Secondly, for new readers who found their way here within the past week – I tend to weave through several related themes at any given time.  I will get back to the socioeconomic evolution thread soon enough.  In the mean time I hope you will enjoy this as well…

Misinterpreted Life Scripts

Last week I wrote a quick reaction to a post by Cal Newport, in which he implied that diligent focus trumps all other factors in the pursuit of career success, including the innate suitability of the chosen career.  Now Cal has written a new post qualifying that position, but again his conclusions are too reductive for my tastes.  I hate to pick on Cal again – I don’t want this to read like a personal attack – but his new post provides such an ideal entry-point for a discussion of broader themes that I can’t pass it up.  That said, I want to be clear up front that I have a lot of respect for Cal’s work (I have previously cited him in a positive context) and the criticisms introduced in this first section will be qualified later on.

Cal begins by describing the events that led Daniel Kahneman and Amos Tversky (abbr: K&T) to initiate research into cognitive heuristics; research that would ultimately result in a Nobel Prize and the birth of behavioral economics:

“Our expert colleagues…greatly exaggerated the likelihood that the original result of an experiment would be successfully replicated,” Kahneman recalls of their results. “They also gave poor advice to a fictitious graduate student about the number of observations she needed to collect.”

“Even statisticians are not good intuitive statisticians,” he concluded

This small observation led to a bigger idea: perhaps humans are hardwired with cognitive shortcuts to help them make sense of an uncertain world, and perhaps these shortcuts, in certain situations, consistently lead to irrational conclusions.

This hypothesis was profound. At the time, social science believed that humans were fundamentally rational, and only emotion, like fear or anger, could lead us to irrational behavior. Kahneman and Tversky were proposing that humans, on the contrary, were wired for illogic. [emphasis original]

Cal proceeds to note the gap of five years between their first meeting and their now famous publication in the journal Science, concluding that though diligent focus was critical, it cannot fully explain the magnitude of their success.  His revised hypothesis:

The Directed Diligence Theory
It’s not enough to just focus relentlessly on a small number of things (though this is almost always necessary). You must also direct this diligence by simultaneously and systematically exposing yourself to the reality of what’s valuable in the relevant field.

Paraphrasing, Cal is arguing for diligent career planning in addition to diligent practice.  Diligent practice provides the means.  To achieve maximum impact, the ends should be determined by a deliberate survey of the chosen field.

This seems like a reasonable inference.  The only problem is that it bears no resemblance whatsoever to what actually happened.  The directed diligence theory is entirely a product of Cal’s preference for reductive principles and bears no relation to K&T’s actual intentions.

Cal’s own wording hints at this inconsistency when he states (above), “This small observation led to a bigger idea“.  The implied order of events is important.  K&T did not set out to leave their mark on the field of psychology.  They were not strategically pursuing “the reality of what [was] valuable in the relevant field“.  They were scratching an itch…exploring a small intrinsically interesting idea that naturally “led to a bigger idea“.  Kahneman’s Nobel Prize autobiography is quite explicit on this point:

I realized only recently how fortunate we were not to have aimed deliberately at the large target we happened to hit. If we had intended the article as a challenge to the rational model, we would have written it differently, and the challenge would have been less effective. [emphasis mine]

The only reasoning Cal offers to justify his conclusion reads as follows:

Kahneman and Tversky’s diligence, for example, was directed by their understanding, as psychology professors, that the model they were pursuing was a radical departure from an orthodoxy that had started to show strain. The field was looking for new models and they knew they were on to one possibility.

Unfortunately, this explanation is a non-sequitor.   Sure, by 1974 K&T were familiar enough with the field of psychology to understand their intellectual surroundings.  But that wasn’t what motivated their research.  They had no intentions of rocking the boat for the sake of individual acclaim.

Kahneman’s personal history suggests that he had been unwittingly pulling on this thread throughout much of his early life.  His autobiography teems with anecdotes and reflections portraying a meandering a career path.  At one point he reflects on a research experience during a summer away from graduate school:

Fifteen years after that summer, I published a book entitled “Attention and Effort,” which contained a theory of attention as a limited resource.  I realized only while writing the acknowledgments for the book that I had revisited the terrain to which Rapaport had first led me. [emphasis mine]

In recounting his early teaching experience, nearly a decade before meeting Amos Tversky, Kahneman observes:

To teach effectively I did a lot of serious thinking about valid intuitions on which I could draw and erroneous intuitions that I should teach students to overcome.  I had no idea, of course, but I was laying the foundation for a program of research on judgment under uncertainty. [emphasis mine]

There is no indication in autobiographical evidence that Kahneman’s research interests were ever influenced by external standards of value.  On the contrary, he consistently followed his intuitions in whatever directions proved intrinsically rewarding.

Cognitive Biases

It is ironic then that Cal chose to frame his argument within a narrative about research into cognitive biases.  When read with a critical eye his post takes on a bizarre self-referential quality.  The evident cognitive dissonance is striking.  Case in point: Cal subtitles the first section of his post “The Five Year Eureka Moment”, despite his own admission that the eureka moment occurred up front – an intuitive insight drawn from a “small observation“.  He may have intended this as a play on words, but even so it misrepresents the reality.

Similarly, he downplays obvious contradictory evidence:

Here’s what caught my attention about this story. This paper — Kahneman and Tversky’s first publication on their theory — came out in 1974, a half decade after they first began pursuing the underlying ideas. In other words, it took them a full five years to refine a rough hunch, through systematic exploration and discussion, into an idea too good to be ignored. [emphasis original]

Here Cal refers to “a rough hunch”, again undermining his presumption of a deliberately directed course of research.  But there is a larger point worth noting:  though Kahneman and Tversky’s most famous paper was published in 1974, prior to that they had jointly published at least four other papers on the same themes.  The 1974 publication wasn’t the first publication of their theory, just the one that happened to attract notice.

This is a subtle but important distinction.  The former framing reinforces the (intended) impression of a carefully scripted assault on the status quo.  The reality is far more ambiguous.

How does a thoughtful individual like Cal Newport manage such a skewed account of events?  In part, this is an example of confirmation bias, the tendency to selectively gather information and/or to selectively interpret information so as to confirm existing beliefs.  But I think there is more to it than that…

Divergent Modes of Cognition

This is where I will expose my own biases.  I will also do my best to contextualize the criticisms presented above.

The perspective I will offer suggests that Cal’s biases are not personal failings.  Rather, I suspect that Cal is largely incapable of seeing the world otherwise, and that we are all inclined towards similar biases (myself included of course ).

By way of analogy, Cal isn’t biased in the sense that a sports fan is biased about his favorite team.  Rather, he is biased in the way that a mother is biased about her newborn child.  In a mother’s perceived reality, her newborn truly is the most uniquely precious child in the world.  She is neurologically precluded from believing otherwise.  Similarly, I suspect that Cal is in a certain sense neurologically incapable of appreciating the role of intuition in the Kahneman & Tversky story.

The divergence between my interpretation and his, is less a matter of the factual record and is more a matter of perspective.  And the differences between our perspectives correlate quite nicely with the divergent modes of cognition in the two hemispheres of the brain.

While there has been plenty of shallow psuedoscientific nonsense written about this topic, the empirical research is quite deep and well validated.  In The Developing Mind, psychiatrist Daniel Siegel summarizes the role of the left hemisphere as follow:

The following findings…have been consistently obtained investigations ranging from studies of “split brain” patients to studies involving brain function imaging.  When information is presented to only the left hemisphere, verbal output reflects an effort to create a story or make sense of what it sees or hears.  Michael Gazzaniga and colleagues have called this the “interpreter” function of the left hemisphere.  For the isolated left hemisphere, these words are confabulations – made-up stories that fit with the data, but are unrelated to the gist or context of the situation…The left hemisphere uses syllogistic reasoning, stating major and minor premises and deducing logical conclusion from a limited set of data in an attempt to clarify cause-effect relationships.
…
The left hemisphere tries to create explanations for the information it receives, but it lacks the ability to process the context of this information, and so its conclusions are based on selected details without relational meaning.  The left hemisphere’s interpreter deduces an explanation that is superficially logical but is often without contextual substance if this hemisphere is acting in isolation from information from the right hemisphere. [emphasis mine]

And the right:

In contrast to the left, the right hemisphere appears to be able to make sense of the essential meaning of the input it is able to perceive: Contextual information is perceived and processed, and the gist of a situation is sized up and understood.  The right hemisphere does not use syllogistic logic to deduce conclusions about cause-effect relationships, but rather represents information about the environment.  Such information includes the relationships of various components of experience, including elements of mental processes and spatial relationships.  Since the right hemisphere is nonverbal, the output of its processing must be expressed in non-word-based ways, such as drawing a picture or pointing to a pictorial set of options to make its output known to the external world.  [emphasis mine]

The left-hemisphere – being the primary seat of language – processes discrete, abstracted, categorical representations in the linear and literal manner that facilitates the sharing of meaning between individuals.

The right hemisphere processes information holistically and non-linearly, preserving contextual relationships, but as a result it cannot externalize or communicate its internal representations nearly as effectively.

In brief, the right hemisphere produces a comprehensive and nuanced mental model of the world, that is intrinsically bound to the subjective context.  The left hemisphere produces the precise (but reductive) representations that enable us to interact with, and manipulate the “objective” world.  (It should be obvious that these statements are themselves highly reductive and should not be taken as comprehensive or absolute.)

