Coevolving Innovations

… in Business Organizations and Information Technologies

Science, systems thinking, and advances in theories, methods and practices

Post-2013 addendum:  Many of the ideas in this January 2012 blog post — particularly around episteme, techne and phronesis — were more formally published in October 2013 as “Rethinking Systems Thinking: Learning and Coevolving with the World”, in Systems Research and Behavioral Science. Please cite that article, rather than this preliminary blog post.

Commenting on the Overview of Systems Science (draft version 0.5) for the Guide to the Systems Engineering Book of Knowledge is problematic. Applying systems thinking on systems thinking constitutes a mess of ideas that is difficult to tease apart. Breaking the idea of “systems science” in its parts of (i) “systems” and (ii) “science” is reductive. The more compatible approach is to view “science” with a larger context of “systems thinking”.

I’ll attempt to shed some more light on concerns and perspectives in the following sections:

  • 1. The definition of science often tends towards disciplinarity; systems thinking aims for transdisciplinarity
  • 2. Science is part of thinking, which can be philosophically framed as episteme (know why), techne (know how) and phronesis (know when, know when, know whom)
  • 3. Domains of systems thinking can be categorized into systems theory, systems methods, and systems practice
  • 4. Incomplete systems thinking may suggest paths through which gaps may be filled
  • 5. Systems thinking has evolved with roots of linear causality, circular causality, complexity theory and reflexivity theory
  • 6. Opportunities to refresh ties between systems thinking and action science, theory of practice and social learning could be pursued

The discussion of science and systems thinking leads to perspectives at another level. There’s an additional appendix on applied philosophy that illustrates that such inquiries are not without history.

1. The definition of science often tends towards disciplinarity; systems thinking aims for transdisciplinarity

In a previous post on systems thinking and (the) systems science(s) in a system of ideas, the correlation between the term “systems science” and “social systems science” at the University of Pennsylvania was reviewed. While “social systems science” was chosen as a term to be purposively clumsy, Russell Ackoff preferred more generally to use the label of “systems thinking”, obviating some criticisms on definitions of science. Science tends to be organized as disciplines. In the Oxford English Dictionary, one definition of discipline is “a branch of instruction or education; a department of learning or knowledge; a science or art in its educational aspect”. Another is “a particular course of instruction to disciples”, which implies a master. Ackoff criticized disciples as anti-systemic, challenging his students and followers to transcend his body of work.

Effective research is not disciplinary, interdisciplinary, or multidisciplinary; it is transdisciplinary.

Systems thinking is holistic; it attempts to derive understanding of parts from the behavior and properties of wholes rather than derive the behavior and properties of wholes from those of their parts.

Disciplines are taken by science to represent different parts of the reality we experience. In effect, science assumes reality is structured and organized the way universities are. This is a double error.

First, disciplines do not constitute different parts of reality; they are different aspects of reality, different points of view. Any part of reality can be viewed from any of these aspects. The whole can be understood only by viewing it from all the perspectives simultaneously. Second, the separation of our different points of view encourages looking for solutions to problems with the same point of view from which the problem was recognized. Paraphrasing Einstein, we cannot deal with problems as effectively as possible by employing the same point of view as was used in recognizing them.

When we know how a system works, how its parts are connected and interact to produce the behavior and properties of the whole, we can almost always find one or more points of view from which better solutions to the problem can be found than can be found from the point of view from which the problem was recognized. For example, we do not try to cure a headache by brain surgery, but by putting a pill in the stomach. We do this because we understand how the body, a biological system, works. When science divides reality up into disciplinary parts and deals with them separately, it reveals a lack of understanding of reality as a whole, as a system.

