The Flynn effect is now a well-known phenomenon, but it remains entirely unexplained. Defined as the consistently observed and population-wide generational increase in raw intelligence scores, the Flynn effect has drawn a multitude of candidates for its underlying cause—including heterosis, better nutrition, more abundant education, environmental complexity, and various combinations of the above—and yet no candidate offered so far has proven to be either scientifically or logically compelling. Thus the Flynn effect remains one of the great challenges of modern science, or as James Flynn (2007) has described it in his book What is Intelligence?, a series of puzzling paradoxes, paradoxes still in need of definitive resolution.
Often when a phenomenon proves to be this intractable, it is indicative of a misunderstanding of the problem domain itself. Human intelligence has garnered a great deal of study over the past century, including an ever-increasing focus on the neuronal aspects of the activity, leading these days to a nearly universal acceptance that intelligence is to be depicted entirely in terms of brain-based functioning alone. But the irony in this brain-based focus on human intelligence is that it has become the greatest obstacle in achieving an understanding of the Flynn effect. If human intelligence is indeed the equivalent of brain-based functioning, then a significant increase in human intelligence implies a correspondingly significant increase in brain-based ability, a conclusion that nearly everyone wants to accept (almost as a shibboleth), but a conclusion that nags nonetheless, because it stretches biological plausibility. It is the essential mismatch between the biological properties of a brain-based intelligence and the phenomenon of a rapid, inexorable and ubiquitous increase in human intelligence that suggests why progress on the Flynn effect has remained so conspicuously non-existent.
Therefore this essay will not approach the Flynn effect by offering yet another strained explanation for the presumed increase in human brain-based ability, a presumption this essay most adamantly denies. Instead, this essay will approach the Flynn effect by proposing a radical shift in the underlying problem domain, outlining an entirely different view of human intelligence itself, a view encompassing a much broader context than merely an exclusive focus on the human brain. This alternative view of human intelligence will be presented through the mechanisms of a simple model, a model that highlights two orthogonal aspects of human intelligence: 1. environmental intelligence, defined as the total amount of non-biological pattern, structure and form tangibly contained within the human environment, and 2. neuronal intelligence, defined as an individual’s neural capacity to absorb and respond to environmental intelligence. It can be shown that it is environmental intelligence that serves as the sole driver of the Flynn effect, and that neuronal intelligence influences the Flynn effect not at all. It can also be shown that environmental intelligence is similar to but far more comprehensive than the concept known as environmental complexity. And finally, it can be demonstrated that it is this dual-aspect model of human intelligence that effectively resolves all the Flynn effect paradoxes enumerated by James Flynn himself.
Generational gains in raw intelligence scores were first noticed by several individuals—including Reed Tuddenham and Richard Lynn—but it was James Flynn in the 1980s who convincingly revealed the widespread nature of what has come to be known as the Flynn effect, uncovering from data set after data set a persistent rise in human intelligence that seemed to be manifesting everywhere, for everyone, and at all times. In the years since, the Flynn effect has attracted a good deal of study and ink—in large part because the phenomenon has continued to be regarded as surprising, and in large part because the phenomenon has continued to defy adequate explanation.
This unsettled state of affairs stands in stark contrast to several other areas of human intelligence research, including investigations into the source and impact of individual and group intelligence differences. Employing factor analysis, identical twin studies and many other tools of modern cognitive research, scientists have been able to demonstrate frequently and with great consistency that individual intelligence differences produce significant impact on such endeavors as academics and career, and that these individual differences are driven primarily by genetics and are almost certainly neurally based. These discoveries and achievements regarding individual and group intelligence differences, captured eloquently in the concept known as Spearman’s g, stand as one of the great success stories of modern research and have led to a nearly unanimous consensus that intelligence is to be regarded exclusively as a brain-produced, genetically driven activity—in short, intelligence correlates directly to the neural effectiveness of the human brain.
