Sapience

George Mobus

The University of Washington Tacoma,
Institute of Technology

Part 1. An Introduction to Sapience
Part 2. The Relationships Between Sapience and Cleverness and Affect
Part 3. The Components of Sapience
Part 4. The Neuroscience of Sapience
Part 5. The Evolution of Sapience

 

Part 3. The Components of Sapience Explained

Background

In the introduction to this series I described, in brief, the four major components, or functions, of sapience as I have been able to decipher from various literature sources. Most of my early thinking about wisdom and sapience derived from the wisdom research literature in psychology, particularly the work presented in Sternberg, 1990. But several lines of neuroscience, regarding the architecture of the brain, in particular the prefrontal cortex, and its evolution have also contributed to some of these ideas (Barrs & Gage, 2007; Calvin, 1996; Calvin & Ojemann, 1994; Damasio, 1994; Gardner, 1999; Gazzaniga, 2005; Goldberg, 2001). In this installment I want to provide more detailed descriptions of the four functions and how I think they interact with one another. The view presented here should not be taken as a neurological one. Even if it turns out that the prefrontal areas I think are most implicated in the central function of sapience, these four sub-functions should be understood as descriptions of functions only and not brain modules. My plan is to provide some intriguing evidence from neuroscience in a follow-on installment. The fifth installment will provide some evolutionary background on sapience — how it may have been selected for, when and how it developed, and how it might have developed to provide better guidance to cleverness.

Recall that the components, as I understand them thus far, are judgment, moral sentiment, systems perspective, and strategic perspective. I will take these in order. And just as I segregated functions of the mind (affect, intelligence, creativity, and sapience) in the prior installment, I will attempt to circumscribe the functions of sapience in order to clarify the role of each separately. Then I will attempt to knit them together to provide a more holistic view of sapience.

As I tried to show in the last installment, the key to understanding the role of sapience is how judgment interacts with cleverness to guide decision processing. This is how sapience affects behavior. Here I will try to show how the other three components of sapience work together to create the framework of judgment.

Figure 1. Sapience can be viewed as four main, interacting functions; judgment, strategic perspective, systems perspective, and moral sentiment. All of these are supported by the storehouse of tacit knowledge generated by judgment-guided learning (supplied by cleverness). See text for explanation.

In the figure above we can visualize a rough map of how these components interact. The main processor I am calling “judgment” in keeping with the role that it plays vis-a-vis guiding cleverness in making decisions as covered in Part 2. The judgment processor receives ‘state of the world’ information from cleverness (intelligence + creativity) as well as inputs from systems and strategic perspectives and moral sentiments. It has access to the storehouse of tacit knowledge which it will use to formulate its outputs, primarily of judgments and intuitions directed at the cleverness component. It also provides information to the three other sapience components as well as modulating input to affect. Affect should be seen as driving or motivating moral sentiments, but the latter are incorporated into sapience as explained later.

The judgment processor assembles the relevant tacit knowledge given the state of the world (and inputs from the other three components). It formulates the recommendation to cleverness, integrates any new knowledge into the previous model, and updates the three components as needed. Note that systems perspective and strategic perspective have interact with one another directly as well. This is part of the hierarchical cybernetic structure discussed at the end of Part 2. The systems perspective is also in communications with cleverness in order to facilitate some logistical, but mostly tactical controls as needed by the strategic controller. This is less relevant to the present discussion but is included for completeness. I will further elucidate this loop in Part 4, The Neuroscience of Sapience when I cover hierarchical cybernetic structures in the brain.

Tacit knowledge includes an elaborate set of models of how the world works. These models are built up from experiences with the world over time through a presumed inductive process. Models are like dynamic concepts. That is they are complex sets of sub-concepts that interact with one another over a temporal frame. One of the simpler models of a small part of the world is a scriptShank & Abelson, 1977). Scripts are learned as sequences of expectations of events and actions that are applicable in numerous situations. They are a generalization over many instances of experience in similar situations. For example, a common script given in the cited reference is that of going to a restaurant and ordering/paying for a meal. The general sequence of events is usually the same at any restaurant you go to, though there are variations between fast food and sit down styles. Once the knower has a reasonable script encoded in tacit knowledge that individual no longer thinks about what to do next. It is automatically generated as part of the knowledge milieu for a decision point in a particular instance of going to a restaurant.

It might be a good idea to pause at this point and distinguish between two types of memories that are sometimes confused, namely between declarative memory and what I have been calling tacit memory (also a form of implicit memory). The former involves memories of actual events, places, faces, etc. The latter is the background knowledge of concepts, categories, and models. Specific memories of places, things, etc., may be the foreground of consciousness while meaning and context, unbidden to ordinary consciousness, is the background. The two memory types are not disconnected, though they are undoubtedly coded differently in the brain and have different locations in the cortices devoted to their management. One form of declarative memory called episodic memory is what most people think about as being 'memories'. For example, they might think that our heads are full of strings of episodes, like frames in a movie film, that somehow all connect, and that is all there is to memory. But memory doesn't work this way. What seems to make episodes encode in memory is a strong relationship to the background meaning, specifically, affective tagging or somatic marking. Briefly, our brains do have an ability to encode sequences of a sort such as the script described above (after all that is what motor programs are). So a specific episode may be encoded given sufficient motivation to do so. As an example we may have a vivid memory of going to a specific restaurant and proposing to our fiance. We might not remember what we ate or how much we tipped the waiter, but we remember most of the actions and they are often indexed by the order of events (I proposed right after they served the dessert). But the pieces that make up the salient parts of an episode are probably not in discrete packages. Rather an episode is reconstructed from pieces of both episodic and tacit memories that are recalled in a specific sequence.

More importantly, there may be a deeper relationship between episodic and tacit memory in that temporarily stored episodes (from the day's activities) in working memory may get analyzed for semantic content which is transferred to tacit memory. At least some researchers suspect this is what is going on in REM sleep. Episodes having unique relevance might be transferred to longer term episodic encoding during non-REM sleep periods. Much research is needed to say much more about the way memories get formed. But the ways in which memory types are used has been revealed sufficiently to make note of these differences. Henceforth I will mostly be concerned with tacit knowledge (note also that tacit knowledge also involves procedural knowledge, as in how to perform some complex tasks without conscious attention or intervention, like riding a bike.)

Consciousness and the Mind Architecture

Though I would love to explore this avenue more fully, I must treat it as a mere detour to provide a little more context for the thesis of sapience. The field of scientific consciousness studies has been making considerable progress in the last decade. Once something no respectable psychologist would touch (only respectable philosophers), the explanation of consciousness is starting to take shape. Neuroscience has had a lot to do with this. It is now possible to identify areas of the brain that are actively participating in conscious awareness by subjects in fMRI and other neuroimaging studies. But for now the relevance is incidental to the main topic of sapience. The two concepts do go hand-in-hand, but, believe it or not, there is much more about sapience that I think needs to be grasped before consciousness (especially the big evolutionary question: what is it for?) can be better elucidated.

Figure 2, below, shows a rough map of the mind in a slightly different way. Here the triangle (or pyramid) shows roughly the amount of neural machinery that is given to various functions. I've also identified the hierarchical cybernetic model represented by brains/minds. The diagram shows relative proportions of brain activity that is either available to conscious awareness (or semi-conscious as in aware of a mood or feeling without being able to say precisely why it is being experienced) compared to subconscious processing.

