Current schools of thought on the sources of objectivity

1. Literalist Fundamentalism: Hybrid of empiricism and scripturalism. Serves capitalism and/or tribalism.
2. New Ageism: Hybrid of tropes of modern science, superstition and common but uncanny experiences, which remain scientifically unexplored due to # 5.
3. Post Modernism: Ever changing truth lies between the lines in the ceaseless revolution against narratives of power.
4. Basic Science: Carries on halfway between rigour and rigor-mortis owing to emphasis on economic benefits, rigid schools of thought, and being a trope of legitimacy unto itself.
5. Reductionist Science: Puts the methodological cart before the ontological horse, confuses the intellectual filing cabinet for reality, hung up on "building blocks", misses context, life, imagines operational definitions to be exhaustive.
6. Promethean Science: A hubristic triumphalism of technology that, like dominionist religions, celebrates our conquest/dominion of nature.

Mental Models: Five of Many Basic Assumptions Currently in Need of Revision

1. The Universe is Composed of Fundamental Building Blocks

This view has proven fruitful in certain types of research, but I wonder why people think that what exists in the universe can be exhaustively explained by reference to fundamental components and their interactions? Effects and causes occur at many scales of granularity.

I also wonder what makes people lean toward the idea that there is a certain "fundamental" aspect of reality? Is the notion of a foundational layer of reality a product of experience or a conceptual hangup?

 

2. Individual Interests Drive Collective Behaviours

Individuals are born into an existing social milieu and learn the language, norms and aspirations of their group. Though I'm not one to say that we are all simply products of our socialization - people have unique sets of abilities and unique ways to express them - in this chicken/egg scenario, the collective comes first. Therefore the collective will is not an aggregation of individual interests and the notion of an "original position" where individuals came together to forge a society is a mythical fancy with no explanatory value.

Another mistake fed by this assumption: Researchers assume that it's altruism or community feeling that needs to be explained rather than individualism because, ironically, individualism is the current ideological norm and raw self interest is seen as the more fundamental fact. This assumption is not objectively justified. It's an idea that supports the economic system and preserves the social order by allowing individuals to be seen as wholly responsible for their own lack of success, regardless of social realities.

3.  All Biological Traits are Products of Adaptation by Natural Selection (Fitness)

Evolution occurs but that doesn't mean that every trait of every species can be explained as a positive contribution to survival. Species not only pass along traits that positively enhance the possibilities of survival, but traits that are not maladaptive - traits that are just there - or even weaknesses that are compensated for by a cluster of other traits.

The attempt to explain every trait in terms of adaptation begs a lot of questions.  Nearly every species eventually becomes extinct or evolves into a different species. Evolution cannot directly explain the biological mechanisms that give rise to the emergence of a new trait, but only indirectly - only insofar as random mutations occur that  aren't survival liabilities or that are likely to enhance survival opportunities.

4. There Are No Natural Final Causes (No Whys, only Hows)

If you're wondering why I've included this, it's because it's generally assumed that any final cause or purpose (sometimes called "teleology") of existence would imply a non-natural (metaphysical) factor. People who believe themselves to be scientifically minded try to distance themselves from the idea that there are purposes in nature because they assume it necessarily aligns them with proponents of reviled "intelligent design" (ID) theories.  ID theories suppose that matter is a passive receptacle for the purposes implanted in it by a divine architect of the whole universe - an architect who cares about us and who especially cares that we are purified of contaminants from our participation in the natural material world in particular - so one can hardly blame them.

In a sense though, the struggle for existence would be a natural final cause, wouldn't it? The drive to survive is a natural purpose, though not necessarily one that is embodied only in individuals.  Scientifically minded folks need to question whether the idea of natural final causes really is an oxymoron and get over feeling guilty-by-association. (This is just one instance of reactive distancing that shuts doors on avenues of meaningful inquiry.)

5. The Ability to Scientifically Predict and Control Phenomena Proves Determinism

To predict and control what happens, a scientist needs to be able to spell out what influences events in the most generic and universal way possible. This is done by eliminating variable, unpredictable influences by trial and error (or prior knowledge) and then by refining the definition of the predictable influences and their objects so that they can be stated in the form of an equation or "law of nature" that plays out within a generic frame of reference.  For example, Newton's laws of motion refer to "bodies" without any reference to their shape or density, and to "motion", without any reference to the wind's influence, etc. To control something, knowing a number of such general laws, technologists can exactly arrange certain chains of events so that they unfold in predictable, mechanical ways. For instance, we have technologically advanced machines. Parts are arranged, the right amount of power is supplied, and presto...