Systems thinking not only erases the boundaries between the points of view that define the sciences and professions, but also erases the boundary between science and the humanities. Science, I believe, consists of the search for similarities among things that are apparently different; the humanities consist of the search for differences among things that are apparently similar. Science and the humanities are the head and tail of reality, viewable separately, but not separable. It is for this reason that I have come to refer to the study of systems as part of the scianities. [Ackoff 1999, pp. 426-427, editorial paragraphing added]

In his books, Ackoff wrote that “the pursuit of truth is the function of science“.  Truth is one of the four ideals from ancient Greek philosophy (including the good, beauty, and plenty). More practically, coming at problematique — a system of problems — with a disciplinary lens can lead — as Ian Mitroff says — to a Type III error, as “the error of solving the ‘wrong’ problem precisely” or “the probability of solving the ‘wrong’ problem when one should have solved the ‘right’ problem”. Ackoff and Mitroff were both students of C. West Churchman, who developed the Design of Inquiring Systems. Inquiry is “an activity which produces knowledge” [Churchman 1971, p. 8]. Transdisciplinary would be one of the features of the “fifth way of knowing“, as unbounded systems thinking.

2. Science is part of thinking, which can be philosophically framed as episteme (know why), techne (know how) and phronesis (know when, know when, know whom)

For a deeper appreciation of the meaning of science, let’s go back to ancient Greek philosophy, and then work our way towards the present. The intellectual virtues of epistemetechne and phronesis are articulated in ancient times, although phronesis has been slower to develop in modern philosophy. Here’s a table summarizing some of the language used in philosophy. While episteme is often described as “know why” and techne as “know how”, it’s my personal intellectual contribution to describe phronesis as “know when, know where, know whom”. This is related to themes coming from phenomenology and social theory.

Table 1: Episteme, techne and phronesis as primary intellectual virtues
Primary intellectual virtue: Episteme Techne Phronesis
Translation / interpretation: Science (viz. epistemology) Craft (viz. technique) Prudence, common sense
Type of virtue: Analytic scientific knowledge Technical knowledge Practical ethics
Orientation: Research Production Action
Nature: Universal Pragmatic Pragmatic
Invariable (in time and space) Variable (in time and space) Variable (in time and space)
Context-independent Context-dependent Context-dependent
Pursuits: Uncovering universal truths Instrumental rationality towards a conscious goal Values in practice based on judgement and experience
Colloquial description: Know why Know how Know when, know where, know whom

As a way of illustrating some distinctions between the approaches, let me describe an experience that I’ve had with practitioners of Traditional Chinese Medicine (TCM). For some time, I’ve been seeing Dr. David Lam, who is trained in both western and Chinese techniques. He thus has been able to give me explanations in multiple ways (e.g. the west sees cortisone produced in the adrenal gland, TCM sees cortisone as produced by kidney system). He applies techniques of pulse diagnosis, and prescribed herbs — now standardized into pill form, manufactured in China. Dr. Lam exhibits understanding and experience all three virtues of episteme, techne, and phronesis. More recently, I’ve also tried an apothecary in Chinatown, who similarly uses pulse diagnosis. He prescribes decoctions of raw herbs to be cooked at home. This apothecary demonstrates techne and phronesis, as knowledge passed down through multiple generations in his family, in the practice of “tasting a thousand herbs“. As effective as the remedies have been, the apothecary has not demonstrated the skill of episteme. He does not have the university diplomas on the wall, as does Dr. Lam. My ailment may have been cured, but the theoretical explanation is incomplete.

A more detailed description of episteme, techne and phronesis as interpreted from Aristotle by Bent Flyvbjerg writes:

Episteme concerns universals and the production of knowledge that is invariable in time and space and achieved with the aid of analytical rationality. Episteme corresponds to the modern scientific ideal as expressed in natural science. In Socrates and Plato, and subsequently in the Enlightenment tradition, this scientific ideal became dominant. [….]

Whereas episteme resembles our ideal modern scientific project, techne and phronesis denote two contrasting roles of intellectual work.Techne can be translated into English as ‘art’ in the sense of ‘craft’; a craftsperson is also an artisan. For Aristotle, both techne and phronesis are connected with the concept of truth, as is episteme. [….]