 

Figure 2. A rough overview of mind/brain functions that shows relative proportions of what is available to conscious awareness in the awake state. Interactions with the body and the outside world are shown at the bottom of the pyramid. Considerable processing power is given to receiving and processing sensory data from both the environment and from the body. The brain integrates this data to form a situation state report. This is sent upward informing the coordination control level and higher levels where motor and endocrine outputs are initiated and sent down for innervation of the body. The highest level of the pyramid is the conscious level where awareness of what is happening and what the body has done in response. At this level strategic controls operating over a much longer time frame formulate plans. Either consciously or unconsciously this level can adapt models in tacit knowledge based on long term results.

 

Sapience is shown at the top as a relatively small part of what the brain is doing. But all activities of the brain do, indeed, eventually feed into this seemingly smaller activity. The flow arrow from the central region, labeled 'models of self & world', show that tacit knowledge about self and the world, which includes current states of both (short arrow pointing straight up in the middle), is available to the conscious/sapient mind which then uses this knowledge to perform executive functions, i.e. to guide intelligence and creativity in decision making.

Most of our routine decisions do not require any awareness, nor strategic control, and so are generated directly by the coordination level. You know the experience of driving a car. You hardly think about controlling it and only need to be keenly engaged (conscious) when a surprising event occurs. Indeed, most of our daily activities do not need supervision by conscious/sapient awareness. Most can be handled nicely by lower level intelligence(s).

When we are conscious we (our brains) are either involved in intentional thinking, attending to novelty or semantic salience in the environment, or are simply aware of spontaneous thoughts (as in day dreaming). The latter is arguable as far as consciousness is concerned, but most of us, when we snap out of a day dream, have a memory of what we were thinking. These conscious moments play an important role in sapience in that they trigger what I call a second-order judgment process. That is, the judgment processor is activated to make judgments about the judgments themselves. We are generally conscious of our decisions (made at the subconscious level) after the fact and we are aware of the effects those decisions have on the situation (the results in the environment and on ourselves). This awareness is fed back to the subconscious mind where it can be used to modify or alter the models if our results were less than favorable, for example.

Thus, sapience and consciousness are interrelated as operations at the highest level of the hierarchical cybernetic architecture of the mind. This, I think, is at least part of the explanation of what is unique about human beings as animals. Our minds have evolved this sapience/consciousness apparatus to achieve strategic control not only for a single individual, but for a social body as well. In a sense this mechanism implements a kind of distributed strategic control function among members of a tribe/family.

One more note on the issue of consciousness before going back to a more mechanical explanation of sapience. Most people will accept that animals are, in some sense, aware of their environments. Many will also accept that some higher mammals, e.g. chimpanzees and possibly dolphins, are self aware. That is they have what I have called second-order consciousness. Self awareness includes awareness of the self being aware of the environment. Such second-order consciousness may have been the route to higher sociality (than just a herd or colony) in mammals. Chimpanzees recognize one another as individuals. They have unique personalities (some claim the same for dolphins and elephants). But sapience may add yet a higher order to consciousness, at least what I have called a 2½-order consciousness wherein we are occasionally aware of being aware of awareness! There are first-party reports, from time to time, from people who have experienced internally observing their own thinking in action. This is often reported as a kind of disembodiment from the mind or as a “higher” mind observing the ordinary mind going about its business of being aware of the world. These reports are rare and sound esoteric. Nevertheless there may be something to this in the model, suggested by Damasio (1994, 1999) of a hierarchy of what he called maps (see also Part 4). Figure 5 provides a quick summary of these ideas and a hint of what this sapient 2½-order consciousness might be.

 

Figure 3. Damasio posits a hierarchy of what he calls maps or images of the states of things from moment to moment. There is a rough correspondence between this model and that in Fig. 2 in that there is a flow of information from the perceptual systems and body sensing through neural structures that map those states and present an integrated version to higher level maps whose job it is to figure out what is happening. The “situation map” is what we would call ordinary or 1st-order consciousness, or awareness of the environment and the body. This map is a convergence zone for all of the inflowing information and is related to lower level operational decisions (e.g. controlling the throwing of a rock). The “awareness map” monitors what is happening in the situation map and this is our ordinary experience of being conscious. We are aware of what is happening but also aware of our memories and objectives. This is where tactical control gets initiated. Working memory provides a scratchpad where current and recent states can be stored and called upon for generating actions, or focusing attention. Note the two-way communications between memory areas (also dynamic maps). Finally, the “reflection map” provides a kind of ultimate monitor able to control the use of tacit memories and working memory through the awareness map. While speculative, this model does help explain a number of phenomena associated with human consciousness and is very much conjoined with the thesis of sapience.

 

Judgment

Making a judgment is not the same thing as ‘taking’ a decision. A judgment may be used to guide a decision but the latter is perceived as a conscious act, whereas the former is perceived as a feeling or intuition. Judgments come automatically from the subconscious mind as part of a ‘knowledge milieu’ (Part 2) that operates in the intelligence processor to effect the option selected. But we should recognize that there are a range of judgments in terms of complexity, scope, and time scale that affect our decisions. There are also differences in judgments with respect to the strength or salience (or conviction) based on the depth of experiential knowledge held in tacit memories. Finally, there is an issue of efficacy of the model being applied. The inherent strength of sapience conditions this factor. Taken together, all of these factors determine how well our judgment succeeds in guiding our decisions toward efficacious outcomes.

Efficacious Models

Starting with the last point above about the efficaciousness of the models of the world and the self, which are used to generate a judgment or intuition, the recent research in human failings at making good, or even reasonable judgments in certain instances has brought to light a possible weakness in our mind's (brain's) capacity to make good decisions. It turns out that the brain is imbued with a number of heuristic-based mechanisms that serve as templates or baseline models for a number of different judgment tasks. There is now a rich literature in what is called the “Heuristics and Biases” program in psychology (Gilovitch, et al., 2002). Investigators have been systematically testing human judgments under a variety of circumstances to determine if there are a set of consistent mistakes made where judgments tend to be biased for some systemic reason. A number of mental heuristics have been proposed that lead to those biases that have been found.

For an example, the representativeness heuristic tries to match a sample (say a percept) with a canonical representation (a generalized concept) by an associative recall process. Features from the sample help recall representative concepts when they are the same or similar as those held in the concept (also called an exemplar). In many early evolutionary real word instances (meaning situations such as seeing a large cat-like creature and recognizing it as potentially dangerous) this is actually a pretty good way to go. It has the advantage of being extremely fast, which in many cases could have been the difference between life and death. There are, however several problems with reliance on representativeness in our complex modern world. First, what if you don't have an efficacious canonical representation that matches the percept? Or, worse yet, you have a generalized representation that is missing some subtle features that are actually important in distinguishing the true character of the percept. The brain will do the best it can, but what is introduced is a tendency to judge the percept on the best you have, and that may not be good enough.

Another example is the availability heuristic. This one seems to be related to the ease of recall from memory (either explicit or tacit). People have often noted what is called the ‘recency’ effect where someone will make a judgment that favors the last experience in a sequence of similar experiences, even if it happened a while ago. For example, clever real estate agents can show prospective buyers a series of houses in which they show the house they really want to sell last. As often as not the buyers have better thoughts about that house. Neurologically, the features of the most recent house may have damped down those of prior seen houses, which might have been even more attractive to the buyers if they could remember them. So there appears to be a consistent tendency for people to base their judgments (when decisions need to be made) on those factors that were most recently activated in memory rather than do a re-analysis of all of their memories. Again, this is actually probably evolutionarily sound. Foragers will frequently pass up smaller game or patches of food when they are not very hungry but will return to the last remembered patch when they are since it is also likely the closest in spatial terms. This even though it might not have been the largest of the ones visited. Here there is an energy saving issue. When you are hungry get to any amount of food that will sustain you in the quickest fashion. You can always go back to a prior visited patch if you need more.