The Flynn effect, however, throws a perplexing monkey wrench into this widely held view. To accept the conclusion that intelligence is exclusively a brain-produced activity, with the effectiveness of that activity determined in large degree by genetics, one must also anticipate that overall human intelligence will remain stable over time. This would be in accordance with all standard biological and evolutionary principles, because nowhere else in nature does one observe an animal species experiencing a rapid generational shift in its biological underpinnings or in its corresponding behavior. Humans have certainly experienced a massive shift in their circumstances over the last several millennia, a shift that has induced certain physical effects—the humans of today are for instance somewhat larger on average than they used to be—but this shift in circumstances should not mislead anyone into believing that humans have biologically transformed since their prehistoric days. The genetic signature of modern Homo sapiens versus ancient Homo sapiens remains fundamentally the same—as is to be expected of any animal species—and if one were to somehow get hold of a kidney for instance from a Cro-Magnon human, it would be utterly shocking to discover that that kidney was somehow different in its physical structure or biological functioning than the kidneys to be found in humans today. It is only with one particular biological organ, the human brain, that it has somehow become commonplace to assume that that organ is mutating dramatically from generation to generation. And indeed if the Flynn effect statistics from the twentieth century are to be believed, then the presumed widespread increase in brain-based ability from generation to generation has now entered the realm of biological miracle—or perhaps to put it a bit more soberly, has now entered the realm of biological magic.
This then is the essential conundrum faced by anyone claiming that human intelligence is exclusively, or even primarily, a brain-based activity. Because either one further accepts that the physical structure and biological functioning of the human brain remains essentially the same today as it was a hundred thousand years ago—which becomes tantamount to a denial of the Flynn effect—or one further accepts that the physical structure and biological functioning of the human brain has been rapidly transforming from generation to generation—which becomes tantamount to a denial of every known tenet of biology and evolution.
A popular means of trying to escape this conundrum is to divorce the Flynn effect entirely from genetics and from evolution, and to look instead for an orthogonal influence on human intelligence that can adequately account for the generational gains in intelligence scores while not trampling upon any biological sensibilities. To put it in the words of James Flynn (1999), it seems as if some unseen hand is propelling scores upwards, and thus the solution to the Flynn effect must lie in the identification of that unseen hand. Furthermore, Richard Lewontin (1976) has already provided a straightforward analogy for how such a mechanism would work, invoking a sack of seed corn full of genetic variability divided randomly into two batches, one planted in soil containing adequate nitrates and the other planted in more barren ground. The individual differences within each batch would remain consistent and would still be attributable to genetic variation, but the overall difference between the two batches would be due solely to the pervasive impact of the nitrates—no tenet of biology or evolution would be violated, and yet the batch-to-batch improvement could still be readily explained. And thus the target of any Flynn effect investigation would seem to be ideally the identification of a real-world, intelligence-boosting equivalent to the role being played by the nitrates.
Nonetheless, such identification has proven to be frustratingly difficult. It has not been because of lack of attempts: advanced education, early education, more widespread education, better nutrition, scientific ethos, video games, television shows with increasingly complex plot lines, more graphical environments, greater exposure to intelligence tests—all these and many similar candidates have been offered as the influence that might be driving intellectual ability ever higher, and yet no candidate offered so far has proven to be even remotely convincing. One major reason for this failure is the utterly pervasive nature of the Flynn effect. Wherever and whenever intelligence scores have been available, the Flynn effect has been evident at every age, for all people, all places and all times, and thus any offered candidate as the influence driving the Flynn effect must of necessity be equally pervasive, a daunting barricade upon which every candidate falls. For instance the Flynn effect has been apparent even when and where education has not been advanced, early or widespread. The Flynn effect was conspicuous even before video games and television shows were a twinkle in anyone’s eye. And the Flynn effect has been evident even when nutrition has been sporadic or poor, and where scientific ethos, graphical environments and intelligence tests have yet to gain much hold. The Flynn effect is literally omnipresent, which is something no offered candidate can manage to be, and the only feeble attempt to address this shortcoming has been to suggest that the influence driving the Flynn effect might consist of some type of combination of the above candidates, along with perhaps several others, a proposal that comes off sounding like less of a solution so much as a concession of defeat.