Techne is … craft and art, and as an activity it is concrete, variable, and context-dependent. The objective of techne is application of technical knowledge and skills according to a pragmatic instrumental rationality, what Foucault calls ‘a practical rationality governed by a conscious goal’ (Foucault 1984b: 255). […]

Whereas episteme concerns theoretical know why and techne denotes technical know how, phronesis emphasizes practical knowledge and practical ethics. Phronesis is often translated as ‘prudence’ or ‘practical common sense’. [….] Phronesis is a sense or a tacit skill for doing the ethically practical rather than a kind of science. [Flyvbjerg 2006, pp. 371-371]

Science in the age of the Enlightenment — which is at the foundation of science in the west today — emphasized episteme and techne. However, the primacy of phronesis in Aristotle’s philosophy has required reiteration.

In Aristotle’s words phronesis is an intellectual virtue that is ‘reasoned, and capable of action with regard to things that are good or bad for man’ (Aristotle, The Nicomachean Ethics …). Phronesis concerns values and goes beyond analytical, scientific knowledge (episteme) and technical knowledge or know how (techne) and it involves judgements and decisions made in the manner of a virtuoso social actor. [….]

Aristotle was explicit in his regard of phronesis as the most important of the three intellectual virtues: epistemetechne, and phronesis. Phronesis is most important because it is that activity by which instrumental rationality is balanced by value-rationality, to use the terms of German sociologist Max Weber; and because, according to Aristotle and Weber, such balancing is crucial to the viability of any organization, from the family to the state. [Flyvbjerg 2006, p. 370]

In a common sense view of the world, applying “know why” (episteme) and/or “know how” (techne) in the wrong place, wrong time and/or with the wrong people signals immaturity in practice. Applying “know when, know where, know whom” appropriately demonstrates an appreciation of the situation at hand, a possible implicit weighing of values, and the setting for an appreciative system.

3. Domains of systems thinking can be categorized into systems theory, systems methods, and systems practice

One breakdown of systems thinking is a three way categorization into systems theory, systems method and systems practice. This is not the only way to analyze systems thinking, yet it may be useful in an alignment with episteme, techne and phronesis. Here’s a list of some top-of-mind systems thinking domains as a sample of the breadth of knowledge, inquiries and approaches. This list is intended as indicative, rather than exhaustive, so other system thinkers may have different views. In addition, since theory and methods and practice can all influence each other, there are some ties between the domains that may not be readily apparent.

Table 2: Systems theory, systems methods and systems practice aligned with intellectual virtues
Categories of systems thinking: Systems theory Systems methods Systems practice
Primary intellectual virtue: Episteme Techne Phronesis
Colloquial description: Know why Know how Know when, know where, know whom
Systems thinking domains:

Even the most well-read systemicists may have only a passing recognition across the multitude of theories, methods and practices labelled as systems thinking or systems science. One authentic path through the body of knowledge is historical, as key figures in the systems movement have each had a system of ideas that has influenced his or her work. Surfacing some of the relationships and social ties between proponents of the systems movement was an objective of systems sciences connections conversations.

4. Incomplete systems thinking may suggest paths through which gaps may be filled

Presuming an interest in rounding out a knowledge of systems thinking, each individual comes from a different background of experiences. We each take different courses in secondary and post-secondary education, and then avocations and passions bring us along different paths. As an exercise, let’s think through three cases in which systems thinking might be developed from different staring points. These are summarized in the following table.

Table 3: Paths to develop complete systems thinking
Incomplete systems thinking presents gaps to be filled (Episteme * Techne) –> Phronesis (Techne * Phronesis) –> Episteme (Episteme * Phronesis) –> Techne
Weakness Weak on know when, know where, know whom Weak on know why Weak on know how
Potential path Deduction Induction Abduction

Summarizing approaches to logic described by Peirce:

  • Deduction starts from a rule (major premise), applies a case (minor premise) and concludes with a result.
  • Induction starts from a result (major premise), applies a case (minor premise) and concludes with a rule.
  • Abduction starts from a rule (major premise), applies a result (minor premise) and concludes with a case.