[For the visual learners, a talk by Iain McGilchrist, adapted into an RSA animate presentation, can be found here.]

Unbalanced Minds?

For many tasks we would ideally want to engage the active cooperation of both hemispheres.  For example, as I write this piece I am compressing imprecise impressions from my subjective mental model into discrete bits of language.  Those bits of language can then be externalized and conveyed to you via context-independent media.

Unfortunately, we are not particularly good at this balancing act…

I am proposing instead that we are each innately partial to one pole or the other.  To be clear, this is educated speculation on my part.  Though I have not yet found research specifically addressing this point, there is plenty of evidence that lateral activation patterns can be uneven.  For example, left-handers are significantly more likely to exhibit language function in the right hemisphere.  From a distinctly different angle: the two hemispheres develop asymmetrically such that environmental factors may affect each uniquely.  Dan Siegel writes:

The right hemisphere is dominant in its activity and development during the first three years of life.  Children who experience severe emotional deprivation during this period may be at most risk of having losses in the structural components of their right hemispheres…These issues also raise the point that the time of experience, be it optimal or traumatic, may have the largest impact on those parts of the brain that are in the most active phase of development. [emphasis mine]

I don’t expect to convince you of this point in the space available here.  I only want introduce the pattern and point out how neatly it maps onto the (mis)interpretations outlined above, as well as my zealous reaction to the same.  In short, Cal Newport demonstrates all the signs of left-hemispheric dominance while I am heavily inclined towards the right.

Cal persistently seeks out universal principles that can be applied independent of context.  He attempts to distill literal cause-effect relationships from complex contextual information.  He is attracted to external/social motivators, as evidenced by his primary theme: “being so good they can’t ignore you“.

In contrast, several of my past posts demonstrate an almost pathological aversion to extrinsic motivators.  I am also highly allergic to formulaic thinking, tending instead to construct elaborate mental models even when I would be better served by simply following instructions.  In an IQ test I will easily ace all the spatial/pattern-recognition questions and struggle with the word associations.

The point here is not that one approach is better than the other.  If these patterns are neurologically fixed to any significant degree, it is more interesting to consider what they suggest about how we (can/should) make individual decisions:

• how we define our life scripts – retrospectively and/or prospectively
• how we perceive success and failure
• how we evaluate advice from others
• how we choose role models and mentors
• what motivates/demotivates us
• where progress is likely to come quickly/slowly

Cal writes:

Returning to my own example, it was only a few years ago that I began to internalize this lesson. Just because an idea was interesting to me, I now accepted, was not enough by itself to justify diligent pursuit.

That sounds like terrible advice to me…but perhaps it is just right for him.

photo courtesy of Rantz

Are these merely provocative analogies or is there a common process underlying each set of events?

Fundamentally these are statements about the nature human productive activity, our methods of organizing that activity, and the tools that facilitate that organizational structure.  Our evaluation of such claims must then be grounded in an understanding of the evolution of organizational structures.

Niche Construction

Lorenz thought that the world is knowable, but it is knowable through the categories of the knower, which were shaped by evolution.

So evolutionary adaptation by natural selection results in a partial correspondence, a kind of isomorphism between the structure of the world and the organization of the knower. On that account, organisms do not make theories of the world, they are theories of the world. [emphasis mine]

-Sam Bowles paraphrasing Conrad Lorenz

The ecological environment is not nearly as natural as we might think.  In reality it is a composite of active efforts by myriad organisms to construct niches that enhance their own prospects for survival and reproduction.

Niche construction is not a phenomena isolated to ecology.  The organism itself is a constructed niche.  It is the niche constructed by and for the genetic material.  Biological organisms are quite literally the ecological environment evolved around their DNA.

In the case of the human organism, niche construction takes the form of the society we see all around us, and that society exhibits the same isomorphism described in the quote above.  Human civilization is an emergent and embodied theory relating the human organism to its external world.  To whatever extent human society expresses a compelling theory of the world, it thrives.

Niche construction promotes survival by buffering the organism from the environment.  Just as the DNA uses the biological body to insulate itself from external selection pressures, so too human civilization serves to buffer the human organism from environmental selection pressures.

However, if/when each evolves towards greater complexity and capability, each creates new pressures – both internally and externally.  Externally, more capable evolutionary machines require a more fruitful environment to sustain themselves.  Internally, more complex evolutionary machines require more advanced means of mediating their own complexity.

…

Given this perspective, we can interpret claims like those at the start of this piece as references to a constructed niche evolving towards greater complexity.  DNA evolved T-cells, red blood cells, and neurotransmitters.  Humans have evolved language, money and information technology.

The remainder of this piece will address common themes apparent throughout the recent evolutionary history of those mechanisms, including:

• how they influence the form of self-organizing social structures
• how those structured societies evolve towards internal and external limits
• the dynamic balance between change and stability, innovation and conservatism, adaptability and survivability
• how that dynamic equilibrium responds to mismatch between organizational capacity and constraints

Understanding the dynamics common to various coordinating mechanisms should allow us to better understand the shifts currently underway in appropriate context, and thereby to better predict the course that current transition might take.

Clarifications and Disclaimers:

Before I dive off the deep end, a bit of housekeeping:

Throughout this piece I use the term “society” frequently.  My usage does not assume any particular definition.  For our purposes, society simply refers to: an interconnected and dynamically interdependent population.

Secondly, what follows is an exercise in pattern recognition.  The goal is to develop a framework with which to organize further exploration.  This piece is not intended as the definitive explanation for all human history.  That much should be obvious.  I do want to encourage your comments and criticisms.  However, I hope you will be mindful of the intended purpose and moderate your feedback accordingly.

Onward…

Four Coordination Paradigms

In a series of previous posts I developed (with your feedback) a framework outlining four modes of economic exchange (read: value creating exchange):

• Relationship Economy -    illegible exchange between related parties
• Political Economy -             legible exchange between related parties
• Transactional Economy - legible exchange between unrelated parties
• Attention Economy -          illegible exchange between unrelated parties

There exists a distinct historical trend in relation to these four modes of coordination that will allow us to repurpose the model towards our current ends…

Relationship Economy

Prehistoric man would have perceived only the relationship economy.  Prior to the advent of agriculture and the formation of stationary civilizations, all “economic” behavior was organized relationally.

Relationship economies were characterized by relative equality and a general lack of structure.

The modes of coordination available to prehistoric man were entirely informal.  All individuals within small tribal groups enjoyed reciprocal relationships with one another.  Productive activity was organized cooperatively and the fruits of that productive activity were allocated according to social norms and customs.

Political Economy

When nomadic tribes began to form stationary civilizations, around the time of the agricultural revolution, new organizational principles emerged.

The political economy is what we are familiar with by reference to the ‘great civilizations’ described in history books.  Through most of recorded history human society was organized predominantly via political coordination.  These societies were characterized by real power projected through hierarchical institutions.  Individuals gained power through explicit status in formal bureaucracies.

Though much production remained within relational units (extended families, small communities), the relational unit was now embedded in a new reality that had grown up around it.  In larger civilizations – enabled by agriculture – individuals could no longer rely exclusively on shared norms to mediate social behavior.  Activity that extended outside the immediate community was mediated by codes of conduct defined by formal institutions.  Productive activity and the allocation of resources were also mediated by a hierarchical social structure.

Transactional Economy

Political economies proceeded to dominate the world scene for thousands of years.  It is only within the past couple hundred years that the transactional paradigm has emerged as the predominant mode of economic coordination.

Transactional economies are characterized by a decentralized self-organizing structure.  Power and influence are a function of access to resources, primarily financial capital.

The bulk of economic activity is coordinated through impersonal markets.  The production and distribution of resources is decentralized and mediated by self-adjusting pricing mechanisms.

Correlations

Admittedly, all of the above is described in very broad strokes.  For those interested in detailed historical examples of each paradigm I recommend David Graeber’s Debt – The First 5000 Years, which I recently reviewed.  My distinctions between relational, political and transactional economies roughly parallel Graeber’s distinctions between communism, hierarchy, and exchange respectively.

Unfortunately, Graeber never builds much conceptual architecture around that basic outline, leaving it to readers to extract their own patterns from the voluminous historical evidence he presents.  With the remainder of this post I will begin outlining the first couple layers of conceptual scaffolding, as I see it.  As you have surely surmised, I will eventually incorporate a fourth category (attention economy), for which Graeber does not offer a parallel. The failure to recognize that fourth paradigm is likely the foremost reason why Graeber seems to favor such an anachronistic position.

After establishing the overall pattern in this post, I will turn in future posts to the competitive dynamic that plays out in the rivalry between paradigms, which will prove particularly interesting as applied to the current shift towards attention economics.

The Evolutionary Pattern

Below is an illustration of the pattern described so far (the arrows labeled rationalization and specialization will be addressed later on):

Human civilization first takes form in relational tribes and remains in that state for quite some time.  The transition to political economy begins around the same time as the agricultural revolution and the advent of stationary populations.  Both of those characteristics – geographic fixedness and development of agriculture – engendered population grow that which was possible with a nomadic lifestyle:

 The shift to agricultural food production supported a denser population, which in turn supported larger sedentary communities, the accumulation of goods and tools, and specialization in diverse forms of new labor. The development of larger societies led to the development of different means of decision making and to governmental organization. Food surpluses made possible the development of a social elite who were not otherwise engaged in agriculture, industry or commerce, but dominated their communities by other means and monopolized decision-making. [wikipedia]

Though human civilizations began dabbling with debt and money thousands of years prior to the industrial revolution, much of that early dabbling amounted to mere dead end experiments.  Transactional markets did not reach a self-sustaining and self-perpetuating inflection point until the last couple hundred years.  That transition corresponds roughly with the industrial revolution.