As a last example of a heuristic that psychologists focus on we return to the affective influence on decisions already discussed. The affect heuristic is what I have claimed is the basic decision guide from our limbic systems. This is also what Damasio called the “somatic marker theory” or tagging an option with valence based on emotion-laden past experiences with the same option (1994). Most of us know quite well what kind of trouble we can get into when we choose based on emotional feelings versus reasoning.

There are many more candidates for heuristics that are pre-programmed, so to speak, into the brain. These heuristics are all part of the ‘system 1’ (Part 1), fast, subconscious judgment process. They probably worked most of the time in early humans, or else we wouldn't be here or they wouldn't still be with us. But in our modern world they too often cause us to make serious errors in critical judgments. They, by themselves, were never able to handle complex social or cultural problem solving. That is why we developed sapience to the degree we did. Sapience strengthens the mind's capacity to override system 1 (system 2 is the rational thinking, but not necessarily just conscious thinking — Part 1). Sapience allows us to learn much more in the way of tacit models of the world and its subsystems. Our representative concepts can be much more detailed and through sapience become ever more efficacious as we age and gain experience. Our control over availability of memories is more strict, causing us to reflect more on not-so-available memories for comparisons. It makes us consider comparisons, seeing samenesses and differences in more subtle features. It also dampens down our affective tendencies to succumb to our wants and desires (or fears).

I believe a very useful measure of the strength of sapience may prove to be the degree to which our heuristics and biases rule our decisions in complex situations. I strongly suspect that observations of a sample of the general population will show that the heuristics are relied upon much more often than appropriate. But that will take some significant advances in the kinds of tests and probes that psychologists have developed so far.

From Mechanical Judgments to Value Judgments to Strategic Judgments

Judgment processing covers a wide range of scope depending on the nature of the decision problem in focus. Something as simple as judging where to put ones foot in stepping forward in rough terrain involves low-level models of ‘difficulties encountered in walking’. In fact the basis for the evolution of higher level judgment capabilities probably started with this kind of background processing in early quadrupeds. Primitive cortices (paleocortex) are found in amphibians and reptiles that may be involved in such low level judgment processing.

The use of tacit knowledge and judgment in guiding current decisions is one of the characteristics of mammalian and avian life forms. What mostly differentiates creatures in the phylogenetic tree is the scope, degree of salience, and time scale over which tacit knowledge spans. For example a duckbill platypus (Ornithorhynchus anatinus, order Monotremata) is an example of an early mammal whose environment is relatively simple and whose modus operandi is fairly straightforward, even if a bit bizarre. It's brain, specifically its cerebral cortex (forebrain), is scarcely more than a shallow covering of the mid-brain (limbic brain centers). This cortex is presumed to code memories for specific places, mate, pups, good hunting places, etc. whatever is important in the life of a platypus. The frontal part of the cortex organizes attention and decisions and the rest of the cortex processes sensory data (much from the sensitive bill) and formulates learned motor responses. Judgment most likely amounts to not more than moment by moment frames for guiding real-time activities.

In mammals and birds living more complex life styles the neocortex is much expanded and thickened owing to the vastly greater amount of knowledge these animals need to learn in order to succeed. Most of the knowledge has to be learned (vs. genetically endowed like affect) because the complex environments are also subject to non-stationarity, meaning that individuals need to be able to adapt behavior over their entire lives.

Additional low level judgments include what we call values. Values are a set of attributes tagged with valences (good or bad) that we use to judge a wide variety of situations. The origin and cognitive processing of values is still an area begging for more research. Some values can be seen to be innate, so probably part of the genetically mediated moral sentiment processor. Such values tend to elicit strong emotions when they have been violated. The emotional response of disgust, for example, seems to be elicited by a number of situations that can be interpreted as harmful if pursued. Evolution equipped us with an automatic revulsion of such situations (one commonly cited example is the near universal revulsion of incest). Other values appear to have been learned in the context of a particular culture. Our moral codes include locally evolved guidelines for what is right and wrong behavior. These learned guidelines generate judgments on on-going situations and even evoke emotional responses that can overcome the rational decision making system. Racial biases are often cited in this vein.

A great deal more research is needed to tease out the innate from the learned values models but the fact remains that these models, and their generated judgments, are powerful forces in guiding thinking and decision making. Higher sapience may dampen down these forces when and if it is exercised.

At an intermediate level we make judgments about a wide variety of situations in daily living. We decide to drive to work rather than take the bus when there is a chance we will have to work late and not be able to catch the bus home. We decide to wear that new shirt to the office because we want to look our best for the new employee that looks attractive. These are examples of judgments that involve a mix of knowledge and affect. These are the most common kinds of judgments we make routinely. And they do wonders to get us through daily life. We do not have to think long-term. We do not have to consider who all might be affected by our decisions. We simply consider the situation at hand and bring to bear a limited and restricted set of models that seem to apply.

At a somewhat higher level, however, we might think twice about taking the car to work because in the back of our minds is the higher price of gasoline and the fact that we want to save for some special reason. The judgment then comes down to simply make sure we leave the office in time to catch the bus. Another situation might involve that new attractive co-worker. Assuming the shirt trick paid off and you got a date, you might start considering the prospects for a longer-term relationship. Now not only emotional drives, but consideration of many other attributes about the person start to enter the mix. And a sufficiently sapient person might be starting to consider what life ten years hence might be like with this other person as a mate.

Still higher in the judgment hierarchy is the kind of considerations needed to think about the good of others. Coming up with worthy judgments about what is good for others requires far more complex models than just coming up with judgments about what is good for ones self. The models have to include those of the persons involved as well as their environments, the context of their lives. Most people formulate opinions about what is good or bad for others. Most of the time these opinions are grounded in values that actually apply to the one having them rather than being considered in the context of the others' lives. They may or may not be good for the other (and too often are not). Wisdom involves arriving at judgments about and for others that are grounded in the others' circumstances and not just their own.

At a very high level of the hierarchy judgments are based on extensive models of the world, not just the local environment. These models are built with extensive knowledge, both explicit and implicit (tacit) and are constantly being modified, improved as new experiences are had. One must be motivated to grasp the ‘bigger picture’ even as they learn more. Persons possessing this level of sapience will naturally tend to think about the future, how the world will evolve, how people will be affected in that future, and what can be done now to improve the chances of good outcomes in that future.

This rough hierarchy of judgments reflects the way in which functionality is accreted in the process of evolution. I will say more about this in Part 4, but the basic idea is that existing structures, that are responsible for certain functions, are not dropped as evolution produces more complex organisms. Rather these functions/structures remain but a new layer of function/structure is accreted to, or built on top of the existing one(s). The new functions might serve to modulate the lower level functions, i.e. suppress them when the higher level function produces a contrary result. We've seen this kind of down modulation with respect to the rational thinking system damping down the affective system in certain decision situations. Figure 4 shows the organization of judgment processing just described. As in the hierarchy of mind itself, we see judgment as a pyramidal structure with the low-level functions occupying the broad base and the highest level social judgment processing occupying the narrow and shallow upper peak. This again reflects the relative strengths of sapience. We might expect that in much higher sapient individuals the upper areas of judgment would be broader that this diagram implies. That is for future research to determine.

 

Figure 4. Judgment processing can be organized (categorized) in a hierarchical structure reflecting the amount of processing power given to various ‘depths’. The vast majority of judgments come from models of mechanical, value, and everyday levels of situations. Only a smaller fraction of judgments are directed at higher needs such as long-term thinking and social judgments.