There is yet a further problem underlying these many attempts to identify an external cause of the Flynn effect, a problem that is less often contemplated but a problem that is ultimately more troubling. Although it is common to divorce the Flynn effect from genetics and from evolution, it is not at all common to divorce the Flynn effect from human physiology, in particular to divorce the Flynn effect from its direct association to the human brain. Each candidate offered as an influence for driving the Flynn effect—be it education, nutrition, or any of the others—each is offered with the tacit understanding that the candidate must be sparking an improvement in human brain-based ability, must be prompting an increase in neural effectiveness. Such an assumption seems only natural—indeed required—since it has become scientific dogma that intelligence is directly correlated with the neural effectiveness of the human brain. But that dogma allows a glossing over of any descriptive mechanism, leaving it entirely unexplained how better nutrition, more education, a video game, etc., could be transforming the workings of cerebral matter. Furthermore, it must be remembered that there already exists a presumed neural mechanism for producing intelligence ability, the one driving individual and group intelligence differences—that mechanism firmly linked to and justified by genetics and evolution. And now alongside this already well-established neural mechanism is theorized yet another, the newcomer much more vague about its justifying mechanics, but just as importantly, absolutely enjoined from any link to genetics and evolution (because remember, the whole motivation behind identifying an orthogonal influence for the Flynn effect was to avoid any trampling on biological sensibilities). Somehow these two distinct mechanisms, emanating from entirely different sources and reliant upon utterly independent means, one driving Spearman’s g and the other driving the Flynn effect, are each supposed to co-exist within the same human skull, each spawning intelligence abilities in its own unique way, and each doing so without interfering in the slightest with the actions of the other. It could only be by way of the dogma, the dogma that insists human intelligence must be directly correlated with the neural effectiveness of the human brain, that scientists can so readily suppress their skepticism and find such easy plausibility in all this theorized neural jumble. Without the dogma, anyone hearing of this brain-based goulash of competing-yet-somehow-cooperating neural mechanisms would think they were being subjected to some kind of madness or joke, because there is nothing in any of this brain-based goulash that resembles either science or logic.
A reasonable alternative would be to drop the dogma altogether. Despite the widespread consensus, there is in fact no direct or conclusive evidence that human intelligence can be explained entirely as a brain-based activity. Although neuroimaging techniques become more powerful with each passing year, and although biometric tools become more sophisticated all the time, and although data and statistical analyses continue to multiply by leaps and bounds, there has yet to appear anything even close to a demonstrated, comprehensive and explanatory link between detailed neural activity and its corresponding intelligence behavior—the workings of the human lobes remain more mystery than established description. Furthermore, with every attempt to link the Flynn effect to genetics, evolution and physiology resulting ultimately in paradox, conundrum and contradiction, it would seem there is adequate motivation to consider the alternative, to consider an influence on human intelligence not associable to the human brain, and to divorce the Flynn effect not just from genetics and evolution, but to divorce it entirely from the human head.
Accordingly, this essay outlines a model of human intelligence that greatly expands the context of that conception, eschewing the notion that intelligence can be adequately described in terms of just brain-based functioning alone. The model describes human intelligence as the combination of two orthogonal components, each essential to intelligence but each acting in an entirely separate domain. One component is called environmental intelligence and is defined as the total amount of non-biological pattern, structure and form tangibly contained within the human environment. It is environmental intelligence that encompasses that aspect of human intelligence that is completely independent of the human brain, and it can be demonstrated that it is environmental intelligence that serves as the sole driver of the Flynn effect. The second component of human intelligence is called neuronal intelligence and is defined as an individual’s neural capacity to absorb and respond to environmental intelligence. Neuronal intelligence is that aspect of human intelligence with which everyone is currently familiar, encompassing as it does all the brain-based elements of intellectual activity. But as its definition states, and quite unlike the common understanding of brain-based intelligence, neuronal intelligence does not capture all the essential features of human intelligence. Instead neuronal intelligence is meaningful only in conjunction with its more substantive counterpart, in conjunction with environmental intelligence, the stimulus to which neuronal intelligence is merely responsive.