Admittedly, the criteria ‘self-perpetuating’ and ‘self-sustaining’ are subjective.  Nonetheless, it is fair to say that the industrial revolution marked a shift away from markets that existed primarily as vehicles for politically oriented rent-seeking, and towards markets driven primarily by market forces.  Surely politically motivated market interventions continues to exist even in present day, however governments’ ability to manipulate markets without provoking massive unintended consequences has steadily decreased.  In other words, governments have become minority players.

The Stimulus

What precipitates the phase changes demarcating individual paradigms?

The scale and complexity achievable within each paradigm is functionally constrained.  The coordination mechanisms available within a given paradigm are limited in both:

• their ability to mediate internal complexity
• their ability to foster technological solutions to environmental constraints

As growth and development proceed within a given paradigm, pressure on existing coordination mechanisms mounts and faults begin to form.  Without new tools one of two outcomes is inevitable:

1. Failures of internal coordination sabotage further growth
2. Unchecked expansion becomes cancerous and crashes into environmental limits

Collapse

Both cases describe a form of collapse.  Joseph Tainter has described the first type, arguing that societies collapse when they encounter problems they are unable to solve:

Tainter argues that sustainability or collapse of societies follow from the success or failure of problem-solving institutions and that societies collapse, when their investments in social complexity and their “energy subsidies” reach a point of diminishing marginal returns. He recognizes collapse when a society rapidly sheds a significant portion of its complexity. [wikipedia]

Collapse in this case takes the form of stagnation or implosion.  The social infrastructure, having exceeded certain limits, produces more costs than benefits and begins tearing itself apart.  In dramatic cases a period of chaos ensues and the population reverts to a simpler way of life until a new paradigm is developed.

Jared Diamond has addressed second situation – collapse as a result of environmental depletion.  Though I haven’t reviewed all of Diamond’s work, my impression is that the collapses he studies are even more destructive.  When environmental constraints are exceeded, complete collapse – resulting in the death of entire populations – tends to follow.

This second sort of collapse may derive indirectly from failings of the first sort.  For example, resource depletion may be avoided if appropriate rationing mechanisms exist.  Similarly, effective signalling mechanisms may be used to raise the alarm and mobilize a search for solutions.  It is when the capabilities don’t exist that populations charge recklessly into environmental collapse.

Revolution

The Social Technology Stack

At this point it is worth addressing a subtle misconception.  It would be easy to read “revolution” as an overthrow of what came before.  That is in fact how we use the term in the geopolitical context.  For example, The French Revolution and The American Revolution were violent conflicts involving the overthrow of old regimes and the birth of entirely new regimes.

Social revolutions present a different character.  Note that in the previous section revolution is offered as counterpoint to collapse.

The emergence of political economy did not (necessarily) imply a violent a dissolution of relational communities.  To the contrary, hierarchical structures must have initially taken form within relational communities.  Likewise, the emergence of transactional markets did not coincide with a violent overthrow of political institutions.  Rather, markets were created by extant political bureaucracies as a means of furthering their influence.

The antagonism that eventually develops between adjacent paradigms is characterized more accurately by the modern definition of disruption, rather than the conventional meaning of revolution.

Transitions

As such, transitions from one paradigm do not represent wholesale change, but instead an accelerating shift at the margin.  Earlier modes of organization may gradually lose influence while remain pervasive in a dwindling capacity. The historical events we assign to demarcate transitions are really just tipping points.  To borrow John Hagel’s terminology – such events are merely harbingers that the core is being pulled towards the edge.

If we were to visualize the evolutionary arc in three dimensions it might look something like a migrating sand dune – the tail gradually shrinking in prominence,  meanwhile the leading edge grows as it is swept forward into virgin territory.

Dialectic rivalry emerges only once the child paradigm grows large enough to threaten the parent.  Moreover, the dialectics themselves are ultimately hollow.  Whatever rivalry may develop, the child cannot snuff out the parent without smashing its own foundation…

Foundations

Each successive paradigm is built upon a foundation constructed in previous periods.  The ideological pillars of political institutions are built upon social norms originally established within the relational context.  Transactional markets sprout only on ground that has been prepared by political hierarchies.

Without the necessary foundations later paradigms are not achievable.  As Graeber points out, the spontaneous emergence of money from primordial barter is a myth.  Communal hunter gatherers would have been mystified by – and likely violently opposed to – the notion of a economic exchange outside the context of custom and ritual.

This is a reality rediscovered all too frequently by development economists, uber-philanthropists and ambitious technocrats.  Well meaning efforts to install market oriented institutions in developing countries have consistently met with disappointing results.  Effective markets require not only well developed institutions, but also a culture of compatible norms and ethics.  Without these foundations markets serve only to produce more efficient corruption [see this recent Econtalk podcast for more].

The Socioeconomic Paradigm Shifts

Let’s dig more deeply into the specific characteristics of the two transitions discussed so far.  In the illustration above I labeled them rationalization and specialization.  We will find that each is a reaction to the particular pressures – the abundance and scarcities – created within the earlier paradigm.

Rationalization

Definition: to make rational or conformable to reason.

Rationalization, in this context, is the process of introducing explicit structure to a previously informal society.  What relational tribes lacked, quite simply, was stability.  The lack of formality has a certain utopian appeal but it also undermined progress.  Nomadic tribes could only produce as much technology as they could carry.  Moreover, reliance on implicit norms restricted relational groups to a scale at which ubiquitous relationships could be maintained (Dunbar’s number +/-).

Rationalization required formalizing implicit social norms, thereby producing explicit standards.  This code of conduct, as such, would allow individuals to expect consistent behavior from others, independent of context.  It is that standard of context independence that would have allowed populations to grow beyond previous limits.

Over the course of thousands of years, greater scale and complexity would have demanded increasing explicit structure, which in turn enabled still greater scale.  And it was the stable, structured, and populous civilization that formed the foundation for the next shift.

Specialization

Specialization is the process of subdividing the labor pool and allowing different groups to focus on developing expertise in specific roles.

Specialization can only emerge from within a rational social structure.  Prior to the advent of stable political economies specialization would have been dangerous.  If you specialize – relinquishing your self-sufficiency – and the social structure proves unreliable, you could starve.  The greater your dependence on unrelated parties for your survival, the more assurance you will require that the existing status quo will not be suddenly disrupted.

If you can rely on people outside your immediate family to act predictably, your universe of feasible productive activities expands dramatically.  However, specialization also introduces a wedge into the hierarchical society.  As individuals specialize they become more expert in their chosen fields than people above them in the hierarchy.  The more specialization, the more intractable this problem becomes.  Economies that are both highly specialized and highly diverse (deep and wide) eventually become unmanageable. Hierarchy becomes at best impotent, and at worst destructive.

It is at this point that decentralized markets become a necessity.

…

Upcoming: competitive dynamics, attention economy, other stuff…

photo courtesy of Jon-Luke

At each pause there is some probability I will break the cycle, but these probabilities do not accrue linearly.  A 20% chance of breaking the cycle does not imply that by the fifth cycle I am sure to stop.  It feels more like a coin flip – each time the probability is the same and sometimes you come up heads ten times in a row.

Last night I nearly fell into the zombie trap.  I was ready to go to sleep, all my electronics already shut down, when some vague hint of a thought about twitter popped into my head.  Because my defenses were primed I was able to resist the impulse, and I decided instead to rewind my memory and analyse the preceding thought process.  This is what I found…

The momentary association with twitter wouldn’t qualify as a legitimate thought.  There wasn’t any real content to it.  Nevertheless, it was immediately followed by a mental image of me picking up my phone and opening the twitter app.  Again, this image didn’t contain any conscious intention.  It was merely an automatic visualization of the next pre-programmed step.

I then decided to project my memories forward to see how this sequence might have played out.  I envisioned myself staring at twitter wondering why/how I had ended up there, then setting the question aside and succumbing to some further automatic behavior like checking for new direct messages or mentions.

Why not just stop after the first befuddled pause?

While reviewing my thought process I realized the psychology is analogous to the loss aversion that compels us to follow stock market investments down rather than cut our losses.

The large majority of all human behavior is controlled unconsciously.  The capacity of conscious awareness is quite limited.  Because conscious awareness cannot keep tabs on everything the unconscious mind is doing, we remain relatively uninhibited when engaging small, trivial, habitual behaviors.  We mindlessly proceed from one pre-programmed action to the next.  If you find yourself in the bathroom with the shower running you won’t often pause to reconsider how you got there.  Rather, you will habitually undress and jump in.

The same cognitive dynamics apply to more significant actions as well.  This is why context change is so helpful when trying to reinforce a set intention.  If you try to exercise at home in front of the television your willpower is likely to dissipate within a few minutes.  By simply driving yourself to the gym you significantly enhance your chances of success.  The change in context offers external cues that constantly reinforce the initial intention.  Moreover, the act of transporting yourself to another location presents a sunk cost that you are compelled to justify.  With each additional layer of intentional behavior the cognitive burden associated with a course reversal becomes more prohibitive.