 

Expanded Dimensions of Interaction

In the bigger, more advanced brains, judgment becomes more important in its role of guiding decisions. Decisions themselves have become much more complex along several dimensions (Horgarth, 1980). First consider the role of time. While the duckbill might only be concerned about what is happening in real-time, more advanced mammals have to make judgments that may have an impact on their lives, days, perhaps weeks from the moment. Humans make judgments that can affect them their whole lives, and the lives of their offspring well past their own deaths.

Another dimension is physical space. Human judgments can extend to the whole world today. Indeed, by making the decision to visit the planets we may make judgments affecting the solar system. When modern humans evolved they were already capable of migrating without a specific destination in mind. They spread from Africa rapidly. But even with this ability, their capacity for building a model of much more than a few hundred kilometers radius around an individual was probably limited. The more area a tribe occupied as effective territory (the known world to any one tribe) the more other tribes and physical conditions they encountered and would have to have models for.

As personal worlds expand the number of distinct objects of all kinds will increase, as will the potential for interactions between these objects. The raw complexity of a larger world probably increases, at least as the square of the radius out from an individual's location.

Stationarity is a fourth dimension. The longer in time, the larger in space, the more complex an individual's world, the more likely that unpredictable changes are going to happen. Murphy's Law comes into effect. No matter how large one's world might seem there is always a larger, more complex world surrounding it and interacting with it. And those interactions can lead to a cascade of changes in the individual's world. Think of the example of the invasion of a foreign species into an ecosystem. Change and difference is inevitable in the world if your world is complex. Species that have existed for so long, like the platypus, have survived in a relatively buffered world or a world where the kinds of changes that did occur had no direct impact on their fitness.

The situation for humans is seemingly at the extremes of time, space, complexity, and non-stationarity. We are omnivores, meaning that changes in species of plants and animals will cause changes in behavior as we attempt to adapt to the new varieties. Our memories, particularly our tacit memory system, must have a huge capacity in order to deal with all relevant knowledge needed to operate successfully in this expanded world. Moreover, it must be capable of constant and life-long learning as the accumulation of experiences act to refine concepts and their interconnections, or even revise older concepts as new evidence is encountered. As we now understand from the research, this latter is very hard for most people to do.

Once certain beliefs are encoded, especially in adults, it is extremely hard for most people to accommodate countervailing evidence and change their minds (c.f. Gardner, 2004, for insights into what it takes to change opinions and beliefs). The more affective attachment to beliefs there is, such as religious doctrines and stories or nationalistic sentiments, the more difficult it is to question them and revise our thinking. This is an aspect of common sapience that keeps humans from attaining wisdom that is effective. Indeed, there is a kind of pseudo-wisdom prevalent in humans who cling to old beliefs and use their tenants to guide decisions. This level of sapience was actually fine for primitive humans living in small bands and roaming over small territories. The wisdom of the elders was based on accumulated traditions (experiences) plus imagined explanatory beliefs. As long as the environment remained reasonably stable, these beliefs could serve a purpose in stabilizing the social framework of the tribe. But it is when the scope of the situation expands along the above dimensions that things go awry. Ancient belief-based wisdom starts to fail and decisions do not produce best outcomes.

One of the difficulties of complex, non-stationary environments is that causal relations are sometimes very confusing. Numerous causes can lead to the same effect. Causal chains can become causal webs. A single causal event can, due to non-linear, chaotic interactions, lead to multiple (stochastic) effects. As a result the veracity of our models of the world, as well as of ourselves, can become degraded too easily. We make poor observations of reality and any errors get encoded into our tacit storehouse. Then owing to the inherent biases of judgment (Marcus, 2008, gives a delightful and sometimes dismaying treatment of built-in biases in ordinary human judgment) our judgments are further distorted from reality.

In short, our minds and our average level of sapience as a species is failing to handle the world of complexity and non-stationarity that we have helped to create. We've made wonderful discoveries in science and engineering thanks to our superior cleverness. But we have generally failed to make wise decisions regarding their exploitation in inventions and their uses. My singular paradigmatic example: nuclear weapons. Indeed the very need for weapons at all points to the massive failures of sapience at the scales beyond the tribal. Of course human evolution included the xenophobic tendencies — the Us vs. Them affective influence (Berreby, 2005) — that give rise to feelings of hostility toward others, especially if competition for resources is prevalent. But again, a higher level of sapience means having the ability to override the limbic impulses long enough to think things through.

Reflective Judgment — Meta-knowledge

Potter (1971) defined wisdom as "...knowledge of how to use knowledge." In other words, wisdom, as he saw it was a kind of meta-knowledge that transcended mere ordinary facts and episodes. He argued that tacit knowledge included an embedded moral aspect (see below) but also involved an ability to reflect on one's own knowledge, what one knew, what one suspected one didn't know, and what one should know to be considered knowledgeable. His emphasis was on explicit self reflection, which must certainly be considered part of wisdom. But as I have argued, deep wisdom also involves non-conscious abilities to judge what tacit knowledge should be learned and attend to experiences that will further that mandate.

This view of meta-knowledge, whether tacit or explicit, helps to differentiate ordinary intelligence from sapience. One might be tempted to call sapience meta-intelligence, or meta-cleverness to include the role of creativity. I prefer sapience because there are aspects of the latter that do not behave as just meta-decision making. But I will return to this subject when I cover the evolution of sapience and the brain structures involved.

The term 'reflective judgment' can be broadly interpreted as the mind (either conscious or not) reflecting on its own judgments and making judgments about those judgments! I call this 'second-order judgment'. That is, the sapient mind examines the results of judgments made, large or small, and presumably guides learning to modify or refine the tacit knowledge that gave rise to the original judgment. Judgments must be judged.

Somewhat more narrowly reflective judgment entails epistemic cognition or thinking about knowledge (Kitchener & Brenner, 1990). Wisdom is often described as including an ability to make complex decisions in the face of uncertainty. Uncertainty is inherent in incomplete knowledge so a wise person understands that the risks associated with any complex, especially socially pertinent, decision is due to an incompleteness in their own knowledge. How gracefully the person deals with such uncertainty, that they continue to apply their best judgment without claiming that it is based on absolute truth, for example, is a property of sapience. The sapient brain knows when it is dealing with incomplete or even inconsistent models of the world and adjusts its judgments accordingly.

This too is a guide to what needs yet to be learned. Uncertainty might be reduced in future such situations by learning more knowledge about the characteristics of the current situation. Models can be improved so that better decisions are made in the future. Or, and this is the harder problem, if outcomes from judgments do not meet expectations, then models may need to be altered. This requires determining the failure and taking steps to correct the model for future use. Many ordinary people find this very difficult or never really realize that it is essential in order to become wiser.

So sapient judgment involves a self-monitoring and meta-judgment capacity that is essentially automatic and should generally result in improving tacit knowledge over time and multiple experiences. People who never reflect on their own progress toward wisdom (or evaluate the efficacy of their judgments) and never seek improvement are doomed to foolishness. An old (I think Chinese) paradox says that if you think you are wise, then you are not, but if you seek wisdom, then you are!

Moral Sentiment and Guidance to Reasoning

There has been a tremendous spurt of research into the basis of moral and ethical behavior in the last several decades. Neuroscientists, psychologists, and anthropologists have begun to unravel the neural substrates and universal behaviors associated with moral sentiments. And the study of the evolution of moral behavior has demonstrated that the human capacity for moral reasoning is innate and has developed extraordinarily in the genus Homo.

The literature on the subject is extensive and I cannot begin to do the subject justice in this short writing. So I will focus on some of the main points that tie in with sapience. The keys to understanding the underlying motivations in sapient minds is the evolution and benefits of true altruism and cooperative attitudes that have allowed humans to form trust-based alliances even with non-kin and strangers.