Only some kinds of investigation allow for this kind of simple analysis and arrangement. For most events, it is not possible to eliminate unpredictable influences and isolate the predictable ones because there is no way to predefine a generic frame of reference within which potential influences are in play.  There is therefore no law in relation to which the influences of an event are "exactly arranged" so that the event rolls out in a pre-determined, mechanical way. Most events are  neither physically nor metaphysically predetermined.

...To be continued...

Initial Conditions and Predictability

According to physicist, Eugene Wigner (link to article), physics is possible because we are able to identify regularities in nature.

The world around us is of baffling complexity and the most obvious fact about it is that we cannot predict the future... It is, as Schrodinger has remarked, a miracle that in spite of the baffling complexity of the world, certain regularities in the events could be discovered. One such regularity, discovered by Galileo, is that two rocks, dropped at the same time from the same height, reach the ground at the same time. The laws of nature are concerned with such regularities...

This is surprising, he says, for a few reasons. The first is that it is true everywhere on earth and it will always be true, i.e., it is invariant. The second reason that it is surprising is that this invariance "is independent of so many conditions that could have an effect on it." It doesn't matter where on earth or by whom the rocks are dropped and "there are innumerable other conditions which are all immaterial from the point of view of the validity of Galileo's regularity." He says,

The irrelevancy of so many circumstances which could play a role in the phenomenon observed has also been called an invariance. However, this invariance is of a different character from the preceding one since it cannot be formulated as a general principle. The exploration of the conditions which do, and which do not, influence a phenomenon is part of the early experimental exploration of a field. It is the skill and ingenuity of the experimenter which show him phenomena which depend on a relatively narrow set of relatively easily realizable and reproducible conditions. (Italics added.)

This is important when it comes to understanding the surprising thing about making predictions. Wigner says, "the law of nature is contained in the statement that the length of time which it takes for a heavy object to fall from a given height is independent of the size, material, and shape of the body which drops."

Given certain "easily realizable and reproducible" Initial Conditions (ICs) and a Law of Nature (LN), then a Prediction will follow. (IC & LN) > P. However, 

the laws of nature can be used to predict future events only under exceptional circumstances - when all the relevant determinants of the present state of the world are known. It is also in consonance with this that the construction of machines, the functioning of which he can foresee, constitutes the most spectacular accomplishment of the physicist. In these machines, the physicist creates a situation in which all the relevant coordinates are known so that the behavior of the machine can be predicted. Radars and nuclear reactors are examples of such machines.

The two important points I draw from the preceding exposition are:

1. In order to apply a law to make a prediction you need to identify the relevant conditions (ICs).
2. The ability to isolate phenomena whose regularity can be demonstrated with easily reproducible conditions cannot be summed up in a general principle. 

 To those two points I would also add an idea that I think follows from an insight of Stuart Kauffman, author of Reinventing the Sacred (linked on the sidebar) where he says, in analyzing mechanical systems, 

physicists since Newton have put in the constraints..."by hand" as what are called the mathematical "boundary conditions" on a system, rather like the boundaries of a billiard table, that keep the balls from rolling off into infinity or under the table. Given the boundary conditions, physicists state the initial conditions, particles and forces, and solve the equations for the subsequent dynamics...

But in the real universe, we can ask, "Where do the constraints themselves come from?"(pp. 90-91) (italics added.)

Although in principle it might be possible to retroactively determine the sequence of events that gave rise to a naturally occurring phenomenon (then again, there's the problem of infinite regress), no one could specify the relevant conditions in advance of every phenomenon-to-be in this complex world. What would we be looking for?


Kauffman (link to book) discusses the evolution of life and considers Darwinian preadaptations; e.g., three bones in the jaw of an ancestral fish that become bones in the middle ear in species descended from it. At the time this ancient fish lived, was there any way to predict the role of its bones in later species, let alone what later species would emerge?