The concept of environmental intelligence captures a phenomenon which not that long ago did not exist on this planet, but which these days has become so ubiquitous within the human world it is essentially taken for granted and overlooked. Humans once lived in an entirely natural setting and were once driven solely by biological need—just as is the case with wild animals today—and any pattern, structure or complexity to be found in that prehistoric world would have been provided by nature alone. But human circumstances clearly have changed, especially over the last fifty thousand years or so, and today humans find themselves thoroughly awash in all manner of artificial pattern, structure and complexity, and find themselves interacting continuously with a plethora of man-made constructs, far removed from any purely biological setting. Spoken words, jewelry, automobiles, music, baseball games, books, skyscrapers—to name just a few—all these newly arrived environmental artifacts embody an increasing cornucopia of pattern, symmetry, repetition, logic, structure and form, and these many environmental artifacts convey their embodied concepts not only to the extant human population, they preserve and accumulate those concepts for future generations as well.
To take just one seemingly simple example, a single library book—the symmetry of its external and internal construction, the linear and repetitive patterns running neatly across every page, the hierarchy of encodings beckoning throughout—in considering the form and complexity of a single library book, one quickly becomes overwhelmed by the sheer amount of structured material palpably contained within this seemingly simple example, and yet a single library book scarcely amounts to a single drop in what has become a palpably complex and ever-growing ocean. To do justice to the enormous impact that artifacts such as library books now have upon the human environment, one would need to multiply a book’s structured material across the number of books contained throughout the world, and one would need to augment this total with the totals from all the other categories of artificial entity, and one would need further to boost this sum by the torrent of new constructions being inserted into the human environment each and every day. It is only after contemplating the tremendous volume of this elaborate calculation and it is only after weighing the staggering immensity of its ensuing result that one can begin to grasp both the conception and the definition of the term environmental intelligence, as the total amount of non-biological pattern, structure and form tangibly contained within the human environment.
That this increasing amount of non-biological pattern and structure would play a primary role in human intelligence should not come as a surprise. When observing and judging modern human activity, people frequently make note of the relative ability with which others absorb and respond to the environment’s many artificial constructs—how well does one read a book, solve a math equation, program a machine, play an instrument, decode a map, navigate city blocks—and those who are seen as interacting more productively with these newfangled entities are the ones judged to be more intelligent. Plus this brand of judgment carries over too into that most direct assessment of intelligence, the IQ exam. An IQ exam’s content is composed entirely out of non-biological features and challenges, an IQ exam’s sole purpose is a reckoning of the test-taker’s dexterity with artificial pattern, structure and form. Thus the content of an IQ exam serves as a proxy for the many newfound complexities of the human world, with a strong correlation between those who better master the proxy and those who better master the intricacies of modern living. And it is no coincidence that as the overall amount of pattern and structure continues to expand within the human environment, IQ exams of necessity must be modified to achieve similar transformation.
Artificial pattern and structure also form the boundary of intelligence, they constitute the observable extent of the intelligence domain. The fastest sprinter, the strongest weightlifter, the most prodigious progenitor—these feats are observed and measured by humans too but they are never categorized under the heading of intelligence. Intelligence has strict association with the non-biological, it is marked invariably by the presence of entities not to be found in the natural world. If for instance humans were to visit a distant planet and were to find there a variety of creatures engaged in the type of survival and procreative pursuit consistent with evolution, while finding little of anything else (much as Earth could have been described not that long ago), the visitors would say that although there is indeed life on this distant planet, there are no obvious signs of intelligence. If on the other hand, humans were to visit a planet where there was no biological life at all, and yet there could be seen everywhere an abundance of symmetrical, structured and patterned artifacts reminiscent of the types of constructions to be found on Earth today, the word intelligence would leap immediately to everyone’s lips, and this without the presence of a single neural cell, without the presence of anything resembling a human brain. Environmental intelligence is the tangible emanation of intelligence, it is for all intents and purposes the physical location of intelligence itself. Without environmental intelligence there really could be no discussion of intelligence at all.
