentration (Krishnamurti, 1994). Concentration is a process of forcing the mind to narrow down to a point, whereas attention is a state in which the mind is constantly learning without a center around which knowledge gathers as accumulated experience. It cannot be cultivated through persuasion, comparison, reward, or punishment, all of which are forms of coercion. The elimination of fear is the beginning of attention. Fear must exist whenever there is an urge to be or to become. Hence, attention arises spontaneously when the learner is surrounded by an atmosphere of well-being, when he or she feels secure and at ease. Similarly, Senge et al. (2005) suggest the importance of observing, becoming one with the world. Consequently, generative learning is associated with intuition and attention, whereas adaptive learning is linked to logical deductive reasoning and concentration.
Isaacs (1993) explains that any conversation flows to deliberation, which is to weigh up: consciously or unconsciously people weigh up different views, finding some with which they agree and others that they dislike. At this point, people face the first crisis, a decision point that can lead either to discussing views or to suspending them (dialogue). Discussion means to shake apart, to analyze the parts (Bohm, 2004b). Discussion implies dialectic conversation or the exchange of arguments and counter-arguments respectively advocating propositions (theses) and counter-propositions (antitheses). The outcome of the exercise might not simply be the refutation of one of the relevant points of view, but a synthesis or combination of the opposing assertions. The aim of the dialectical method, often known as dialectic or dialectics, is to try to resolve the disagreement through rational discussion, and ultimately, the search for truth or objective reality. In order to improve the explicate order (knowledge, paradigm, etc.), discussions are based on its analysis, by improving the perception of reality. Complex adaptive systems are purposeful, are determined to act in a certain way, basically to adapt to an environment, which implies improving the explicate order, to advance or make progress in what is desirable.
Bohm (2004b: 7) explains that dialogue is a stream of meaning flowing among and through us and between us. This will allow meaning to flow in the whole group, out of which may emerge some new understanding. In dialogue nobody is trying to win; everybody wins if anybody wins (Bohm, 2004b). Following Isaacs (2003), dialogue also begins with conversation, but when different views appear, instead of discussing them (dialectic; to break apart; to win), people suspend them (Bohm, 2004b). They begin to see and explore the range of assumptions that are present. For Bohm (2004b), suspending assumptions implies neither carrying them nor suppressing them, you do not believe them, nor do you disbelieve them. This idea can be related to the concept of Epoché, a Greek term developed by Aristotle and more recently by Husserl that describes the theoretical moment where all beliefs are suspended. Similarly, methodic doubt, which has become a characteristic method in philosophy popularized by Descartes, is a systematic process of being skeptical about the truth of one’s beliefs. Isaacs (1993: 30) considers that dialogue is an attempt to perceive the world through new eyes, not merely to solve problems using the thought that created them in the first instance. Likewise, Bohm (1980) and Krishnamurti (1969, 1974, 1994, 2005) consider that knowledge prevents generative learning. Krishnamurti (1974) considers that the simple acquisition of information or knowledge is not learning. Learning is finding out, observing, exploring relationships.
Dialogue is defined by Isaacs (1993) as a sustained collective inquiry into the processes, assumptions, and certainties that make up everyday experience. In order to learn, Krishnamurti (2005) maintains that one needs to be in a state of inquiry, which requires a previous state of discontent. Discontent prompts a move to go beyond the limitations of the actual model or tendency. He proposes questioning or inquiring into everything that has been accepted.
In sum, adaptive and generative learning carry out different processes and might be catalyzed or facilitated by different factors. Thus, two propositions are put forward:
Proposition 1: Adaptive learning involves any improvement or development of the explicate order through a process of self-organization. Self-organization is a self-referential process characterized by logic, deductive reasoning, concentration, discussion and improvement.
Proposition 2: Generative learning involves any approach to the implicate order through a process of self-transcendence. Self-transcendence is a holo-organizational process characterized by intuition, attention, dialogue and inquiry.
Organizing and learning have traditionally been considered as antithetical processes, which qualify OL as an oxymoron (Weick and Westley, 1996: 440). According to this approach, organizing means ordering, structuring and controlling the chaotic world (Watson, 1994), and learning is to disorganize and increase variety. However, Clegg et al. (2005) consider that organizing is not just the process of managing uncertainty, but is a process of increasing complexity and reducing it; ordering and disordering are interdependent, supplementary and parasitic. For these authors, learning becomes just one element in the process of organizing (Clegg et al., 2005: 155). In our paper, organizing and learning are considered as closely linked concepts. As suggested above, learning involves creating or searching for order (explicate or implicate), and organizing implies ordering.
Generative learning is a process that involves searching for implicate order, which is a holistic understanding of anything or anyone we interact with (holo-organization). When unfolded, represented or enacted, this implicate order becomes explicate order, or the manifested world, which signifies mental models, paradigms etc. This process of unfoldment, similar to Crossan et al.’s (1999) interpreting or Senge et al.’s (2005) realizing, consists of unfolding the implicate order; making it explicit, applicable, knowledgeable.
Knowledge is the body of data that comprises our rational picture of the world and how to live in it, and, while Krishnamurti (1994) recognizes its usefulness, he cautions us against focusing too exclusively on the building-up of knowledge at the expense of generative learning, which is a liberation from the limits of knowledge. Therefore, generative learning is beyond knowledge, because the latter is rooted in the past and would obviously prevent new things being seen. However, adaptive learning uses and improves knowledge, the explicate order.
Organizations are systems formed by other systems or agents (individuals and groups), all of which can be considered as social actors. We consider that adaptive and generative learning might happen in any social actor or agent, individuals and groups, which implies affirming that organizations learn through individuals (Simon, 1991), by reasoning-concentration or intuiting-attention and also through communities (Brown and Duguid, 1991), by discussing or dialoguing. Learning may start in individuals and in relationships, which means following a comprehensive view or accepting both perspectives, individual and social (Örtenblad, 2002; Elkjaer, 2004; Chiva and Alegre, 2005). Similarly, by adopting a social complexity perspective, Antonacopoulou and Chiva (2007: 289) seek a more holistic understanding of learning across multiple levels.
When explicate orders from individuals or groups change, a process of institutionalization (Crossan et al., 1999) influences the explicate order of the organization. Crossan et al (1999: 529) affirm that OL is different from the simple sum of the learning of its members. Although individuals may come and go, what they have learned as individuals or in groups does not necessarily leave with them. Some learning is embedded in the systems, structures, strategy, routines, prescribed practices of the organizations, etc. Finally, when organizational explicate order influences or affects individual or group explicate order a process of exploitation (March, 1991) takes place. Crossan et al (1999) consider this as a feedback process. Consequently, and following March’s (1991) terms, the exploration process might in our model take two modes: a self-organization process (adaptive) and a self-transcendence process (generative). Figure 3 describes the whole OL process.
Insert Figure 3 about here