At the core of the more sapient dynamics of social interactions is the sense of fairness and justice that helps maintain a generally well functioning social network. Fairness sentiments have recently been demonstrated at work in lower primates. Details of how humans experience justice and fairness have lately emerged from behavioral economics where many of the classical economics assumptions about rational agents have been found baseless or called into serious question. Models of humans operating under innate sentiments of fairness and justice have helped explain a good deal of human behavior that is otherwise puzzling under theories of human nature that depend on rational thinking.

But sentiments of justice and fairness have a dark side that, if not controlled, can lead to a breakdown of social structure. That is retribution, the fairness sentiment that demands punishment for cheating and immorality. The invention of rule of law has been one of mankind's greatest achievements whereby people feeling cheated are restrained from wonton retribution. The state takes responsibility for punishment and when things work right, the accused are afforded due process to determine guilt or innocence lest retribution be wrongly taken and lead to further conflict. Of course even the rule of law is no guarantee that things work properly. There are always tyrants and cheaters among the judges who subvert the process for their own gain. The proper execution of the law, in the end, depends on the judgments of judges! This is a critical aspect of societies. Judges who have the power to condemn or free must have good judgment. Unfortunately, if my conjecture about the rarity of higher sapience is correct, then our court systems, dealing with unprecedented numbers of cases and requiring a greater volume of judges on the bench, is doomed to poor judgments more often than not.

And that is the difference between strong sapience and the lesser kind that seems to be our lot. Truly sapient individuals seem to have the ability to down-modulate their own desires for revenge and thus have greater control over their more affective (limbic) reactions to cheats and criminals. This doesn't mean that sapient individuals do not experience anger and desire for revenge or retribution. It simply says that stronger sapience somehow controls those limbic-based urges and keeps them in check so as to make decisions more wisely. Recent imaging studies of brain functions have shown that some individuals do seem to have more prefrontal activity during episodes of exposure to cheating or perceived unfairness, correlated with more restrained decisions. We also have evidence from neuroanatomy that inhibitory efferent fibers from the frontal cortex to various limbic areas, including the amygdala, act to dampen emotional responses to events in order for the prefrontal cortex to 'consider' the situation before acting.

Altruism to Empathy to Caring and Sharing

A starting point for understanding moral sentiment as an underpinning of sapience is to see the role that altruistic motives play in human life. Our whole sense of wanting to be good, and help others starts with this basic biological mechanism for ensuring the success of tightly bound social groups in out competing other groups. It is an evolutionary argument but it takes an interesting twist at the human level when altruism turns into empathy and caring with intentional altruistic behavior.

A fundamental premise of altruistic behavior is that one individual is willing (or compelled) to sacrifice its life for the benefit of one or more conspecifics. Sober and Wilson (1998) describe altruistic-like behavior in a trematode parasite (page 18). Other researchers have observed altruistic behavior in numerous species at all stages of evolutionary complexity.

For some time evolutionists had wondered about altruism and how it could have come about. It seems obvious, on the surface, that altruistic behavior would reduce the fitness of an individual (by exposing them more frequently to life-ending situations) and so selection would have weeded it out. But it is so clearly engrained in so many species that it must have an evolutionary purpose. Researchers have described various degrees of altruism and have generally provided satisfactory reasons why they would be favored. At the lowest level is the theory of kin selection, which basically posits that an individual's gene's chances of showing up in the next generation are improved if that individual ensures that close relatives are taken care of or protected, even if the individual does not reproduce. This mechanism is used to explain why female worker bees don't bother to reproduce. The principle may extend to tribes or colonies in some species where distant related individuals sound alarms when a predator is spotted, thus increasing their risk of calling attention of the predator to themselves.

Somewhat more inclusive (beyond kin) is the theory of reciprocal altruism in which members of the same community are willing to sacrifice themselves or take non-reproductive roles even when there is a weak genetic connection between members. Presumably there are strong benefits of other kinds in tight social networks such that it still increases the inclusive fitness of the group to have this kind of behavior even in the absence of direct genetic benefit (see Sober and Wilson, 1998 for a model of group selection providing a solution).

Many social psychologists have not been able to admit that the above mechanisms apply to human altruism, or what some have labeled 'true' altruism. While cases of people jumping into a frozen lake to save a stranger may have some basis in the above described, seemingly automatic reactions, what appears to most of us as genuine conscious caring for others goes far beyond mere kin or group fitness improvement. There must be something more that produces these feelings in humans. And that may be the role of sapience. The key being empathy.

Recently neuroscientists have discovered a remarkable kind of neuron in the brains of primates and possibly a few other non-primate mammals (and even birds). These neurons, called mirror neurons, have the interesting characteristic of firing both during the performance of an action by an individual and during that same act being performed by another individual when observed. These neurons, and in fact, systems of these neurons have been identified in human brains embedded in several higher order perceptual and integrative processing areas. This suggests that humans are capable of entailment with respect to much more subtle behavior by others, such as facial expressions conveying emotional state information of the other. There have been several studies that show that human subjects experience emotional mirroring wherein they not only grasp the emotion being expressed by others but actually experience a mood change in the direction of that emotion. The general phenomenon is what we would call empathy (Goleman, 2006, pp 40-43 for an introduction to mirror neurons and their possible role in empathy).

Altruism based in deep evolutionary roots of the brain along with this new mechanism of empathetic coupling may go a long way to explain so-called 'true' altruism. Other mental factors may still be active in some forms of altruism. It is suggested that a main motive for why people give to charitable causes is that they get a mental reward for doing so, thus suggesting there is no such thing as 'true' altruism. However, I do not see how these various mechanisms are mutually exclusive. Both empathetic-based behavior and subsequent reward are perfectly compatible means of reinforcing altruistic sharing and care.

Regardless of the details, it is recognized that deep caring for others is a core trait of wise people. Wisdom involves understanding that sharing and caring are at the heart of viable social groups. And, I suspect that even low levels of sapience involve a basic tendency toward more of this than being uncaring and selfish.

Yet selfishness is a problem in our societies today. The basic human propensity for sharing and caring might be muted when the social domain exceeds a limit based on sheer numbers and kinds of people encountered. Mankind evolved in a world where tribes rarely exceed several hundred individuals. It isn't unlikely that our subsequent evolution selected for those able to accommodate larger groups and strangers. After all, we have been living in such groups, villages, towns, states, etc. for five to eight thousand years. And we have adapted culturally, if not biologically, somewhat to those conditions. But the rate of change wrought in the information age has surely exceeded our abilities to accommodate the myriad strangers we encounter today. Indeed issues of xenophobia, ethnic conflict, etc. may have their roots in the fact that we have exceeded the number of others that we can extend our sharing and caring to.

One test of sapience might very well involve determining the extent to which a person can feel empathy toward strangers, and how much caring can be extended to different kinds of people.

Justice and Fairness

What is right behavior? What is wrong behavior? Are there universal rights and wrongs? And what makes it right or wrong in the first place?

Not that long ago the general belief was that different cultures around the world had different beliefs about what constituted right and wrong behaviors. The argument went so far as to claim that there were no universally held beliefs about right and wrong and therefore cultures should not be judged on the basis of their mores. It was all relative. And the evidence seemed solid. Even though, for example, most people throughout the world viewed incest as wrong, a few cultures, including some western ones, have practiced ritualistic incest (e.g. Hawaiian royalty marrying - brothers and sisters - to maintain the royal line). Similarly cannibalism is repugnant to most societies, yet some tribes have practiced ritualistic cannibalism for religious reasons.