Because environmental intelligence is entirely open to observation, it is in theory measurable. This was hinted at in the discussion of the single library book, where quantification of the book’s structured material was broadly contemplated, along with augmentation from the many other sources of structured material contained throughout the human world. But this example also illustrates that although measurement of environmental intelligence is theoretically possible, if one were to actually attempt such a feat it would inevitably degenerate into a pragmatic nightmare. How does one assign a distinct quantity to the pattern of a line of text? How does one supplement this amount by an assessment of the book’s symmetry? And even assuming such non-trivial details could be resolved, there would still be the matter of the calculation quickly becoming unwieldy. Environmental intelligence is literally everywhere, it manifests at every layer of observation. Environmental intelligence has become so pervasive and has expanded to such hierarchical extreme that to assign any type of number to it at all would strain numberdom itself—not to mention human patience. The best that might be offered is an acknowledgement that while in the case of quantifying environmental intelligence the practical difficulties will almost always triumph over theoretical opportunity, it is still possible, using the broadest of strokes, to arrive at meaningful numeric conclusions. For instance, it can still be stated with confidence that environmental intelligence must have measured at absolute zero for quite some time, because it was not that long ago in Earth’s history that there were no artificial features to be found in the environment at all. It can also be stated with confidence that environmental intelligence would have reached a more substantive level by say ten thousand years ago, when civilization was just beginning and humans were at the edge of recorded history. And it can finally be stated with confidence that whatever that ten-thousand-year-ago measure might have been, it would pale in comparison to any statistics that might be gathered today, where the complexity of a single city block would overwhelm any ancient total. The main quantitative conclusion to draw from environmental intelligence is that in recent human history it has been constantly and rapidly on the rise, and thus if one were to go in search of a candidate to match the Flynn effect’s recent meteoric advance, one could do much worse than giving a nod towards the quickly changing dynamics of environmental intelligence.
As foreign as the concept of environmental intelligence might at first seem, the concept of neuronal intelligence by contrast is likely to be more familiar, encompassing as it does that aspect of intelligence to be associated with biology and the human brain. Neuronal intelligence scarcely needs much in the way of introduction, since it has been the subject now of more than a century’s worth of scientific study, study that has produced many definitive and well-publicized results. Neuronal intelligence is measured primarily by relative scores on an IQ exam, neuronal intelligence is quantifiable through the notion of general intelligence or Spearman’s g, neuronal intelligence is determined in large degree by human genetics, and neuronal intelligence is directly correlated to success in such endeavors as academics and career. With the advent of neuroimaging equipment and with the development of many classes of biometric tools, it has become increasingly feasible to observe various types of synaptic behavior and to pair this behavior with actual intelligence events, and although such experiments and analyses remain too crude for any type of detailed or descriptive understanding, the direct association of neural activity with human intelligence has become essentially undeniable. By every indication, neuronal intelligence is marked by an overall neural effectiveness, it is a product of the human neural system, it is a function of the human brain.
Nonetheless, the one thing this essay claims that neuronal intelligence is not, is a sufficient explanation for overall human intelligence. This insufficiency is stated directly in the given definition of neuronal intelligence, as an individual’s neural capacity to absorb and respond to environmental intelligence. This definition, dependent upon another concept, remains entirely consistent with what is broadly known about neural systems, namely that they are mechanisms primarily of biological response, employed always in conjunction with external stimulus. Predator and prey, water and shelter, sexual target and foe—in the wild, whether by evolutionary instinct or through real-time species learning, neural systems are honed to be reactive to their surroundings, with the effectiveness of this reactivity often the determinant factor in matters of life and death. It is only in the supposedly exceptional case of human intelligence that a neural system is commonly assumed to have capacity that goes beyond responsiveness to the external world, it is only in the case of human intelligence that a neural system is assumed to be spontaneously capable of producing behavior heretofore unseen throughout the biological kingdom. This essay strongly rejects such assumptions, reserving for the human neural system only the role to which neural systems have been traditionally assigned, as agents solely of biological response, as reactors dependent upon external stimulus. In this way neuronal intelligence is not called upon to do anything biologically magical, it is not obligated to go beyond what is biologically common and known.