Investments and Loss Aversion

If we reverse the intentional process described above, the result is loss aversion.  Intentional decisions have a certain characteristic smell to them.  Walking into the bathroom and turning on the shower feels intentional even when we do it automatically.  When you were a child you probably hated showers.  At some point along the way you intentionally trained yourself to shower habitually, and eventually you began to enjoy it.  That aura of intentionality still lingers.

Investment decisions have that same characteristic smell, only much stronger.  As a result, we implicitly accept that past investment decisions must have been made for a good reason even when the conscious mind can’t immediately conjure up what that reason might have been.  If investment decisions are actually not intentional…when we invest impulsively…then we irrationally resist selling losers because there exists no evidence that could logically contradict the original decision.

In short, if you buy impulsively then you condemn yourself to sell irrationally as well.  And if you are already locked into an irrational decision, how likely is it that you will impulsively decide to eat a loss?

Note the parallels to the zombie clicking trap.  When I suddenly find myself staring blankly at twitter, my first question is – Why am I here?  If I can’t answer that question then I am locked into an irrational state of mind.  But of course, internally it doesn’t feel like an irrational state of mind…it just feels like I haven’t yet found what I came for.  If I just look around for moment I’m sure I will remember what I was doing.

As such, it isn’t stubbornness that compels me to justify the sunk cost.  Rather, it is cognitive incoherence – the brain’s effort to reconcile its default premise with an incompatible observation.

• Premise: My behaviors are motivated by sensible intentions.
• Observation: I am staring at twitter for no discernible reason.

It is far less cognitively burdensome to follow the script – to continue mindlessly clicking away, expecting at any moment to stumble upon the clue needed to contradict the observation – than it is to open the can of worms that follows from doubting the premise.

The Fix?

Senseless habitualized behaviors are more difficult to overcome than it might seem at first.

Stock market professionals advise that you should always develop an explicit investment thesis prior to acting on any investment decision.  You need to understand your explicit reasons for buying so that you can rationally evaluate arguments for selling.

Unfortunately, exercising greater conscious awareness is only a limited solution.   Opening that can of worms indiscriminately will lead only to a perpetual state of paralyzing doubt.  Over-reliance on conscious evaluation is the definition of analysis paralysis.

The key then is to distinguish generative patterns from destructive ones, and to sequester individual behavioral patterns based on increasingly subtle contextual cues.  Context used to be obvious.  You would adopt one set of behaviors at the office, then swap in a different behavioral pattern at home.  Balancing the two was a relatively trivial matter of balancing time between the two physical locations.

Now those boundaries are blurred and our computers and phones do everything.  Yet context, however ambiguous, is no less important.  Are you exploring or exploiting?  Consuming or producing?  Learning or performing? Are you acting socially or individualistically?  Collaboratively or cooperatively?

Each distinction suggests certain shifts in the allocation of focused awareness.  Accepting the wrong premises for a given context can result in confounding cognitive contradictions.  And we have a long way yet to go.  Expect zombie traps to be become far more prevalent before any semblance of predictable order returns to the world.

photo courtesy of Zebra Pares 

The Good

As a historical survey Debt provides valuable perspective to the contemporary ideologically driven economic debate.  Graeber convincingly demonstrates that that markets have not historical been opposed to government planning so much as they are a product of it.  Modern markets and financial mechanisms emerged most readily when and where governments encouraged them, usually as a means to coerce citizens into funding and supplying military campaigns.  Monarchs, despots and warlords throughout history have instituted taxes, payable only in official currency of the realm, in order to force captive populations to produce goods salable for currency of the realm – typically weapons and other war supplies.

Along the way Graeber thoroughly debunks the barter myth common to every introductory economics textbook ever written.  As the story goes, at some indeterminate point in the past, proto-economic man grew frustrated with the inefficiencies of barter and decided a common currency was needed to facilitate more fluid trading relations.  Hence money was born…and gdp grew grew happily at 4% per annum ever after.  Graeber’s research reveals the absurdity of this fairy tale, documenting the long evolution of debt relations that preceded the use of transactional currency.

For the skeptic this point may be a bit of a straw-man.  In my experience, through both formal education and informal learning, the barter myth has been presented more as a thought experiment than a historical fact.  For what it’s worth, Graeber claims that Adam Smith was the originator of the myth and that Smith fully expected contemporary explorers to stumble upon proto-economic tribes living out his ideal-barter fantasies.

Suffice it to say, if the barter myth is foundational to any of your economic principles you might want to do some soul searching.

The Questionable

The trouble with Graeber’s historicist approach is that it restricts him to relatively limited modes of argumentation.  Graeber clearly intends to cast doubt upon the foundations of modern capitalism, however, casting doubt on certain bits of conventional wisdom is about all that the historical record is able to accomplish.

Demonstrating that the earth was not created 6,000 years ago does not disprove the existence of a biblical God.  Likewise, the mythical origins of primordial barter are only tangentially relevant to modern applications of monetary theory.

Much of the book takes the form of describing the morally distasteful origins of specific institutions and thereby insinuating that the reader ought to doubt the credibility of those institutions.  Because this approach is necessarily inconclusive, Graeber is forced to lead the reader in the intended direction via the tone of his language:

The story of the origins of capitalism, then, is not the story of the gradual destruction of traditional communities by the impersonal power of the market.  It is, rather, the story of how an economy of credit was converted into an economy of interest; of the gradual transformation of moral networks by the intrusion of the impersonal – and often vindictive – power of the state.

Unfortunately, Graeber never steps outside his own perspective long enough to integrate the many indictments, like the one presented above, into a coherent narrative.

If the origins of capitalism are so repugnant why has it proliferated so successfully?

Debt offers myriad case histories but fails to extract a compelling thesis from them.  The vigorous success of capitalism cannot be so easily dismissed as simple dogmatic adherence to historical myth.  The best Graeber can manage is to document in great detail how the “impersonal power of the market” has been advanced through violence.

But, why so successfully?

Throughout history, unsavory characters have attempted to violently disseminate countless vile ideologies.  If impersonal markets are such a bad deal, why have so many people so readily been suckered into playing along?  When dispassionate analysis runs out of steam, Graeber reverts to begging the question:

It is the secret scandal of capitalism that at no point has it been organized primarily around free labor.  The conquest of the Americas began with mass enslavement, then gradually settled into various forms of debt peonage, African slavery, and “indentured service”…Needless to say, indentured servants were recruited largely from among people who were already debtors…

The serialized accounting of forced labor relations continues for the better part of another page.  To be fair, Graeber does defend his historical claims rigorously.  It is the framing of his arguments that is lacking.

Does the passage above truly describe a scandal of capitalism?

It should come as no surprise that the real world is more complex than the tidy thought experiments offered in textbooks.  The same is true of all human institutions.  Graeber elaborates further:

This is a scandal not just because the system occasionally goes haywire…but because it plays havoc with our most cherished assumptions about what capitalism really is – particularly, that, in its basic nature, capitalism has something to do with freedom.

This would be a sound point if not for the glaring absence of contextual subtlety.  Obviously capitalism is not a system of pure unrestrained freedom.  It would be naive to contend that a wage laborer is more free than a hunter-gatherer tribesman.  But that would be the wrong comparison.  We associate capitalism with freedom due its 20th century dialectical rivalry with communism – a system that was decidedly less free.  In that context capitalism surely does have something to do with freedom.

Characteristically, Graeber overextends himself, further indulging in a tenuous analogy between wage labor and slavery:

There is, and has always been, a curious affinity between wage labor and slavery.  This is not just because it was slaves on Caribbean sugar plantations who supplied the quick-energy products that powered much early wage laborers’ work; not just because most of the scientific management techniques applied in factories in the industrial revolution can be traced back to those sugar plantations; but also because both the relation between master and slave, and between employer and employee, are in principle impersonal: whether you’ve been sold or you’re [sic] simply rented yourself out, the moment money changes hands, who you are is supposed to be unimportant; all that’s important is that you are capable of understanding orders and doing what you’re told.  (emphasis mine)

To the extent that Debt succeeds in conveying a consistent thesis, the highlighted section above captures it.  In short:

Transactional = Impersonal = Violence = Slavery

As with the quotes cited earlier, it is unclear how this conclusion applies particularly to the institutions of capitalism.  As populations grow, nearly all social institutions become more impersonal.  Governance mechanism become more impersonal.  Communities become more impersonal.  Even families become more impersonal.  All of the above are effects of scale, not effects of transactional market per se.  I will acknowledge that capitalism has facilitated growth and scale.  However, the arrow of causation points in many directions.

The Frustrating

Ultimately Debt fails to do justice to the complexity of the real world.  Its conclusion perfectly exemplifies Graeber’s ability to confound the critical reader.

It seems to me that we are long overdue for some kind of Biblical-style Jubilee: one that would affect both international debt and consumer debt.  It would be salutory not just because it would relieve so much genuine human suffering, but also because it would be our way of reminding ourselves that money is not ineffable, that paying one’s debts is not the essence of morality, that all these things are human arrangements and that if democracy is to mean anything, it is the ability to all agree to arrange things in a different way.

Even the skeptic will be convinced “that money is not ineffable, that paying one’s debts is not the essence of morality, that all these things are human arrangements“.  Graeber’s scholarship is thorough, comprehensive, and persuasive.