However as the science has progressed it is becoming clear that there is something like a universal semantics of moral/ethical behavior in a manner not dissimilar to the universal disposition to language, e.g. speaking, hearing, and signing. All humans have a sense of right and wrong, even if the specific instances of what counts as right or wrong vary from one culture to the next. Moral sense is innate.

One of the clearest pieces of evidence for this innateness comes from experimental work with monkeys and apes which demonstrate a built-in sense of fairness (De Waal, 2005, Chpt. 5). Fairness involves a relational observation between the subject and others in the group. For example, when one individual perceives another getting an unearned reward he/she will tend to feel resentment toward the receiver if there is no apparent agent giving the reward (perceiving the recipient as a cheater). Or the observer may feel anger toward the agent that provided the unearned reward. It also works on the punishment end. If an individual observes a perceived cheater being punished, then he/she feels satisfied that this is an appropriate outcome — in other words justice has been served.

The fairness sentiment can also lead to jealousy. When one individual perceives another winning a reward he/she can feel jealous but not feel anger since the reward was earned. In a good way jealousy might lead the individual to efforts to seek a similar reward to even out the balance, to get one's fair share. Of course that can lead to frustration if the reward was actually a result of chance and not truly earned.

The main point is that our sense of what is right and wrong starts with an innate sense of fairness. Behaviors that help the members of the group achieve a fair balance of resource sharing, for example, are associated with right actions and lead observers of those actions to have favorable memories of the actor. Similarly, behaviors that unbalance the resources or harm others are perceived as wrong and lead observers to have negative memories of the perpetrator. Cheating is defined by this criteria, when an actor derives benefit unfairly. And feelings of retribution follow when the cheater is caught. All of this sense of righteous and moral sentiment plus many more related sentiments arise from innate mechanisms in the brains of social animals. And that includes humans. Our moral sentiments are grounded in innate senses of fairness and right and wrong actions (relative to the individual).

But another question that should be asked is: If fairness is innately based, how can there be cheaters and sinners in the first place? And that is a critical question to ask. The answer is likely grounded in evolutionary theory and the inherent variation in gene alleles in a population. At a more transcendent level of social life occasional cheating may be advantageous in terms of the exploitation/exploration trade-off that the evolutionary algorithm is always manipulating. Cheaters are in a sense a kind of exploration of the space of possible behaviors while conformers are exploiters of good behaviors as defined historically. Every so often the environment may change in a way that some form of cheating behavior leads to a survival advantage that assures at least some members of the species show up in the aftermath. Or it could lead to a behavior that actually helps the group.

So innate cheaters are a consequence of normal variation in the population. Under ordinary circumstances the cheater's behavior is not helpful to the group and so mechanisms for detecting and punishing cheaters are necessary to maintain group cohesion and functioning. Hence justice. The sense that a cheater has been punished is part of the package. In humans we find a spectrum of the concept of justice with regards to the protection of non-cheaters for whom some evidence suggests they are cheaters. This problem probably doesn't arise much in non-human apes and other social mammals. But human social structures are complex and, as I have asserted, the causal chains are often obscure so that it is hard to abduce the cause of an innocent being caught looking like a cheater. Once again the human propensity to create laws that protect the innocent until evidence can be examined fairly provides a way to mitigate injustices. Of course the various laws and institutions for applying them are as imperfect as their creators and so are no guarantee that justice will prevail. And cheaters can be found within complex institutions using laws and procedures for personal gain (picture the district attorney who is anxious to get a conviction so as to promote getting re-elected).

Emotional Control

The final piece I want to cover here involves the capacity of a sapient individual to dampen innate emotional responses to cheating and immorality in others. As mentioned above, this facility is what allows man to formulate laws and procedures to protect innocents. Handling the capture and punishment of cheaters and sinners requires dispassionate observation of the recoverable facts of the matter before finalizing a judgment. It is no accident that we look for some level of wisdom in those we elect or appoint as judges in our judicial system.

This control of the limbic responses to external events by the frontal cortex is found in all primate brain anatomies. But in humans it has reached its greatest effectiveness. There are many more efferent and afferent fibers connecting various areas in the frontal, and especially the prefrontal, cortices with numerous limbic nuclei in humans than in other apes (LeDoux, 1996). The prefrontal cortex monitors limbic activities and acts to dampen the motor responses until the executive functions in the frontal cortex has time to evaluate the correctness of the limbic response. I will be providing some more detail in the fourth installment regarding the neural basis for sapience.

Systems Perspective

Seed Knowledge — The Systems Scaffold

Our models of how the world, other people, and ourselves work are based on having a built-in intuition about how systems work in general. Indeed, our entire knowledge base is organized around systemness. And when we learn, we are incorporating our perceptions into a framework of systemness because that is how our brains are wired.

Our minds naturally look for things like boundaries, wholeness (Gestalt), cause-effect relations, and a myriad of characteristics of systemness. We automatically attempt to find patterns in noisy data, and categorize patterns in hierarchical structures. Our brains process incoming perceptions so as to see the systemic nature of nature. We can't help it.

This is not surprising since through science, which is supposed to be objective, we have discovered that the world, the universe, is indeed comprised of systems and systems of systems. We find causal relations among system components everywhere we look. In fact, the drive behind the scientific approach to knowing is that when we find phenomena that are not previously categorized, for which a pattern of organization and causal relations have not been identified, then we are essentially forced to look for these things. It is as if evolution predisposes us to see systemness because everywhere there are systems. We are systems. And we are subsystems of larger meta-systems.

This propensity to see systemness, or discover it if we don't immediately see it, is a fundamental organizing principle which our brains are constrained to use to learn about the world. The generic system is a kind of seed structure upon which we map percepts in order to have a means of organizing our knowledge.

Every knowledge construction requires some kind of template upon which to organize new knowledge. The mind is not a blank slate (Pinker, 2002). The brain itself is organized in such a way that we begin our construction of knowledge with the aid of built-in biases for key perceptions and organization of those into early conceptual structures, like categorization and hierarchies of types. Thus as we grow and develop our models of the world and ourselves, we start with a foundation of generic systemness and a scaffolding that provides a basic shape to how we understand the world. Literally, we can't see it any other way. To that structure we start fitting our experiences into place. It is probably more a matter of jostling the bits and pieces around until they 'fit' into the scaffolding and among other bits and pieces already integrated. It is a stochastic process. Some bits won't fit anywhere in the edifice and so get dropped even if they should legitimately be part of the knowledge base. Fortunately, these bits are likely to be encountered later again so they have more than one opportunity to get incorporated.

The point is that knowledge is built upon prior existing knowledge and the ultimate seed knowledge is provided by evolution in the form of an ability to model systems.

In the next part I will provide some ideas about how the brain actually accomplishes this feat. For now all you need recognize is that the generic system can be represented as a network or, in mathematics, a flow graph. Figure 1, above, is such a network and it represents the system I have been describing in words. The dashed line circumscribing sapience demarcates the system of interest and the other entities provide inputs and take outputs from that system. Figure 5 shows a generic system with the expected kinds of components. The system of interest has a boundary of some kind, it has component subsystems between which flows and associations occur in an internal network (not shown). It receives inputs of energy, material, and messages from environmental sources and it produces outputs of similar kinds that flow to environmental sinks. The arrows from and to environmental entities may also be reciprocal linkages with entities rather than explicit flows. This representation is kept simple for demonstration purposes.

 

Figure 5. A generic system has all of the features/attributes of a basic system in generalized form. Neural networks can encode the various elements and their generic interactions. The human brain has the ability to make copies of this generic model and then learn the particular features of each kind of component.