For those claiming however that human intelligence can be understood entirely in terms of brain-based functioning, the biologically magical is far less easy to avoid. The cerebral presence of intelligence itself is difficult enough to account for, given its unprecedented standing in evolutionary history. Add to this the observation that intelligence is significantly increasing with each generation, and the challenge only becomes that more daunting. Finally, consider that every explanation must be strictly confined to the workings inside the human skull, and it is little wonder that the pressure soon becomes irresistible to begin leaning towards the biologically fantastical. Modern explanations of human cerebral activity tend to invoke such notions as brain modules, brain pathways and brain regions, specialized areas of neural circuitry, each devoted to producing particular intelligence effects. One brain module for handling mathematical and logical reasoning, another brain pathway devoted to musical performance, finally an all-powerful brain region primed for linguistic activity. Every intelligence behavior, no matter how modern or how strange, must have its corresponding brain geographical counterpart, because in a system of strictly brain-based functioning it seems no other explanation can do. Unfortunately, these notions of brain module, brain pathway and brain region, despite their apparent necessity, remain entirely hypothetical at best, having never been demonstrated or described in anything resembling sufficient detail. And more disturbingly, one realizes that the Flynn effect imposes a particularly onerous requirement on all these brain-based components, demanding of each module, region and pathway that it undergo physical and functional improvement with each successive generation—an image quite at home in a science fiction movie, but an image that in the real world goes far beyond any known limits of biological and evolutionary plausibility.
The irony is, all these hypothetical brain-based components are entirely unnecessary. By reserving to neuronal intelligence only the traditional role of a neural system—as an agent strictly of biological response—and by assigning instead to environmental intelligence all the physical and expanding complexity that constitutes the hallmark trait of human intelligence, one can thereby untangle every biological and evolutionary concern. The logic of a math equation, the structure of a music performance, the pattern of a linguistic phrase—all these instances of human intelligence do indeed have a corresponding geographical counterpart, but that counterpart exists only in the external world, it does not exist inside the human head. To take just one seemingly simple example, a single library book—the symmetry of its external and internal construction, the linear and repetitive patterns running neatly across every page, the hierarchy of encodings beckoning throughout—nearly all the structural complexity to be associated with linguistic intelligence can be observed directly right there, can be taken in with little more than a glance, is laid out entirely right before one’s very eyes. No neuroimaging equipment is required, no probing by the latest in biometric tools, no need to unlock deeper meanings within synaptic signatures. The structural complexity of human intelligence exists literally and palpably right there within the human environment, and to attempt to double this structural complexity by positing its neural equivalent within the human head would be to engage in nothing more than a redundant endeavor—dubious enough in and of itself, but made even more so by its fundamental conflict with the many tenets of biology and evolution.
Freed of such fantastical notions as enhanced brain modules, brain pathways and brain regions, and having to serve only as an agent of biological reaction (as it has always served), neuronal intelligence is under no obligation to undergo physical or biological change. Thus neuronal intelligence in humans today can be described as being essentially the same as it was in humans from tens of thousands of years ago, the only difference being that neuronal intelligence in humans today finds a great deal more environmental intelligence to which to respond. The rise in human intelligence is therefore not produced by alterations in biological brain-based abilities; the rise in human intelligence is produced instead by alterations in the non-biological human environment. It is environmental intelligence, itself under no biological or evolutionary constraint, that can be transformed at almost any conceivable pace. It is environmental intelligence, moribund for hundreds of millions of years on this planet, that has come to existence within the human world starting not that long ago, and has been rapidly accumulating ever since. And it is this increase in environmental intelligence—not any change or enhancement within the human brain—that can be identified as the sole driver of the Flynn effect.