This is not just an issue of complexity or chaos; i.e., sensitivity to initial conditions (a.k.a "the butterfly effect"). It is that, as Kauffman says, we can't prestate the relevant conditions  (p. 139 ff). What potentials will become actualities?  In Kauffman's view, this is not just an epistemic limitation, it is an ontological one. He says, "the evolution of life violates no law of physics, but cannot be reduced to physics." Not all of nature is law governed. 

So it seems to Kauffman, and to me, that the "natural law" model of a mechanistic universe has limited applicability; i.e., to "phenomena which depend on a relatively narrow set of relatively easily realizable and reproducible conditions."


We cannot completely predict the future, and generally that idea gives me comfort. Nature has space to play.

Also see P. Anderson, More is Different

Materialists aren't materialists.

We don't live in a "materialist" society.  The prevailing views about what's real in the world are not based on a materialist philosophy, but on an inverted kind of transcendence, the decaying legacy of an ancient metaphorical, conceptual separation of heaven and earth. (This separation has evolved over history, but I'm starting with its most recent incarnation.)

So, what is inverted transcendence? Think of it this way. Since ancient times, we have believed that the most knowable is the most real. The most profound way we have of knowing our world comes through the use of concepts and mathematics. Concepts and mathematical relationships describing nature are idealizations of patterns of regularity that we find in nature. 

To get objective about nature, we have to arrange it so it fits our conceptual and mathematical tools, our idealizations of it. This has proven very successful in areas where researchers can control and eliminate local contingencies to get to the universally constant laws (such as laws of motion.) This is what allows people to build reliable machines. However, not all of nature is amenable to this approach to research (unless you think that nature is "nothing but" particles in motion; i.e., unless you privilege that one scale of things and stamp it with the label, Reality, and talk of building blocks, putting the methodological cart firmly before the ontological horse as is the wont of reductionists...) 

Nature is not just particles in motion, it exists on many scales - it is ecosystems, tectonic plates smashing together, the act of breathing, rustling leaves, strange creatures swimming by vents in the ocean floor, reproducing, etc.  These things have power to make changes in the world. Not all causality occurs at the level of sub atomic particles. 

One cannot locate and eliminate local contingencies and make rigorously controlled experiments when studying human behaviour and other phenomena. All natural phenomena are complex.  Human beings reduce natural phenomena to idealized mathematical objects, quantities and relations - particles in motion governed by natural laws. 

So, from a scientific perspective, the matter we call objective reality is a conceptually reduced scale of existence - a useful idealization. Note the absence of any value ideal in those mathematical idealizations, though. Nature, as seen through the reductionist lens, has no purpose. So what are we transcending with our idealizations of matter? Our vitality? Our lived experiences? Our woes and joys? Certainly there is joy in the act of genuine discovery, but that's peripheral to the reductionistic project. More and more people talk of the next stage of evolution as a cyborg society, to my mind a symptom of the nihilism in the project. Even basic drive is purpose. Even this nihilism is purpose.

So what is inverted transcendence, as distinguished from materialism? Painted in an extreme kind of way, I'd say an inverted transcendence is one which focuses on reduced idealized matter, not on nature, and has as its point the reduction and idealization of nature, and the subjection of our human interests and cares to that model.  Or perhaps I could put it this way: Heaven and earth became separated and nature was reduced to an idealized inert matter. It was virginalized. Next, heaven was eliminated from the picture of how the world is,  leaving us with laws of nature or what Sheldrake calls "the ghost of the god of the world machine." (Have a listen to Minute 13:30 to 15:30 of his CBC podcast. I'm deeply skeptical of many of Sheldrake's explanations, but like his questions.)

Having shied from understanding material nature in its richness, we're not really asking or learning about ourselves in a way that situates us in nature, where we might gather the learning we need to adjust and make the right decisions. There is a loss of meaning. Meanwhile, we're inundated with products. We're all dressed up with nowhere to go, except to an ecological tipping point.

I don't think the solution to this strange nihilism is to reinstate some kind of theological or platonic heaven but to heal the split and come back to earth. To do that, we need to find a new way of looking at matter, while questioning what it is we wish to transcend.

Matter is not inert.