Let’s flesh out some potential descriptions where systems thinking needs development.

Path (a): Strong on episteme and techne, weak on phronesis:
A person could be strong in episteme (e.g. classroom or book learning) and techne (e.g. methods and techniques), but weak in phronesis (e.g. practical experience). A deductive path of learning could include conscious placements into those situations (i.e. appropriate when, where and whom) on which the phronesis could be developed. This is the spirit behind job rotation, in the development of well-rounded employees.
Path (b): Strong on techne and phronesis, weak on episteme:
A person could be strong in techne (e.g. project management) and phronesis (e.g. hand-on experience), but weak in episteme (e.g. theoretical science). An inductive path of learning could include mentoring by a master who can develop insight into how prior experiences are (or are not) similar. Such regimens of abstraction can deepen expertise, separating the novice who still needs the textbook from the guru who writes them.
Path (c) Strong on episteme and phronesis, weak on techne:
A person could be strong on episteme (e.g. theory) and phronesis (e.g. learning by doing), but weak on techne (e.g. standardized processes). An abductive path of learning could propose repeatable methods that might cover the most common situations, and gradually expand to include greater variability. Technique can be improved both at individual and collective levels.  

Getting some parties to admit to gaps in knowledge may require working on their humility. Identifying the gaps to be filled is a first step in learning.

5. Systems thinking has evolved with roots in linear causality, circular causality, complexity theory and reflexivity theory

The domains of knowledge in systems thinking (and the systems sciences) have not been standing still. Critics of mainstream science often center on a philosophy of logical positivism. In a broader view, Stuart Umbleby describes four models used in the systems sciences: (i) linear causality; (ii) circular causality; (iii) complexity theory, and (iv) reflexivity theory:

One way to understand how the system sciences are developing is to look at the creation of new methods for conducting inquiry. Presently four models are being used in science.

1.1 Linear Causality
Linear causality is the way most science has been done and is still being done. It is the way most dissertations are written. It is supported by many statistical techniques, including multiple regression. It has numerous advantages. Hypotheses can be falsified. Propositions can be assigned a level of statistical significance. The objective is to create descriptions which correspond to observations.
1.2 Circular Causality
Circular causality is essential to any regulatory process – a thermostat, an automated assembly line, driving a car, or managing an organization. Circular causal processes can be modeled with causal influence diagrams and system dynamics models. Often a psychological variable is involved, e.g., perception of…, or desire for…
1.3 Complexity Theory
Complexity theory is primarily a method of computer simulation. It is based on cellular automata and genetic algorithms. The “game of life” is a simple example. The basic idea is very general and encompasses competition among species or corporations, also conjectures and refutations in philosophy. There are two processes involved — the creation of new variety and selection of appropriate variety. The combination of these processes explains emergence of new order.
1.4 Reflexivity Theory
Reflexivity theory requires operations on two levels – observing and participating. Reflexivity involves self-reference, hence paradox, hence inconsistency. Reflexivity violates three informal fallacies – circular arguments, the ad hominem fallacy, and the fallacy of accent (referring to two levels of analysis at one time). [Umpleby 2010, p. 1]

Reflexivity theory has only begun to rise over the past few decades. Since systems thinking centers on appreciating with multiple levels and time scales in relations between parts and wholes, reflexivity is not necessarily such a big stretch for the immersed. The conceptual challenge is likely greater for those more comfortable within the boundaries of disciplinary-focused perspectives. Scientists successful in the current scientific mainstream may not be so motivated to go through a paradigm shift.

… we can now ask which models are considered acceptable by the contemporary academic community. Linear causality, the first model, is the dominant conception of science. It is what doctoral students are taught to use when writing dissertations. Circular causality, the second model, was used in first order cybernetics, but it involves circularity, which some people interpret as fallacious reasoning. Complexity, the third model, includes Stephen Wolfram’s [2002] “new kind of science” and the idea of self-organizing systems. Complexity theory uses a new kind of mathematics, but does not violate any informal fallacies. It is easily recognized as “science” by people trained in the physical sciences. Reflexivity, the fourth model, is very close to second order cybernetics.