Does that imply we can (should) whimsically “agree to arrange things in a different way“, whenever and however we choose?  It does not…at least not in the form of top-down policy.  As complex systems evolve they accrue increasingly entangled layers of dynamic interdependence.  The record for wholesale engineering of such systems is not encouraging.

All told, Debt is a worthwhile read for anyone motivated to independently integrate the mountain of compelling scholarship Graeber offers.  Despite the predominantly negative tone of this review, I will probably find myself referencing Debt from time to time in future posts.  Unfortunately, as a self-contained commentary pertinent to current institutions it leaves a lot to be desired.

Acknowledgement: Thank you to William Tozer for generously providing a free copy in order to stimulate debate on this subject.

The two updates both derive from discussions related to gift economies.  When I first introduced the four quadrant model I expected that gift economy would stir up the most debate and as a result I avoided addressing the subject until some time later.  As expected, numerous people weighed in, offering disparate perspectives on what gift economies are and are not.  The obvious conclusion became unavoidable – gifts can take many forms and are proffered in many disparate contexts.  The act of gifting, of giving generously, is clearly not isolated to any categorical form of exchange.  My attempt to shoehorn gift exchange into one specific quadrant produced an unnecessarily fragile model.

Gift Economies…Loosely Redefined

As it became painfully clear that no single definition of “gift economy” would satisfy everyone, I began to wonder if there was any salvageable meaning to the term whatsoever.  Obviously my preferred interpretation was sinking, but were any of the various other (often contradictory) interpretations any more valid?

The common theme resonating through much of the feedback I received was asymmetry.  People argued, in many different forms, that ‘gift’ should refer to those exchanges that lack a formal expectation of reciprocity.  There might exist social norms dictating some degree of loose reciprocity in the long run, but in the short run most people expected gifts to convey generosity.  The greater the potential for asymmetry in a given exchange, the more we perceive it as gift-like.

This dynamic can potentially exist in any of the four quadrants.  For context, here is the model as originally proposed:

Gifts are obviously exchanged within relationships on the basis of generosity alone.  A slightly different form of gifting is also present in the attention economy, as digital content is commonly offered freely without any necessary expectation of reciprocation.  In the transactional economy gifts can be  proffered in the form of philanthropy.

That leaves us with the now nameless upper-right quadrant.  Before we can address that we need to take a quick detour…

Refinement and Legibility

In the original model the y-axis represented the variable refinement, which I defined as follows:

1. the degree to which a given value proposition can be accurately judged prior to exchange
2. the ease with which that value is extracted by the recipient

In thinking about this further I realized that my definition muddled two related concepts together: refinement and legibility. Legibility is a concept I first encountered through Venkat Rao via his post – A Big Little Idea Called Legibility:

…the word “legibility” is not a metaphor; the actual visual/textual sense of the word (as in “readability”) is what is meant.

You will get a much better feel for the idea by reading Venkat’s full post. He himself admits that “it is surprisingly hard to find words to express it succinctly“.

For our purposes here, I will simply suggest that legibility is the compliment to refinement. Of my original definitions (above), the first more appropriately describes legibility. Refinement is more accurately defined as the effort on the part of a producer to make the value of a given product more more accessible to the consumer.

As such, legibility and refinement are two sides of the same coin.  Refinement produces a more legible value proposition. Branding, standardizing, and anchoring are all refining tactics. Alternatively, as suggested in the second definition above, refinement could simply make the product itself more accessible such that its consumption value is more obvious (i.e. legible). That is how we use the term in reference to “refined sugar” or “refined oil”.

The Illegibility of Relational Gifts

Why did the previous discussion of gift economies require a tangent into refinement and legibility?  Consider a commonly referenced hypothetical scenario:

Two friends get together regularly at local restaurants.  On these occasions it is customary for one person to pick up the entire bill.  Custom also dictates that they alternate picking up the tab, though this may vary depending on the occasion (birthdays, etc).  Neither person keeps a strict tally of how many times they have each paid or who has paid more in aggregate.

Intuitively we will want to say that the above scenario describes a series of exchanges that should map to the relationship economy.  Yet, restaurant meals are clearly not unrefined according to definitions offered above.  Quite the opposite.  Restaurant meals are highly standardized and clearly priced.  The original model created confusion by suggesting that this sort of social exchange should map to the upper-right quadrant.  Fortunately, that confusion resolves if we take legibility into account on vertical axis.

Though the goods in question (restaurant meals) are thoroughly refined (facilitating transactional exchange between customer and restaurant), both friends endeavor to obscure the terms of the quid pro quo between themselves.  Social norms dictate the they do everything possible to make the refined value exchanged less legible.  If the recipient of the “gift” on any particular night were to ask about the amount of the bill, the giver would generally deflect the question: “Don’t worry about it…you paid last time.”

The taboo against discussing the formal quid pro quo persists so long as the balance falls within an implicitly accepted margin of error.  When that implicit margin is not mutually understood, painfully awkward situations ensue…

Next time you are out at a popular restaurant keep an eye open for large groups of 20-somethings and watch to see what happens when they get the bill.  Often you will notice one member of the group intent on precisely allocating the bill down to the last penny while others at the table exchange uncomfortable glances with each other.

Adopting the concept of legibility allows us to account for these sorts of ambiguous situations.  Whenever the parties to an exchange actively obscure the explicit terms of trade, the intent is to push towards relational or attentional dynamics.  When the explicit terms of trade are emphasized the intent is to invoke a formal transaction or a legible debt.  ”Gifting” with the intent to invoke a legible debt is how I originally characterized gift economies, by analogy to tribal gift economies.  How then to rename the now nameless quadrant?

The Political Economy

I have taken recently to referencing the upper-right quadrant as the political economy.  The political arena incorporates all the social/economic dynamics applicable to refined/legible exchange between related parties…

• Trading favors – check
• Perpetual jockeying for status and influence – check
• Duplicitous behavior enabled by lack of transparency – check
• Shifting alliance based on Machiavellian pragmatism – check

The reason for this unsavory behavior is rather simple – both relatedness and refinement (legibility) facilitate keeping score.  When score keeping behavior festers over an extended period of time, people tend to lose sight of their original motives and blindly pursue the score itself.  They mistake the metric for meaning.

Of course, political dynamics are not entirely negative.  The above observations are drawn from entrenched political environments that have advanced into the later stages of ossification.  These same dynamics may present in a significantly healthier form in newly emergent political regimes.  But that will have to wait until next time…

Upcoming: the evolutionary lifecycle of socioeconomic dynamics

photo courtesy of barefootsong

In a sense the jungle elephants engage in an instinctual (naturally selected) form of agriculture.  But of course, this limited form of environmental engineering is not sufficient to meet the nutritional needs of an animals that can consume hundreds of kilograms of vegetation a day.  As noted above, the elephants cover hundreds of kilometers in search of a broad variety of food sources.  At every step along this journey they must choose between exploring and exploiting.  They can stay in a given area and pull every last plant from the ground or they can move on to a new location with no guarantee that they will find food.

This sounds like a simple decision but in fact these turn out to be very difficult mathematical problems if you attempt to formalize them, particularly when there are so many unknowns.  Fortunately for the elephants, their decision algorithms are genetically programmed.  Each individual within a given population will have certain innate tendencies.  Evolution has even had to account for higher order explore/exploit dilemmas.  Within a given population, how many individuals should stick strictly to the proven strategy and how many should diverge from the norm and be compelled to experiment with new strategies.

Everyday Optimization

We face these same dilemmas daily.  Most people are rarely aware of them, but once you grasp the concept you see explore/exploit decisions everywhere.

• Should you watch the same tired sitcom every Thursday night or should you experiment with something new?
• Should you introduce that newfangled collaborative tool into your work group or should you stick with what works?
• Should you search for the fastest commute home, risking even worse traffic, or should you take the usual route so you can zone out?
• Should you bring up that thing that’s been bothering you with a particular family member, or is it better to simply smile and nod to keep the peace?

Most people have a tendency towards one or the other.  They like things (or processes) that are well understood or they get anxious for that opportunity to discover something new.  However, the explore/exploit concept is not quite so trite as saying that some people like to try new things while others prefer that which is comfortably familiar.

Here in the San Francisco bay area the foodie culture is something of a metropolitan pastime.  Is the foodie an explorer?  Perhaps. Perhaps not.  The foodie is demonstrating some relatively simple first-order exploration by iterating a formulaic process repeatedly.  So as not to sound condescending, I will throw one of my hobbies, Crossfit, into the mix.  One of the tenets of crossfit is “constantly varied”.  Yet, about 95% of the time that amounts to variety of the same magnitude experience by the foodie.  Only about one in twenty workouts is a completely unexpected curveball that catches everyone off guard.

Higher order exploration patterns are surprisingly difficult to consistently adhere to and seriously limit your exploitation ability.  Crossfit is a case in point.  Nearly everyone follows a workout schedule programmed (explored) by a coach or trainer so that they can focus on the workout itself without equivocation.  In other words, they welcome a set of external constraints that allows them to focus on exploitation.  Attempting to do both, to any significant degree, mixes performance with meta-cognition too thoroughly.

Finding Balance

I noticed this same pattern while reviewing my blogging activity over the past year.  I have reasonably high expectations for what I post here.  I don’t expect my writing to be particularly poetic but I do expect my ideas to be well thought out and coherently presented.  In other words, I try to exploit my ideas at least somewhat comprehensively beforehand, rather than posting stream-of-consciousness speculations.  That has proved a significant hurdle, particularly for the newer material that is most motivating but least refined.