Change Discourse: An Aside on Planning and Evaluation

In large organizations, in the accepted practices of planning and evaluation, we are hampered by our inability to acknowledge unanticipated benefits, i.e., the creativity of what is proposed. We seem to be unable to value options that we haven't anticipated in advance or even to accommodate valuations of unanticipated options. What would count as legitimation in these instances?  The unanticipated benefit cannot be considered relevant, based on pre-established criteria.

Why do we deprive ourselves of anything more than our presupposed potential?  The standard (ontological and meta-ethical) notions of objectivity and fairness in evaluation are in need of a major rethink, especially in a complex, rapidly changing world where future potentiality becomes at least as important as present actualities. Adaptability and responsiveness are more important than adhering to artificial and outdated notions of objectivity, which for at least two millennia, have been more about projecting our conceptual filing cabinets on events than on encouraging openness to new an novel ideas and approaches. To add irony to insult, in today's variant, to mimic the successful model of reductionist science, it is assumed that the ability to assign a number to some evaluative criterion makes that criterion objective. 

The difference between living and mechanical linear/reductionist notions of objectivity needs to be emphasized. In the linear/reductionist model, the relevant determinants of an event  are isolated and identified in a rigorous way, such that they can be arranged and used in planning experiments and building machines. As successful as this method has been, however, according to scientists such as Eugene Wigner, the approach legitimately applies to only a small set of relatively easily manipulable things (which is why basic physics is about necessary laws and anything more complex is statistical at best at the lowest level of granularity.)  The attempt to apply it to a large open-ended organization occasions the kinds of issues described by Burt Perrin (Paragraph 103). 

Stuart Kauffman shows that a living system is one where the boundary conditions are intrinsic to the phenomena under investigation, which are not "placed by hand" as they are in a more mechanistic model. He further argues(cf. pp. 131-143) that there is "no way to pick out the relevant collective variables that will play a causal role in the further evolution" of living systems.  (p.140-1) Nevertheless, we put our methodological carts before our ontological horses, and worse, we justify our aims based on our methods, rather than the reverse. This is not only reductionist. It reduces us.


Our model of measurement needs to change from a mechanical one to one that respects that we work in living systems. We need to use something a bit less pedantic than a pre-established list of specific criteria for evaluation and learn how to acknowledge context, the context being our actual overall aims in relation to what is being evaluated both now, and as they change, with learning, over time.  We need to look at a higher level of granularity if we're really serious about innovation or getting beyond a nihilistic means-focused outlook (a hamster wheel).  This will require a sea change at every juncture. Responsiveness and resiliency will be key.

On Risk Aversion

Is risk aversion a fear of auditors or bad press...or is it denial of the natural transformation that is occurring now towards models of complexity and resilience? It seems we prefer the illusion of control, delivered by models that are
- analytical,
- artificial,
- compartmentalized,
- categorical
- linear,
- mechanical, and
- simplistic.

To be able to achieve manageable simplicity, we would have to be able to identify and control the context, the boundaries, the parameters in which we operate. It is no longer possible to imagine that that we can. The flurry of performance measurement gone mad is probably a reaction formation. Facile metrics are a tragic and total waste of resources, and that's one of the few simple things we do really all know.

Conceptual Filing Cabinets are not Reality

Ever noticed that when corporate downloads an initiative to remedy an internal management problem, the effects on the ground tend to be the opposite of what was intended? Without going into details, this may explain why. Mintzberg said:

"Strategic planning is not strategic thinking. One is analysis, the other is synthesis"*

The fact is, the corporate structure tends to be organized in terms of business lines or branches, so initiatives get forumulated around compartmentalized resources.  That means analytical thinking will predominate in planning - and analytical thinking relies on compartmentalized categories – checklist items. People mistake their conceptual filing cabinets for reality and are rewarded for substituting numbers for facts. But as some astute Brit said not long ago, “You don’t fatten a pig by weighing it.”  The success of mechanistic models of the past has seduced us to seeking "simple" solutions in  complex arenas, much more complex than are tackled by the hard numbers of "hard science." 

Most activities in business are dynamically interconnected and adjustments in one area can be offset by failing to consider their impact on other areas. Thinking strategically involves connecting the dots, lateral thinking, the use of the right brain, which is basically grounded in intention, will, and commitment (caring).

The first thing required for an effective strategy is that you genuinely care.

The second thing is flexibility and openness.