Models 1 and 3 – linear causality and complexity theory — are acceptable. No informal fallacies are violated. Model 2 — circular causality — is suspect. It involves circular reasoning. But it has proven to be useful. Model 4 — reflexivity — violates 3 informal fallacies, so is highly suspect. Scientists shun it. They do not take it seriously. Indeed physical scientists seem to have a visceral reaction against it. But the informal fallacies are just “rules of thumb.” [….]

Practicing managers and social scientists will readily agree that human beings are both observers and participants in social systems. Indeed, they say this idea is “not new.” But this perspective is not permitted by the classical conception of science. The conception of science needs to be expanded in order fully to encompass social systems. [Umpleby 2010, pp. 4-5]

Second order cybernetics dates back into the 1970s.  Reflexivity has made significant inroads into social theories in cultural anthropology (e.g. Pierre Bourdieu, with An Invitation to Reflexive Sociology and in understanding the workings of financial markets (e.g. George Soros, with a General Theory of Reflexivity).

6. Opportunities to refresh ties between systems thinking and action science, theory of practice and social learning could be pursued

Some ways of thinking in domains regarded as outside the systems movement may not have been recognized as part of systems thinking, yet could be highly compatible. With some effort from both sides, bridges could be built for mutual benefit. Many of these advances has been associated with interests in (human) action, practice and (social) learning.

Action science, as originally developed by Chris Argyris, was the foundation for the more familiar concepts of organizational learning and double-loop learning. Systemicists have often closely related this work to learning as described in Steps to an Ecology of Mind, by Gregory Bateson.

(Action science) is an inquiry into social practice, broadly defined, and is interested in producing knowledge in the service of such practice. Thus, what counts as a solution for action science both overlaps with and diverges from prevailing scientific criteria. Like the empirical-analytic tradition, action science requires that knowledge include empirically disconfirmable propositions that can be organized into generalizable theory. But at the same time, it also requires that these propositions be falsifiable in real-life contexts by the practitioners whom they are addressed. Like applied research, action science requires knowledge to be useful. Yet in so doing it emphasizes the designing and implementation of social action, and it rejects the current dichotomy between basic research and applied research. It instead asks that its knowledge illuminate basic issues in ways that are at once generalizable and applicable in particular cases. (Argyris et al. 1985, p. 232)

Theory of practice was revolutionized by Pierre Bourdieu. His system of ideas has influenced a generation of sociologists and organization scientists. Bourdieu didn’t believe in defining terms as independent and objective entities. A concise description appears in a chapter by Moishe Postone, outlining the key ideas of habitus, capital and field, in a reflexive perspective:

[In] attempting to transcend the opposition between science and its object, Bourdieu treats science and scientists as part and product of their social universe. The scientific field can lay claim to no special privilege as against other fields; it too is structured by forces in terms of which agents struggle to improve their positions. Science seeks to analyze the contribution of agents’ conceptions to the construction of social reality, while recognizing that those conceptions frequently misrecognize that social reality. By the same token, scientists’ constructions of their own reality — the scientific field and the motivations for scientific behavior — often misrecognize that reality. Consequently, it is essential to advance and endorse a reflexive science of society.

Bourdieu’s project, then, can be described generally as an ongoing attempt to overcome theoretically the oppositions that have characterized social theory and to formulate a reflexive approach to social life. Three fundamental concepts lie at the heart of this project: “habitus,” “capital,” and “field.”

The notion of habitus is central to Bourdieu’s theory of practice …. To this end, Bourdieu treats social life as a mutually constituting interaction of structures, dispositions, and actions whereby social structures and embodied (therefore situated) knowledge of those structures produce enduring orientations to action which, in turn, are constitutive of social structures. Hence, these orientations are at once “structuring structures” and “structured structures”; they shape and are shaped by social practice. Practice, however, does not follow directly from orientations, in the manner of attitude studies, but rather results from a process of improvisation that, in turn, is structured by cultural orientations, personal trajectories, and the ability to play the game of social interaction.