 

A generic system is encoded into the brain as a template for the learning of all real systems/objects that the brain will encounter in the future. Systems learning entails making a copy of the generic template somewhere in the cortex (probably in the frontal-parietal areas) and then begriming to link up specific perceptual and other conceptual features to the copy as it becomes particularized to the real system being learned. In Part 4 I will revisit this in terms of plausible neural circuits. The point here is that our brains are wired to look for subsystems and boundaries and connections, etc. as we construct a larger network of particulars. Figure 6 is meant to capture some of this. Starting with a fixed template copy, the brain learns the particulars of a system by identifying the features and attributes that should be attached to the model of the real system while also expanding and modifying some of the details. For example, the real system being modeled will have many more component subsystems with particular linkages. Characteristics, such as the nature of the boundary, may be modified as well.

 

Figure 6. A particular (real) system is learned by attaching perceptual and conceptual features to the template copy and expanding where needed, e.g. in the number of subsystems and their linkages. This is the basis for humans learning what is in the world and how things, and the world, work.

 

Since systems are subsystems of larger meta-systems, and are, themselves composed of subsystems, this copying-modifying procedure works in both the direction of the larger and the smaller. The brain can build a model of the meta-system by starting with an already built subsystem (now treated as a component) and situating it within the larger system. Note that the entities identified as sources and sinks can now be modeled in their own rights and their linkages constitute the more complete model of the meta-system.

Working from smaller systems to larger meta-systems is a synthesis/integration process. Working from a system inward to model the component subsystems as systems in their own right is analytical reduction. The brain automatically works at doing both of these. The former is driven by a need to understand the context of a particular system and leads to a grasp of a larger world. The latter is driven by the need to understand how a particular system works. Both of these processes are aimed at providing the brain with a basis for anticipating the future behavior of the systems it observes (see below).

Sapient Systems Thinking

As indicated above, one of the characteristics of judgment is in guiding what should be learned. We can now see that the systems bias is part of the basis for this. As our internal models of world systems improve over time and experience, our judgment derived from them can better guide the intelligence machinery in attending to perceptions that help improve the systems models. This is low-level judgment at work, the kind our biological ancestors had evolved. What makes for sapient systems thinking, and judgment so informed, is the role of strategic (long-term planning, see below) thinking, conscious reflection on knowledge being constructed and editing knowledge as needed (including editing plans for acquiring knowledge in the future). Such judgments guide which systems need to be learned.

This is a huge subject, of course, and will need much explication, beyond the scope of this work. One succinct way of looking at this is that sapience expands the role of judgment in guiding future learning and refines the systemic nature of what is attended to in that future time. As noted above, the drives that produce the learning of particular systems causes us to explore both inward (reductionist analysis) and outward (synthesis and integration). The more sapient mind is equally interested in both directions. But all too often most humans run into limitations on what they are able to do in terms of expanding their models and understandings both inward and outward. This is a scope issue relating to the same problem as mentioned above for judgment. Most humans have limited curiosity. They are not driven past a certain point, reached about middle age, I suspect. As children, while the brain is still in rapid development, curiosity directed at learning the smallest details and the largest relationships is at a maximum. It is hard to say for certain when in a person's life the drive to curiosity starts to diminish. It is hard to say why it does. One can imagine a storage limit, but as I have argued, this seems less likely given the way the brain encodes systems by reusing features that are common to many systems and simply organizing appropriate linkages (see Part 4). As an aside, I do posit that our modern education system may have a great deal to do with damping down children's enthusiasm as it attempts to force-feed knowledge, which is generally not systemic in nature, into the minds of young people. By the time they graduate from high school (if they graduate) they have been told, in so many words, that the world contains many different disparate bodies of knowledge and they must choose one such body to learn well so that they can do a good job in the marketplace. It is hard to imagine how this message can promote curiosity and a love for learning.

But I also suspect that a continuing life-long drive to curiosity depends on the level of sapience in the individual. With lower sapience comes a limited scope and time scale for thinking. People learn just what they need to know to get by in the world they are used to. They do not, in general, expect that world to change very much. They expect whatever trends exist to continue on into the future. So at some point they are no longer concerned with expanding their scope (learning the yet larger meta-system in which they are embedded) and they feel competent knowing ‘enough’ about the daily systems they deal with that they do not need to know how they work inside. Lower sapience goes along with a limited world view.

Sapience involves intentional model building such that one becomes more effective in problem solving in an ever wider scope as experience grows. One attribute of a wise person is grasping the interconnections between elements of a complex system, especially a social organization. Applying systems thinking to such organizations increases the probability of finding solutions that will work. And wise people seem to continue learning their whole lives.

Strategic Perspective

Strategic Thinking and Wisdom

Systems, and the meta-systems perspective in particular, allows the human mind to contemplate the future. When one begins to understand what we could call the ‘bigger picture’, one recognizes that the larger meta-system in which they are embedded is an on-going process operating on many time scales. Humans can think about the future. They can think about tomorrow, next week, next year, and even the next century. They can imagine the future state of things in the world. And their imaginings may be more or less veridical based on how well they know how the world works. The better their mental models of the world, the more efficacious their suppositions about what may transpire become.

The trick I introduced in the last section, regarding the copying and modifying of neural representations of systems, allows another wondrous capability. Since our model of the world and how it works is our highest meta-model it seems to have been an easy though incredibly significant step in human evolution to apply the copy-modify and run-the-model trick to that model, or subsystems within it. To imagine the future it is only necessary to copy our model of the world into another neural circuit and then, under the auspices of our prefrontal cortex, adjust the model in certain ways to essentially play, ‘What If’. We can, under conscious or subconscious sapient control, try new things. We can construct hypotheses in mental space and then let the internal dynamics of the model play out in fast time to see what that hypothetical world would be like under those ‘assumptions’

We can, in fact, generate any number of alternative scenarios. Sometimes we do this in a serious vein meaning to try to anticipate what would happen in the real world if we took such-and-such actions right now. At other times we do it for entertainment of affective reward, creating fantasy worlds that we know (if we are sapient enough) are just play things for our amusement. Either way we can generate a seemingly endless number of futures by considering a variation in behavior of ourselves or others, constrained by real world rules (like the laws of nature), and then see where the dynamics lead. Not only can we set up initial conditions and run the model (somewhat analogous to running a computer model) but we can actually interact with the model as it runs changing this or that parameter to ‘guide’ the process if we think it is going astray.

This ability is in every human brain. What makes a difference in terms of its value is how we use the capability. Daydreaming and wishful thinking are necessary refreshments, I imagine, so should not be excluded. But failure to use the facility for thinking seriously about the future is too often the case with lower sapience. Sapience seeks to model the world sufficiently accurately to be useful as a tool in projecting possible futures. It also seeks to manipulate the model for the purpose of finding actions (decisions) that can produce good future outcomes. The world the sapient mind models must be at the largest possible scale and over the longest possible time frame in order to include all that the sapient being cares about (values). The higher the sapience the larger that model.

This is, of course, what we mean by strategic thinking and planning. Our models allow us to play 'what-if' games with the future. And if our future projections include a favorable outcome given we take a particular action now, then it makes sense to do so. All that is necessary is that we have knowledge of causal relations that provide leverage over the way the future unwinds. Sapience involves such a power.

Wise individuals have always concerned themselves with long-term and wide-scale outcomes when making judgments about actions to be taken in the present. Indeed this actually applies to follow-on actions in the future that will need to be taken in order to keep the world moving in the desired direction. Alternatively, the wise also contend with the issue of worlds that are not changeable by any action that can be taken. Sometimes the future is inevitable because the forces in action are overwhelming to human actions. A truly wise person will have a sufficiently efficacious model of the world that they can tell when action is appropriate and when it is not.