Some folks believe that analytical thinking is a cut above more poetic sensitivities and that it is the sole defender objectivity and of fairness. I'd like you to consider that such a view is rather narrow, sometimes honest but simplistic, other times useful to people with a power-for-power's-sake agenda. Models of evaluation based on analytical thinking are just as prone to manipulation and bias as any poetic kind of perspective. They are also dangerous as one doesn't need brute strength or mass hysteria to convince, but one can just point to "the numbers"as an incantation. This is less likely in very precise areas such as physics, but in business, there are just no exhaustive and exclusive definitions that can be reliably used for evaulative purposes. Our definitions and indicators are handy rules of thumb, never meant to be the be-all and end-all of evaluation. (ISO - I despair.) A planner can pick a few handy items from a potentially infinite list of possible indicators.  Nevertheless, those who employ a definition, a methodology, who fail to think things through broad-mindedly with an honourable meaning, purpose and value, who yet check a list of measures, have the advantage of the appearance of objectivity. This is a pernicious effect of the "trope of science" and needs rooting out.

*link no longer available.

Complexity and Employee Engagement

In a blog entry called Social Media vs. Knowledge Management: A Generational War , Venkatesh Rao states

[N]ot only do Boomers not get complexity, they are suspicious of it, thanks to their early cultural training which deifies simplicity. The result of this difference is that Boomer management models rely too much on simplistic ideological-vision-driven ideas. Consider, for instance, the classic Boomer idea of creating “communities of practice” with defined “Charters” and devoted to identifying “Best Practices.” No Gen X’er or Millenial would dare to reduce the complexity of real-world social engineering to a fixed “charter” or presume to nominate any work process as “best.” … I suspect, as Gen X’ers and Millenials take over, that the idea of vision and mission statements will be quietly retired in favor of more dynamic corporate navigation constructs.

I don’t know that this is strictly about the generations, but it certainly is insightful. I’d like to link this to the debate between what is called reductionism and complexity. Reductionists believe that “the truth is simple” and try to explain things by reducing everything to a narrow set of definable objects and a set of laws for their interactions. It’s as if there is a warehouse full of categorized objects (e.g., sub-atomic particles, genes) and a certain set of rules about how these are to interact, that are based on these things’ intrinsic, mathematizable qualities.

To me, it’s obvious that nothing in the universe is like that. First of all, laws are not forces, but mathematical conceptions of patterns of interaction. The idea that you can produce and explain things through the placement of objects and the application of laws leaves out a lot of information. For instance, in nature, when does a process start, and with what event or thing? What are the boundaries and parameters of a system of interactions? (How do you know what factors will be/become relevant?) Does one particle have the same properties as a number of them, and if not what is the “minimum”?

In recent years, complexity and complex systems theory have undercut a lot, but certainly not all (or even most), of reductionist thinking. Physicist, Robert B. Laughlin, for instance, argues that laws are not what causes certain interactions, but the reverse, laws are what emerge from interactions. Complexity theorist, Stuart Kauffman observes that reductionists just take parameters as givens, while showing that in living systems, life creates its own parameters (e.g., cell walls). Nature is self-organizing.

The point is that the old Newtonian paradigm is now crumbling and a new paradigm is well underway to becoming the reigning one, a point that Gilles Paquet has made with effect. So how does this tie to mission statements and charters and what-not?

Methodologies parameterize: They define limits of operation, without necessarily any awareness being generated of how the limits are drawn. This is why there are predictably going to be “perverse effects” of target-setting. Transaction quotas, for instance.

Programmed procedures might be great when you can reasonably identify all of the things that might have an effect on the outcome and control for that but, outside of a laboratory or some staple factories perhaps, life’s not like that. It’s putting the cart before the horse to think that the methods, processes, templates, and formalized procedures we've come up with so far provide adequate parameters of possible activity. Process templates and toolkits, initially touted as panaceas, are all eventually discarded, not always because of the shocking unforeseen, but due to the fact that they can never capture all of the complexity of normal operations. And besides, most people prefer to think rather than follow instructions, as long as they have the time to do so.

An over-reliance on methodology cuts off possibilities and prohibits learning and risk-taking and the use of good judgment, and sets up blind, impersonal systems as abstract authorities. The results of over-programming organizational processes mean you’ll lose the engagement of more risk-tolerant and innovative employees and wind up entangled in a web of rules.