[….] The habitus is at once intersubjective and the site of the constitution of the person-in-action; it is a system of dispositions that is both objective and subjective. So conceived, the habitus is the dynamic intersection of structure and action, society and the individual. [….]

Bourdieu’s notion of capital, which is neither Marxian nor formal economic, entails the capacity to exercise control over one’s own future and that of others. As such, it is a form of power. This notion of capital also serves to theoretically mediate individual and society. On one level, society is structured by the differential distribution of capital, according so Bourdieu. On another level, individuals strive to maximize their capital.[….] The capital they are able to accumulate defines their social trajectory (that is, their life chances); moreover, it also serves to reproduce class distinctions.

Much of Bourdieu’s work focuses on the interplay among what he distinguishes as social, cultural, and economic capital. [….] Although the economic is crucially determining, it must be symbolically mediated. [….] Symbolic capital functions to mask the economic domination of the dominant class and socially legitimate hierarchy by essentializing and naturalizing social position. [….]

The purpose of Bourdieu’s concept of field is to provide the frame for a “relational analysis,” by which he means an account of the multi-dimensional space of positions and the position taking of agents. The position of a particular agent is the result of an interplay between that person’s habitus and his or her place in a field of positions as defined by the distribution of the appropriate form of capital. The nature and range of possible positions varies socially and historically.

Each field is semi-autonomous, characterized by its own determinate agents (for example, students, novelists, scientists), its own accumulation of history, its own logic of action, and its own forms of capital. The fields are not fully autonomous, however. Capital rewards gained in one field may be transferred to another. Moreover, each field is immersed in an institutional field of power and, even more broadly, in the field of class relations. Each field is the site of struggles. [….]

Bourdieu interrelates the three central concepts we have outlined. He conceives of social practice in terms of the relationship between class habitus and current capital as realized within the specific logic of a given field. An agent’s capital is itself the product of the habitus, just as the specificity of a field is an objectified history that embodies the habitus of agents who have operated in that field. The habitus is self-reflexive in that, each time it is animated in practice, it encounters itself both as embodied and as objectified history.

On the basis of these three concepts, Bourdieu has attempted to formulate a reflexive approach to social life that uncovers the arbitrary conditions of the production of the social structure and of those dispositions and attitudes that are related to it. [….] [Postone et al. 1993, pp. 3-6]

Social learning is generally known as the domain of “communities of practice”, originated by Etienne Wenger. With Bourdieu as one of his foundations, learning is expressed in both the contexts of individuals and collectives in a framework that includes (i) meaning, (ii) practice, (iii) community, and (iv) identity.

A social theory of learning must … integrate the components necessary to characterize social participation as a process of learning and of knowing. These components … include the following.

1) Meaning: a way of talking about our (changing) ability — individually and collectively — to experience our life and the world as meaningful.

2) Practice: a way of talking about the shared historical and social resources, frameworks, and perspectives that can sustain mutual engagement in action.

3) Community: a way of talking about the social configurations in which our enterprises are defined as worth pursuing and our participation is recognizable as competence.

4) ldentity: a way of talking about how learning changes who we are and creates personal histories of becoming in the context of our communities.

Clearly, these elements are deeply interconnected and mutually defining. [Wenger 1999, pp. 4-5]

The domains of systems thinking and systems engineering certainly have perspectives on action, practice, and learning. As we seek to deepen our appreciation of the meaning of (the) systems science(s), we should be aware of advances in other fields that could help to inform our understanding of the world.

Appendix: On applied philosophy

The above essay has jumped from science to broader definitions of thinking, and philosophy. In the same way that engineering is applied science, we shouldn’t hesitate to expand a view of science as applied philosophy. There’s a history of applied philosophy with the history of the systems movement, as described in the memoirs of Russell Ackoff.