Around midyear I revived my old posterous blog, renamed it the idea incubator, and began using that space to present shorter and more spontaneous musings.  In looking back over those posts I am finding that quite a few of them are among my favorites from the past year.  Here is a sampling:

1. Big Thinking in Dense Packages
2. Moving Beyond the Dialectical Socioeconomic Debate
3. Peter Thiel Needs a Session With Clay Shirky
4. Project Oriented Start-ups and the Entrepreneurial Personality
5. On Working Backwards
6. Fear of Illegibility

I am reminded now of an excellent youtube video I came across on twitter just the other day featuring Ira Glass talking about the creative process:

I have always preferred exploring to exploiting, but I am also painfully aware that that preference has handicapped my exploitation muscles.  As Ira Glass conveys so concisely, even when the work is missing that special something the only option is to try again.  My takeaway from reviewing the exploratory posts linked above, is not to let weaknesses get in the way of strengths.  For me, the refinement process is often a struggle but the stuff that flows spontaneously isn’t that bad.

The broader takeaway is that we are all making explore/exploit choices either consciously or unconsciously.  It is impossible to identify with any certainty the optimal balance between two.  We can however, sensitize our intuition to alert us when we have drifted away towards a definitively non-optimal balance.

(Thanks to Neil LaChapelle for persistently reiterating the explore/exploit theme in our conversations.)

photo courtesy of Eliel Freitas Jr

Before I get to that I am going to indulge my current fascination with learning and productivity curves one more time.  I’ll make some effort to keep us on topic  at the end of the post by relating this theme back to the current economic malaise.

A few weeks ago I explored the dynamics driving the oscillations, between periods of acceleration and stagnation, throughout an individual’s long term learning/productivity curve.  Today, one additional principle coalesced in my mind that I want to hash out briefly.

I will tentatively call this principle the dual-mind limitation:

It is difficult, bordering on impossible, for an individual to focus on both meta-learning and performance at the same time.

That may sound a bit vague or cryptic but the principle itself is quite simple.  The basic hypothesis is that we are only capable of maintaining two levels of awareness in mind at a given time.  You can perform and learn at the same time.  You can focus on learning and meta-learning at the same time.  But you can’t do all three.

A personal example…
I have written previously about the lessens learned from my experience with crossfit.  That experience offers an appropriate example here as well.  Suppose I am training some specific physical movement such as a muscle-up.  I might be focused at any of three levels:

• performing the movement
• learning the movement (coaching myself)
• learning how to learn the movement (learning to coach myself)

Of those three, I can only do two at a time.  Supposing I am in the middle of a workout; the clock is running and I am trying to finish a specified number of repetitions as quickly as possible.  Obviously I am trying to perform the movement as well as possible.  At the same time I can observe my own performance and coach myself between repetitions – “keep you elbows in…push your head through…secure your grip before initiating the pull”.  Both levels of focus can be achieved seamlessly and will feel like one fluid experience.  But as soon as I start debating whether I am issuing myself the correct coaching cues, the performance is disrupted.

Likewise, if I am learning a new movement I can focus on learning and meta-learning at the same time, but that requires dismissing any attention focused on performance.  This would take the form of practicing the movement (learning) while also observing what goes wrong when I fail to perform it correctly (meta-learning).  I could then be devising new coaching cues between practice reps.  But as soon as I start trying to perform the movement quickly – rushing through it – meta-learning is lost.  I can’t diagnose previously unrecognized weaknesses or identify new practice techniques while also trying to move fast or lift heavy weight.

You have likely experienced the same phenomena in numerous other domains.  Productivity hackers commonly advise you not to write vague to-do items.  Your to-do list should be as specific as possible.  Why?  Because it is so difficult to multitask between three levels of awareness at once.  Vague to-do lists require you to:

• Decide which item to execute
• Decide how to execute that item
• Execute it

Doing all three at once requires a degree of cognitive multitasking that very few of us can manage with any degree of competence.  If you can eliminate the middle step by maintaining a well specified list the task is dramatically simplified.

As we approach New Year’s Resolution season most people will commit to resolutions like – lose weight, get in shape, read more books, learn a new skill.

Fail, fail, fail fail!