Strategic thinking, like moral sentiments, can have a dark side when sapience is unbalanced among its components. Thinking about the future and what might happen if such-and-such is done now is not always done with good intentions. A more Machiavellian person might set plans to establish or keep power over others. And those plans might include coercion and threats of violence as the actions to be taken. So by itself, strategic thinking is not sufficient to constitute a more sapient mind.

We can see now why strong positive moral sentiments are a necessary element in sapience. We don't tend to think of those who plot against others for personal gain of wealth or power as particularly wise people. Indeed one can argue that such plotting really isn't strategic thinking because in the long run evil purposes will result in failure (well we like to believe that good always triumphs in the end). However it is hard to assess a time horizon that matters in human affairs. Is a year a strategic time horizon? Is ten years? What about several generations? The answer is probably all of the above. The major issue in strategic thinking is that it is oriented toward the future, that it involves multiple possible outcomes each with associated likelihoods, and that it focuses on actions to take in the present to improve the odds of a favorable outcome in that future time. But to be sapient the favorableness has to be defined for more than the single individual. The wise elders look to the future for their people, not just themselves. They can see beyond their own deaths to a time when their grandchildren will face the environment on their own. What should we do today to assure those grandchildren have favorable options?

What Are the Functions of Strategic Thinking?

It turns out that many aspects of strategic thinking have been formalized much as aspects of judgment have been formalized under the rubric of decision science. Strategic planning and management have been developed into a model that has been used in the commercial and non-profit organizational world for many years now. Much of the formal model was worked out ages ago for military management. These formal aspects, I assert, reflect what goes on in each of our heads now to some degree or another. In our formal approaches we have simply succeeded in codifying what goes on in strategic planning/management activities in our own thinking and built systems within organizations to carry these functions out.

Strategic control is at the epitome of a system designed to keep an active agent (a person, a tribe, a company, or an army) effectively operating in the context of a dynamic, non-stationary environment. Psychologist David Geary has written an extremely lucid book on the evolution of the mind, integrating neurobiological aspects with behavioral (I will be returning to this reference in the next part). In it he expands on the theory that the human brain evolved as it did to increase the animal's control over its environment. Indeed, he argues that much of human social interaction involves subtle innate strategic interactions between members of the society as they collectively cooperate to tame the biophysical environment, and compete with one another for social influence without it becoming a violent process. The human brain represents the growth in importance of strategic thinking on top of logistic, tactical, and operational thinking (Geary, 2005).

 

Figure 7. Strategic thinking involves monitoring the external world as well as the activities of tactical and logistical thinking/planning/control subsystems. It uses and adapts the world model (the world system from above) to play what-if and generate scenarios. It plans and chooses tactical and logistical commands that will be carried out by those systems. And it monitors the unfolding of events to see if the long-term desired outcomes (achieving goals) are being reached. Not shown, intelligence + creativity (cleverness) is also directed in terms of refining the model as experience is gained.

 

Planning

There are some well-known pieces of strategic planning that you can map to your own approach to your future plans. For example you have to think about your overarching mission in life! Most of us don't have a conscious mission (some zealots think they do) but we all have our biological mandates to survive and procreate. Some people are driven by a need to accumulate material wealth, so they see their mission in terms of making a lot of money. Others just want to muddle through without too much hassle. So many people don't actually make mission-oriented plans even though they are subconsciously driven toward certain end goals. They behave as if they have a mission.

Each of us is constantly rolling out various scenarios about our social lives. What do I need to do to win Mary Jane's (or Billy Bob's) heart? is usually high on the priority list when we are young and/or single. The mission is in place and now I have to consider. Who are my allies? Who are my competitors? What talents and charms do I have? What flaws might I have? What will my competitors do if I exercise this charm, how will they counter? What might my competitor do to exploit my flaws (most of us have difficulty thinking about our own flaws, which is probably a good thing since if we did we might never try to make the score). What goals should I set to take actions on?

These are the kinds of questions each person asks themselves when they are in the courting mode. Similar kinds of questions suit other modes as well. Each of us are forever assessing our situation and our long-term prospects within the social networks to which we belong. Later, when we have a mate and offspring our strategic questions and approaches turn to how we might best position the family for the future. This growth of strategic thinking extends when we have grandchildren. Indeed, a few individuals demonstrate an ability to think strategically for multiple families. The wise elders of years gone by.

And that is what sapient strategic thinking is about. Sapience involves the ability to include many others, including non-relatives, in the circle of others for whom strategic advice might be needed. In sum, sapient strategic thinking poses a future that is the best situation for the most people possible in accordance with good moral sentiments.

Conclusion (So Far)

Sapience is built upon formerly evolved functions such as simple judgment, systems perspective and moral sentiments, primitive versions of which are seen in many mammals and some birds. Strategic perspective and thinking, at least in terms of thinking beyond the immediate future, seems to be a unique function in the genus Homo; I will return to the evolutionary perspective in the final installment.

Wisdom is described as a complex set of psychological functions. Sternberg and others have determined that it is not just intelligence, though it is correlated with intelligence in several important ways (Sternberg, 2003). Wisdom is viewed as a kind of meta-knowledge with a meta-intelligence (and creativity) to process the meta-knowledge. I am suggesting that the model of sapience presented here helps to organize our understanding of the psychological underpinnings of wisdom.

Sapience, like intelligence, is a behavioral and mental construct with identifiable neurological underpinnings. Wisdom, by itself as a psychological construct, is a window into how humans make hard or “wicked-problem” decisions based on a wealth of tacit knowledge. But wisdom seems to require aging — one has to live a long time and aggregate the needed tacit knowledge. Sapience is a native capacity, like intelligence, that makes wisdom possible, just as intelligence makes knowledgeability possible. Whether or not wisdom obtains in an individual will depend at least in part on what kind of world the individual lives in, just as how smart someone becomes depends on how their intelligence is exercised in life. If one lives among similarly sapient and wise elders, then it is possible to see a wise person emerging from a life of learning. On the other hand, just as a potentially smart individual, trapped in a non-stimulating environment, might turn out dull in later life, so too a more sapient person might still turn out foolish if trapped in a foolish environment.

The really big questions that this model raise have to do with how much sapience do ordinary people have relative to what is needed to live successfully in this complex, overcrowded world. That is, how powerful is the computational competence of the brain with respect to sapience? General fluid intelligence is characterized in terms of speed of memory acquisition and recall, working memory capacity and other psychometric measures. Collectively these are attributes that determine how intelligently a person is in problem solving and learning. In a similar fashion I expect there are measures of attributes associated with judgment, moral sentiments, systems modeling, and strategic thinking that collectively constitute sapience level. This model provides a way to generate testable hypotheses with regards to overall decision making competency with respect to complex, uncertain problem domains.

The question of competency level is an important one. In the case of intelligence the definition of the norm is a statistical property of the population. We assign the value of 100 as the intelligence quotient of the average person (the peak of a bell curve). And for the issues in life that intelligence, or cleverness, is good for addressing, this system seems to work pretty well to attribute relative intelligence levels. Since the curve is Gaussian the bulk of people are near the norm and there are jobs for everyone. But with sapience the situation may be different. If it is a newly emerged capability in Homo, as I suspect, then the distribution curve may have a more skewed shape. It may be that the majority of people fall in the lower end of the curve. In the last installment I will explore this possibility more fully. Consider, for now, that such a distribution might well explain the seeming paucity of wisdom in our current societies. That we as a species are in the mess we are in because our cleverness exceeds our wisdom would be a reasonable conjecture.


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