Churchman and I designed an Institute of Experimental Method that was intended to conduct interdisciplinary research and problem solving where societies were involved. We took our proposal to the President of University [of Pennysylvania] who showed interest in it. He said he would create such an Institute if we could get the support in writing of three different departrnents. lt took almost a year to get the approvals required. In the meantime the President had retired due to illness and had been replaced by a lower level officer of the University. When we showed him the proposal and conditions for approval that his predecessor had established, he told us he was not bound by agreements made by his predecessor. He showed no interest in our proposal. I took that as a rejection of our idea and saw no reason to remain at Penn even if I could have.

I graduated with a PhD in the spring of 1947. During the summer that followed I accepted an appointment in the Philosophy Department of Wayne University in Detroit. (lt was not then a state supported institution. That came later, after I had left the University.) The Dean of the College had assured me that he would support the creation of an Institute much like the one Penn had rejected. lt was to be called the Institute of Applied Philosophy. [Ackoff 2010, pp. 98-99]

Criticism of “high science” are not new. The disconnects from Plato through Descartes have been described by Stephen Toulmin, in support of broader views of science (e.g. participatory action research).

The High Science model, then, rests on two chief assumptions. The older of these — the assumption that the only authentic knowledge is universal, general and timeless — can already be found in the Greek philosophers of Antiquity. This belief is what gave the theorems of abstract geometry their particular charm for Plato and his successors; within an axiomatic system, our understanding of spatial relations and other properties of Nature achieves — so they dreamed — a general, eternal, immutable order unavailable to the pedestrian, disorderly facts of everyday experience.

This superior kind of knowledge came to be called episteme (theoretical grasp): the Platonist dream was that the knowledge we generate in dealings with the world can be organized into systems of theorems, from whose axioms all humbler, more detailed kinds of knowledge can be formally deduced. As the inscription over the entry to the Academy declared, no one could hope to grasp the principles of public affairs who had not already mastered the model High Science — i.e. geometry.

The other assumption of thc High Science model is more recent and more elaborate. In all his own writings, from 1629 on, René Descartes combined a scientific admiration for Galileo’s telescopic discoveries with philosophical commitment to this kind of Platonism. After 1640 the use of axiom systems to organize knowledge and experience of other kinds soon became common form: Isaac Newton’s Mathematical Principles of Natural Philosophy was just one very successful example out of many. In this respect theoretical physicists, up to James Clerk Maxwell and beyond, have shared Descartes and Newton’s Platonic vision, of episteme as the exemplar of high, pure science.

Before long, the geometrical model of a scientific theory was linked to half a dozen other maxims of method. These concerned

  • the kinds of experiments and observations that. are acceptable in a Science;
  • the objective. detached posture of the scientist toward his objects of study;
  • the inferior status of ‘practical’ knowledge, as a secondary (applied) mode of understanding.

As a youth, Descartes found Poetry and History entrancing; but, when introduced to Philosophy, he decided that those fields — though pleasing — lacked intellectual depth. History, in particular. was like Foreign Travel: it broadened the Mind. but it did not deepen it. Only mathematical knowledge (he concluded) could do that!

If, in methodological terms. the only legitimate approach to Science is to accept the Platonist vision of episteme — with or without its Cartesian additions -— the methods of inquiry of participatory action research are philosophically indefensible. Confronting these methodological hurdles, it falls at the first fence. It has practical not theoretical aims, it fails to separate the observer and observed, and its empirical results cannot be generalized or abstracted from their original loci; the list of defects goes on and on. lf we are to find a way ahead from this point, we shall need another line of approach, powerful and reputable enough to stand comparison with the familiar model of High Science. [Toulmin 1996, pp. 206-207]

Aristotle’s criticism of the Platonic model are further fleshed out by Toulmin.

Later in the Ethics, Aristotle goes on to classify the different species of knowledge: these included techne (know how) and phronesis (the ability to spot the action called for in any situation) as well as Plato’s favored episteme (theoretical grasp}. In this way, he raises the possibility that different inquiries can be pursued and judged ‘rational,’ in their own different, yet appropriate ways. He elaborates on this view in later works, starting with the Art of Rhetoric. Geometry may be admirable in its way; but practical inquiries like clinical medicine and helmsmanship do not demand (say) the formal skills possessed by mathematical whizzkids. Practical competence in such arts is acquired, rather, over the course of long experience.