If you have ever tried dieting without first committing to a very specific plan then you know that these resolutions are destined for failure.  You can’t at once – refine your diet plan, observe your adherence to that plan, and attend to the willpower necessary to adhere to the plan.

~~~

I am calling this the dual-mind limitation because I suspect it is caused by the hemispheric division within the brain.  We are able to maintain two levels of awareness at any given time because the brain is organized into two distinct hemispheres.  When we approach a task with our full attention one hemisphere is adopting the role of performer while the other is adopting the role of observer.  Switching to a new level of awareness requires that both hemispheres drop what they were doing.  Hemisphere A adopts the task previously performed by hemisphere B while hemisphere B adopts the newly required level of awareness.  The assignment of “A” and “B” to the left or right hemispheres will depend on the context and the direction of the attentional shift (towards performance or towards meta-cognition.

I’m not prepared to deep dive into the cognitive neuroscience just yet but perhaps in a future edition…

Implications for Mindful Learning Curves

This is just one more perspective that describes the cyclical nature of the mindful learning curve.  Periods of acceleration tend to be those marked by an emphasis on performance.  When a period of acceleration exhausts itself we are plunged into uncertainty…forced to regroup and develop a new situational awareness.  Periods of stagnation tend to marked by their emphasis on first meta-learning and then learning.

These cycles will frequently involve violent ups and downs because dual mind limitations prevent effective smoothing.  An effective shift towards meta-learning will demand a significant attentional shift away from performance.  The internal experience of stagnation will therefore be synonymous not just with inability to perform, but also with inability to focus on performance.  During periods of meta-learning performance is inhibited not only by simple performance anxiety but also by constant second guessing and meta-evaluation that interrupts flow.

Periods of acceleration begin to gain momentum once a satisfactory mental model has been reconstructed.

Dual Mind Limitations and Structural Change

Similar dynamics will apply to any organizational unit that regards itself as a functional whole.  The implications for our current economic malaise should be obvious.  Any singular policy focused on a monolithic unit such as the national economy will prove unable to promote both current performance and meta-learning (structural change) at the same time.  These are mutually exclusive intentions that a homogeneous or consensus-seeking group cannot pursue simultaneously.

This is why emerging economies adopted special economic zones and why they are now beginning to experiment with charter cities.  One set of policies, promoting current performance, is preserved in one set of geographic areas.  Another set of policies, promoting entrepreneurial experimentation and meta-learning, is developed for the newly established economic zones.  To the degree that the two policy environments remain distinct performance and meta-learning are achieved simultaneously.

Policy makers in developed economies around the world would do well to acknowledge this reality.  Until then we will drift aimlessly from one overly vague diet plan failure to another.

photo courtesy of eukalanato

Does engagement lead to productive collaboration or distraction?

…

I faced a curious conundrum recently when someone pointed out that I was equally supporting two apparently contradictory positions.  A few weeks ago I wrote a long essay exploring the phenomenology of continuous learning.  That was largely a story about developing one’s own internal capabilities.  The implied hypothesis was that by focusing deliberately on certain forms of creative discipline, an individual can develop exponentially superior capabilities in the long run.

On the other hand, a common theme throughout much of my writing has been the value of collaboration, intellectual diversity, and knowledge sharing.  The basic hypothesis underlying this line of thinking is that individuals can develop superior results in the long run by actively engaging with communities of similarly enlightened confederates.  As  such, learning is conceived as a social activity.

One strategy emphasizes individual learning while the other emphasizes group learning.  One suggests isolation and focus while the other suggests engagement and openness.  Both dangle the same carrot – compounding gains in knowledge and capabilities.  Can both be correct without contradicting each other?

Let’s dig a little deeper…

Finding Flow

The argument for individual learning derives largely from two popular notions: flow and deliberate practice.  Ideally, consistent deliberate practice improves an individual’s ability to achieve flow.  Deliberate practice trains the mind, habituating the flow state.  Regular achievement of flow then further accelerates the learning curve.  Cal Newport concisely outlines  the characteristics of deliberate practice (condensed from a list originally produced by Geoff Colvin):

1. It’s designed to improve performance. “The essence of deliberate practice is continually stretching an individual just beyond his or her current abilities. That may sound obvious, but most of us don’t do it in the activities we think of as practice.”
2. It’s repeated a lot. “High repetition is the most important difference between deliberate practice of a task and performing the task for real, when it counts.”
3. Feedback on results is continuously available. “You may think that your rehearsal of a job interview was flawless, but your opinion isn’t what counts.”
4. It’s highly demanding mentally. “Deliberate practice is above all an effort of focus and concentration. That is what makes it ‘deliberate,’ as distinct from the mindless playing of scales or hitting of tennis balls that most people engage in.”
5. It’s hard. “Doing things we know how to do well is enjoyable, and that’s exactly the opposite of what deliberate practice demands.”
6. It requires (good) goals. “The best performers set goals that are not about the outcome but rather about the process of reaching the outcome.”

Though #5 notes that it’s hard, the individual practiced in deliberate practice should develop a superior ability to achieve flow.  With achievement of the flow state comes all the benefits associated with accelerated learning:

Flow has a strong, documented correlation with performance enhancement. Researchers have found that achieving a flow state is positively correlated with optimal performance in the fields of artistic and scientific creativity, teaching, learning, and sports.

Flow also has a strong correlation with the further development of skills and personal growth. When one is in a flow state, he or she is working to master the activity at hand. To maintain that flow state, one must seek increasingly greater challenges. Attempting these new, difficult challenges stretches one’s skills. One emerges from such a flow experience with a bit of personal growth and great “feelings of competence and efficacy”.
(citations were removed from this quote for readability, see original)

If internal flow so thoroughly magnifies our capabilities, would we ever want to distract ourselves with hassles of teamwork?

Participating in Flows

This conundrum revealed itself while spending a week working with a team whose goal it is to create an ecosystem of tools that sustain and amplify scenius.  The lifeblood of scenius is knowledge flow.  The more knowledge flowing the better your chances of sparking scenius.  The obvious reason is that the knowledge brought to a community by each individual is compounded as it is shared and recombined with the knowledge contributed by all other community members.  This is what John Hagel and John Seely Brown have described as the collaboration curve:

There’s a classic story in economics primers illustrating the power of network effects. It tells how the first fax machine gave little value to its owner–after all, there was no one else with whom to send and receive faxes. As time went by, however, the value of that first machine increased as other people bought fax machines, and soon its owner could send faxes to the far corners of the earth, and receive them in return.

The point of the story is how the value of a node in a network rises exponentially as more nodes are added to it. These are called network effects.

Now let’s add a twist to the story. What would happen if, at the same time more fax machines joined the network, each machine rapidly improved its performance? The result would be an amplifying effect on the first level of exponential performance. One exponential effect occurs from growth in the number of nodes. A second amplifying effect arises from the improving performance of the machines themselves.

Fax machines, of course, don’t perform better as you add more of them to a network. But people and institutions do. And that’s where the concept of network effects gets more interesting–when we apply it to how people might perform better.

Surely not just any collaboration will do.  Certain parameters must be established to ensure clear communication and a sufficient signal-to-noise ratio.  But when the environment is just right magic can happen.  In Kevin Kelly’s words:

Individuals immersed in a productive scenius will blossom and produce their best work. When buoyed by scenius, you act like genius. Your like-minded peers, and the entire environment inspire you.

You act like a genius.  Are you actually genius…or are you simply buoyed temporarily by scenius?

Reconciliation

We have two approaches offering apparently opposite prescriptions.  One prescribes more time spent quietly engaging in deliberate practice.  The collaboration curve suggests that we should spend more time sharing tacit knowledge in the pursuit of scenius.  Both promise that properly following these prescriptions will unlock compounding performance improvements.

We might simply conclude that each strategy has merit in its appropriate domain.  The disciple of deliberate practice will achieve accelerating performance gains in individual creative endeavors.  The surfer of networked flows will achieve accelerating performance in collaborative endeavors.  One becomes a genius while the other nurtures scenius.

There is however a more satisfying possibility…

Do I contradict myself?
Very well, then I contradict myself;
I am large — I contain multitudes.
-Walt Whitman

Abstracting from our natural fixation on the individual perspective, it becomes clear that both prescriptions are in fact identical.  Both notions of flow have the same inherent meaning – optimizing communication between nodes in network.  In the cultivation of scenius the networked nodes are individual people.  In the cultivation of genius the networked nodes are the multitudes within one’s own mind.  The state of flow described by Csíkszentmihályi is a state of scenius occurring within the brain of a single individual.  It occurs when an individual, through deliberate practice, has cultivated his internal environment in the same way that a community pursuing scenius cultivates its external social environment.

There is however, one critical flaw in the deliberate practice hypothesis.  The third principle quoted above states:

Feedback on results is continuously available. “You may think that your rehearsal of a job interview was flawless, but your opinion isn’t what counts.”

Feedback is easy to obtain if your goal is to be a violinist or a quarterback.  In each case the task is well defined the base of prior art is prodigious.  If your task entails creative destruction then the sources offering meaningful feedback are far less obvious.  And therein lies our point of reconciliation.  Scenius plays the role of coach for learning curves that are uncoachable…learning curves that cannot be plotted in advance and lack prior art.  Scenius provides the flowing genius with an environment in which to test hypotheses and validate conclusions.

Rather than being contradictory, each strategy, though distinct from the perspective of the individual, is critically important to the other.  A genius without a scene is just a nutty professor.  Scenius with genius is merely a mutual admiration society.  If each strategy does exhibit compounded effects then the best strategy is to alternate between the two…riding out the duration of a deliberate learning curve before switching to focus on a collaboration curve.  Building then testing.  Exploring and exploiting…

photo courtesy of craft_uas

The hacks and habits that I had learned previously have not only proved insufficient; in many cases they have proved counter-productive.  The habits that lead to success as an employee generally entail suppressing your unique strengths and emphasizing the strengths demanded by your employer.  In fact, the ability to (on demand) suppress your areas of divergence and emphasize your areas of convergence is an employment skill in itself.  The ability to thoughtfully choose between convergence and divergence is a free agent skill.  That may be less true for people who have found particularly fitting professions, but of course the dream-jobbers are not the people adopting free agent life-styles.

The dictum – emphasize your strengths – can however be dangerous.  It leads us to seek out people like ourselves and to emphasize divergence at the expense of convergence, rather than thoughtfully switching between the two.  It leads us to more isolationism and less collaboration.

How does one discover an optimal balance between convergence and divergence?

What does it mean to switch between the two?

The best principle I have discovered to date is expressed in the title of this post.  In the process of traveling deeper and deeper down the personality type rabbit hole I have hypothesized types for nearly everyone with whom I regularly collaborate or socialize.  Given a sufficient sample, consistent patterns emerge quite clearly…

People with similar personality types are almost invariably people who speak my language.  I can learn from them directly with very little effort.  Our conversations feel like I have plugged a matrix jack into the back of my head and I am directly downloading their knowledge.  Unfortunately, these people also share my same blind spots.

Communication with divergent personality types is more challenging.  Often we don’t speak the same language.  If I ask for advice directly, the response I get will feel wrong.  Occasionally this reaction is simple resistence, but more often it occurs because our basic mental models are dissonent.

The easy thing to do in such situations is to dismiss the other person’s perspective…to assume I can’t learn anything from someone so different.  The more productive response I am learning (and relearning, and re-relearning) is to observe.

More often than not, I can learn from what someone does even if our models for understanding that behavior initially appear irreconcilable.  Moreover, if I can develop my own understanding of a particular behavior it will usually turn out that I can reconcile our mental models as well.  That process of reconciling mental models is essentially what this deep dive into personality types has been all about.