With these understandings of environmental intelligence and neuronal intelligence, it is now possible to demonstrate how these two orthogonal influences in tandem can account for the salient characteristics of human intelligence, including the notion of a general intelligence captured by Spearman’s g, and including the Flynn effect. Such demonstration can be accomplished through the means of a simple scenario, a scenario in which IQ exams are administered to representative groups of individuals at two distinct points in time, the times separated by several generations. This scenario will be in most respects unremarkable, since its IQ exam statistics will be stated in such a way as to reflect the type of IQ exam data that has been gathered consistently over the past many decades. But in one respect the scenario will be unique, because quite unlike what has been done in the real world, this scenario will give a transparent accounting of environmental intelligence.
To account for environmental intelligence, there are only two assumptions required. One, it must be assumed that the practical difficulties in measuring environmental intelligence can be theoretically overcome; and two, consistent with observation from recent human history, it is assumed that environmental intelligence will always increase between two generationally distinct points in time. These assumptions are actualized in the scenario by saying that humans have developed a scale for quantifying the amount of artificial pattern, structure and form contained within their physical environment, and that this scale is calibrated in something called environmental intelligence units, or EIUs. At Time 1—after measuring the patterns in many lines of text, after reckoning for the symmetry of countless buildings, after calculating the structural impact of thousands of streets and roads (and after assessing a good deal more)—humans have determined that the total amount of non-biological pattern, structure and form contained within this Time 1 environment measures in at 200 environmental intelligence units, or 200 EIUs. Furthermore, when this operation is repeated several generations later at Time 2—after accounting for how the means of communication have become more elaborate and widespread, after determining that the now larger architectural edifices have become more suffused with intricate supportive systems, after providing for how the modes of transportation have become much faster and greater ranging (and after assessing a good deal more)—humans have determined that the total amount of non-biological pattern, structure and form contained within this Time 2 environment now measures in at 400 EIUs. These numbers and units of measure are of course entirely arbitrary and serve only illustrative purpose, but it needs to be realized that the numbers and units are not of themselves essential to the demonstration. All that is required for the scenario is a means of quantification for environmental intelligence, along with an assurance that environmental intelligence will always increase over time.
The scenario begins at Time 1, where as has been stated environmental intelligence measures in at 200 EIUs. At Time 1, a standard battery of intelligence tests is administered to a broad sampling from the general population, and as is done with real-world intelligence exams, the raw scores are then normed and classified by rank. The essential characteristics of this process can be summarized by examining the results from just three individuals—call them A1, B1 and C1—individuals who represent respectively normed results that have been categorized as high intelligence, medium intelligence and low intelligence. The raw intelligence scores of these three individuals can be stated as the percentage of test questions each has answered correctly: for instance, before norming and ranking take place, it is noted that A1 has answered 80% of the test questions correctly, B1 has answered 70% correctly, and C1 60%. The results of all these Time 1 environmental and individual intelligence measures can be summarized by the following chart:
|Raw Test Score||Normed Population Rank|
From the normed results alone, standard research analysis regarding individual intelligence differences is performed in the usual manner, leading to the types of findings that have been categorized previously under the heading of neuronal intelligence. Employing factor analysis and incorporating an assortment of statistical and biological data gathered from the general population, scientists demonstrate with considerable confidence that, all other things being equal, A1 can expect greater success than his B1 and C1 peers in such areas as academics and career, and that the individual intelligence differences between A1, B1 and C1 can be attributed in large degree to their genetic background, and that these performance differences are largely quantifiable under the statistic of Spearman’s g and reflect corresponding levels of overall neural effectiveness. As has been stated, this particular aspect of the scenario is entirely unremarkable, since it reflects the type of research and outcomes that have been consistently presented by intelligence researchers throughout the course of many years. Nonetheless, it should be noted that these findings are based entirely on relative rankings—the raw test scores do not come into play here, and there is no attempt to derive an absolute measure of intelligence. When it comes to determining the characteristics of neuronal intelligence, relative performance at a particular point in time is entirely sufficient to achieve nearly every meaningful result.