Aristotle treats the multiplicity of intellectual disciplines in a democratic, not in an elitist way. We need not enthrone any single discipline as the Master Science, whether geometry for Plato or theoretical physics for 20th century readers. Nor need we rule out, as unsound, inquiries that do not follow the methods or conform to the standards of the Platonist ideal. Each discipline can match its methods and standards to its special subject matter and problems. Fields like clinical medicine, horticulture and ornithology are, thus, no more bound than political science to produce axiomatic theories, Indeed, from this alternative point of view, the High Science model is not so much convincing as pretentious. [Toulmin 1996, pp. 207-208]

To bring us up to date from the ancient Greeks to the 20th century, Rojcewicz provides an interpretation of Heidegger’s interpretation of Aristotle (interpreting Plato). We add technology into the mix.

For Heidegger … technology is a theoretical — not a practical — affair. Technology is not directed toward making things, doing things, finding means to ends, instrumentality. More precisely, technology is primarily a theoretical affair. There is a practical side to technology, but that is secondary; it follows upon the theoretical understanding. Technology is, of, course, related to making things and doing things, but it is so related only because technology first of all is an understanding of what things are in general. Technology does determine our doing and making, but only because it determines what we take to be a thing in general in the first place. Technology is not practical directly, but only indirectly: by disclosing to us what constitutes beings, it provides us with a guideline that governs all our relations to beings, including our practical relations. lt is in virtue of the truth disclosed in technology, i.e., in virtue of its theoretical significance, that technology is practical. Technology can do things only on account of what it sees, and what it sees is that which makes a being be a being at all. [Rojcewicz 2006, pp. 56-57]

Techne can then be framed with the changeable, and episteme with the unchangeable.

What then, for Aristotle, is the difference between techne and episteme, between techne and knowledge pure and simple? As Heidegger says, they differ with respect to what they disclose and how they disclose. Episteme discloses what is unchangeable, techne what is changeable. And episteme is disclosure for its own sake, while techne has an ulterior motive beyond mere disclosure. Thus episteme is literally knowledge pure and simple: it is knowledge of what is simple (the eternal and unchangeable), and it is pure knowledge (for its own sake). Let us delve a little more deeply into this basic characterization of episteme in order to understand how techne differs from it.

For Aristotle, knowledge does not change. What most properly deserves the name knowledge is constant and permanent. But such a knowledge is possible only of unchanging objects. For Aristotle it is primarily the object that determines the character of the knowledge, not vice versa. There can be genuine knowledge, then, only of what is changeless, and what is changeless is eternal, never having come into being and never going out of being. Hence, there is no genuine knowledge of individual things; knowledge is possible only of the principles of things, the essences of beings (in Plato’s terms, the Ideas), and the ultimate principle of beings is Being. The most genuine knowledge is then ontological knowledge, and this more than anything else deserves to he called knowledge, episteme. Accordingly, there is only one genuine episteme, and that is philosophy or the understanding of Being as such. This knowledge has no ulterior motive, since the object of the knowledge, Being, cannot be influenced or manipulated or changed in any way. This knowledge is disclosive looking for the mere sake of disclosure; it is purely theoretical.

Techne, in contrast to episteme, is knowledge of changeable things; its objects come and go and change in various ways, and so techne cannot be considered knowledge in the most proper sense. In particular, its objects are not the changeable things of nature, which come and go of themselves, but the things that come and go due to a role played by the one who possesses the techne. This person discloses what does not yet exist concretely; and that disclosure is subject to change, since the thing may turn out differently than it was envisioned. [Rojcewicz 2006, p. 59-60]

With a shared understanding of the foundational philosophies, the thinking originating in the times of the ancient Greeks may be advanced with our contemporary pursuits.


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