The Lesson:

Effective personal development demands two distinct learning arcs.  The first involves discovering and developing our own strengths.  This process can be accelerated by learning from people with similar strengths.  The perspectives acquired from these cognitive dopplegangers will click instantly and can often be adopted immediately.

The second learning arc demands that we identify our blind spots.  These blind spots tend to reveal themselves through interactions with people of dissonent mental models.  Though it may seem that such people are too different and have nothing to teach us, we do learn from our interactions with them.  By observing divergent personalities we learn to emulate the strengths we wouldn’t develop natively.

photo courtesy of Eddi van W.

Why is creative work so perpetually frustrating ?

Why do you constantly feel like you are falling behind?

In an effort to recover from my recent mini-rut I spent quite a bit of time consuming material that, in retrospect, revolved around these questions.  I will try to synthesize several of the more promising items and see if I can’t push them a bit further.

Thrust and Drag

Venkat Rao, attempting to explain the phenomenon of the 10x engineer, proposes a model of creative work based on an analogy to the mechanical concepts of thrust and drag:

He defines thrust work as those tasks with the potential for super-linear performance improvements as a function of consistent extended blocks of deliberate practice:

…such exponential gains always involve positive feedback loops, and thrust tasks contain two of them: the autotelic loop within a session, and the longer-term deliberate practice benefits that carry over between sessions.  These two positive-feedback loops together basically create an addiction.

Drag comes from those tasks that do not allow for super-linear performance improvement and moreover, tend to distract us from thrust work, interrupting the feedback loops noted in the quote above.

The moral of the story – if you optimize your time around thrust work and minimize drag, in the long run you will find yourself far ahead of the competition.  I won’t rehash all the details.  If you haven’t yet read Venkat’s piece you should take a quick detour over to the Tempo blog.

What is Drag?

If you’re back then you know that Venkat focuses specifically on managing drag work.  These are the tasks that seem important, even urgent, but ultimately offer little leverage in the pursuit of meaningful long-term development.  The solution offered is to optimize your schedule around thrust work.

But, suppose you have perfected the art of schedule management…have you permanently defeated the scourge that is drag?

Of course not.  Ultimately drag is anything that distracts you from thrust work.  Biological needs are sources of drag.  You surely know at least a few people who periodically engage in near-manic bouts of creative effort, largely by ignoring their needs to eat, sleep, or maintain decent hygiene.

Venkat focuses on schedule management because it is an obvious limiting factor.  Schedule management, for many people is the low hanging fruit.  However, alleviating one source of drag will only enable a temporary period of productive acceleration before another, previously latent source of drag emerges as a limiting factor.  You might reconfigure your schedule only to realize some weeks later that your poor eating habits limit your energy, crippling your ability to stay alert and focused.  While your schedule remained a mess, the constant distractions had obscured the limitations imposed by deficient diet.

If we incorporate the potential impact of lurking drag, the Thrust/Drag model no describes a steady accumulation of creative thrust.  Instead it describes a punctuated series of episodic curves.  A multi-year trajectory might be visualized as follows:

Each individual creative episode is unsustainable by its very nature.  As a given episode accelerates, surpassing the sustainable long term trajectory, the thrust engine overwhelms the available supporting capabilities.  For example, consider a common episodic cycle in the development of a consumer web start-up.

Starting from point A above, the company (let’s call it thrust.ly):

• slowly builds its user base through organic word-of-mouth marketing
• user growth hits an inflection point and accelerates (point B)
• the company is featured on TechCrunch and traffic explodes (point C)
• …and then the site crashes (point D)

Just as momentum build to truly exciting levels…some new limitation appears squelching that momentum.  For thrust.ly, new user growth stagnates for a period of time while they patch up their back-end to handle new levels of traffic.  Point D represents the anti-climactic transition to a new episodic growth curve.  The main source of drag throughout the previous episode (lack of exposure) has been alleviated but a new source of drag (lack of scalability) quickly emerges as the limit to growth.

The same dynamics apply in the individual context that Venkat addresses.  You work on something for a long time gradually accumulating momentum.  Finally you hit a milestone, accolades follow, then after a brief period of excitement…anti-climax.  You achieved your big goal…now what?

The problem is that you outran your supporting capabilities and that deficit became a source of drag.  Perhaps you didn’t have systems in place to capture leads.  Perhaps you lacked the bandwidth necessary to follow up on all the new opportunities.  Perhaps, due to lack of experience, you pursued the wrong opportunities.  Perhaps you just didn’t know what to do next – you outran your existing knowledge base.

In one way or another new varieties of drag emerge.   The accelerating curve you had been riding becomes unsustainable and you find yourself mired in the slow build of the next episode.  This is what we experience as anti-climax and temporary stagnation.

Mindful Learning Curves

This cycle of acceleration and setback comports with another post by Venkat describing the Mindful Learning Curve:

Traditional learning curves are typically smooth and S-shaped.

They are smooth because they typically track only peak or trough performance.

They plateau for a different reason: they use the same performance metric for all levels of performance. This may work at the Olympics, but is deeply misguided in most real-world domains. Performance quality is something you measure differently as skill levels increase.

He offers the following graphic as an alternative:

Why might a long term learning curve evolve in this sort of pattern?  Venkat explores the question at the level of day-to-day energy and inspiration.  But if we are to interpret the cycles in the chart above as phenomena evolving over weeks, months, or years, then we need a similarly scaled driver.

Fortunately, the analogy to thrust and drag provides just such an explanation.  Superimposing a few additional curves yields following:

The green line represents a sustainable multi-year trajectory.  The blue lines indicate the trajectory of each individual performance episode.  If you could accurately forecast the shape of each curve then you could make a clean jump from one episode to the next wherever two blue lines intersect, producing a clean staircase progression.  Unfortunately, in the real world our timing is rarely so precise.

More often than not, we ride the high of each episode too long and then crash only when previously latent sources of drag become unbearable.  Recall Venkat’s claim:

These two positive-feedback loops together basically create an addiction.

That predictable behavioral pattern produces the saw-tooth function seen above.

Trials and Tribulations

Episodic acceleration also helps explain why creative work is so perpetually frustrating.  The 10x engineer is able to achieve such a great disparity relative to his peers only because so few of those peers persist in the pursuit of thrust work.  Most fall of the wagon because objectively they don’t seem to be making any meaningful progress.  And in fact, through the large majority of the curve that assessment is accurate.  Venkat concludes:

I’ll be 37 next month. I’d estimate that I’ve spent maybe 8-12 months overall in 10x mode. I am trying to systematically raise the “10x uptime” in my life, but it isn’t easy.

It may be damn near impossible.  The reality of exponential progress is that you spend the vast majority of your time slowly building momentum in order to enjoy the brief flashes of rapid progress.

If you’ve ever watched a space shuttle launch you have witnessed this phenomenon.  The countdown approaches zero, engines fire, smoke engulfs the launch platform…and the shuttle doesn’t budge.  Finally the countdown hits zero and the shuttle lifts almost imperceptibly off the platform…slowly accumulating velocity as it rises into the sky.  Not until nearly a minute after the engines ignite does it break the sound barrier.

That is the nature of thrust.  The ultimate surge as you approach escape velocity may be spectacular…but it is fleeting.  The space shuttle rapidly consumes its fuel and its momentum succumbs to the “drag” of Earth’s gravity.  Re-accelerating to escape velocity requires another arduous slow burn.

Paul Graham, in an essay exploring the differences between intelligence and wisdom, reflects on one facet of this phenomenon:

To me it was a relief just to realize it might be ok to be discontented. The idea that a successful person should be happy has thousands of years of momentum behind it. If I was any good, why didn’t I have the easy confidence winners are supposed to have? But that, I now believe, is like a runner asking “If I’m such a good athlete, why do I feel so tired?” Good runners still get tired; they just get tired at higher speeds.

Graham lacks “the easy confidence of winner” because most of the time he isn’t winning.  The episodic trajectory suggests that each win merely offers the opportunity to enter a new episode as a beginner.  Venkat argues that it is precisely this capacity to dynamically shift from a beginner’s mind to a winner’s mind, and back again, that enables the long term momentum:

Those who focus only on the peak get addicted to the highs that peaks bring. They abandon discipline and only attempt performance episodes when they feel the “flow” coming on. Unfortunately, without disciplined and regular “showing up,” these events become increasingly rare.  [Elizabeth] Gilbert’s daemon is not predictable but it expects you to be.

There is something like an economy of performers in your life. Every day you are a different person. Some days you are wealthy with flow, other days you are impoverished.

Many people are good at managing episodic tempo on either end of the spectrum. They might be good at peak performance or trough performance, or even both, but are bad at choosing the right tempo management behavior at the right time, and switching frictionlessly. It’s a mental trick — being able to swap out a peak game-mind for a trough game-mind very quickly.

In other words, creative work will always be frustrating because you can never be sure where you are in the process.  The best you can do is follow the most promising breadcrumbs and continually refine your own internal gyroscope.

A Different Sort of Rat Race

The skeptical reader at this point might contend that I am misrepresenting that nature of exponential growth, that we can only identify inflection points in retrospect, and that every point on an exponential curve looks exponential at the appropriate scale.  These would be reasonable criticisms if human intuition was scale invariant, but obviously that is not the case.  Quite the contrary, an unfortunate side effect of super-linear mindful learning curve is that you perpetually feel like you are falling behind.

Why?

Because paradoxically you are perpetually falling behind.  At any point in your journey you will tend to compare yourself to peers who have abandoned the long term trajectory and are progressing more quickly along comfortable linear paths.

Paul Graham continues the previously quoted comment as follows:

People whose work is to invent or discover things are in the same position as the runner. There’s no way for them to do the best they can, because there’s no limit to what they could do. The closest you can come is to compare yourself to other people. But the better you do, the less this matters. An undergrad who gets something published feels like a star. But for someone at the top of the field, what’s the test of doing well?
(emphasis mine)

Does the undergrad really feel like a star after getting something published?

Perhaps he does.  Perhaps he is approaching an episodic peak and his life feels like one uninterrupted peak performance.  But that can’t last forever.  As he accumulates thrust he also accumulates drag.  Soon he will have a choice to make: transition to the next episode and embark on a new slow build, or parlay his big break into a comfortable role that offers predictable linear advances.  If he persists along the mindful learning curve he will soon find himself falling behind peers who made the easy choice.

On this point Graham misses the mark.  The vast majority of people who “invent or discover things” are not at the top of their field, and they are hardly immune from the dissatisfaction that he describes.  For them, it is not unbounded expectations or unreachable potentialities that are frustrating.  Nor are potential comparisons to their most prodigious peers what they find most discouraging.  Most people learn to modulate their expectations at least that much.

No, it is the comparisons to people who are less talented yet objectively more successful that are truly disheartening.  At any level, there will be peers who have opted out of the mindful path and accepted a predictable linear course – the engineer who accepted the cushy soul-crushing corporate job, or the artist who started shucking formulaic garbage to a captive audience, or the entrepreneur who built a disruption-resistant moat around his one big idea.  They will be steadily accumulating tangible rewards while you are struggling for each sub-linear advancement.

Of course, if you persist in your dedication to thrust work, you will eventually surpass your linear counterparts.  Over the long haul you will end up in a different class.  But with each episodic jump you will be comparing yourself to (and steadily falling behind) a new cohort of peers.

The NFL rookie quarterback who invests a year on the bench adapting to the speed and complexity of the pro game, finds little solace in comparisons to all the guys who went undrafted.  Instead he grates at the comparison to the guy who was picked late in the draft yet still managed to jump right onto the field running a dumbed-down offense.

As Venkat notes:

Performance quality is something you measure differently as skill levels increase.

Once you graduate from a given episode your notions of success evolve.  Comparing yourself to a prior cohort of peers offers little consolation.  The only consolation available is the knowledge that there is no going back.  I will second Venkat’s assertion:

 Being without a thrust-engine is horrible. The periods of my life when I lacked one are the worst ones I remember.

Once you’ve had a taste, no extrinsic reward can offer a viable substitute.

photo courtesy of Eole