This does raise the question however of whether one can seek for an absolute measure of intelligence in addition to the universally employed relative rankings, and in this scenario, where environmental intelligence has been adequately accounted for, an absolute measure of intelligence is indeed viable. Recall that the raw intelligence scores of A1, B1 and C1 have been stated as the percentage of test questions each has successfully answered—80% for A1, 70% for B1, and 60% for C1—and this suggests that the raw intelligence scores of these three individuals could alternatively be stated as a percentage of environmental intelligence each has successfully mastered. This latter approach derives from the recognition that the content of an intelligence exam serves as a proxy for the artificial and structural complexity to be found in the human world, and thus serves as a proxy for environmental intelligence. If for instance the standard battery of intelligence tests being administered to this population could be described as a perfect proxy for environmental intelligence, then A1, by answering 80% of the test questions correctly, would be demonstrating a mastery of 80% of the environmental intelligence to be found in the everyday world. B1 and C1 would be respectively demonstrating a mastery of 70% and 60% of environmental intelligence. In reality, probably no intelligence exam can serve as a perfect proxy for environmental intelligence, and thus a factor of adjustment would be needed to account for any discrepancy, but in the interest of keeping the calculations simple, there is no harm in assuming that this particular battery of intelligence tests, in its totality, is a near perfect proxy for environmental intelligence—the assumption impacts only the calculated number, it does not disturb any of the resulting analysis.
Recognizing that the raw scores on an intelligence exam provide a direct link to environmental intelligence, and taking advantage of the fact that in this scenario environmental intelligence has been measured and quantified, it is now possible to provide an absolute intelligence score for each of the studied individuals. For A1, who has answered 80% of the test questions correctly—and with the battery of tests assumed to be a perfect proxy for environmental intelligence, and with the level of Time 1 environmental intelligence measured at 200 EIUs—A1’s absolute intelligence score is calculated to be 160 EIUs, the result of multiplying 200 EIUs by 80%. For B1, the calculation produces an absolute intelligence score of 140 EIUs (200 EIUs x 70%), and for C1, the calculation results in an absolute intelligence score of 120 EIUs (200 EIUs x 60%). These results can be incorporated into the summarizing chart:
|Raw Test Score||Normed Population Rank||Absolute Intelligence Score|
|A1||80%||High Intelligence||160 EIUs|
|B1||70%||Medium Intelligence||140 EIUs|
|C1||60%||Low Intelligence||120 EIUs|
What might seem strange about this effort to derive an absolute intelligence score is that at Time 1 it will make no difference whatsoever. If researchers were to make use of the absolute intelligence scores instead of the relative rankings, they would still arrive at all the same conclusions. Intelligence differences would still be attributable to genetic causes, there would still be the same correlative success with academics and career, and Spearman’s g would still emerge. Thus it might seem that the calculation of an absolute intelligence score is of no scientific value at all, is little more than a waste of time and effort. But such a conclusion would be premature. An absolute intelligence score does indeed contain valuable information—perhaps the most valuable information of all—but this information does not become apparent until the entire operation is repeated, is repeated several generations later at Time 2.
At Time 2, where environmental intelligence has been measured at 400 EIUs, the standard battery of intelligence tests is again administered to a broad sampling from the general population, and as was done at Time 1, the raw scores are then normed and classified by rank. A1, B1 and C1 are of course no longer part of the extant population, but the Time 2 results suggest that they have been equivalently replaced by three similar individuals—call them A2, B2 and C2—individuals who continue to represent normed results that have been categorized as high intelligence, medium intelligence and low intelligence. Indeed so similar are these three individuals to their Time 1 counterparts that their raw intelligence scores—that is, the percentage of test questions each has answered correctly—turn out to be exactly the same. A2 has answered 80% of the test questions correctly, B2 has answered 70% correctly, and C2 60%. The results of these Time 2 environmental and individual intelligence measures can be summarized by the following chart:
|Raw Test Score||Normed Population Rank|
Once again from the normed results alone, standard research analysis regarding individual intelligence differences is performed in the usual manner, leading once again to the types of findings that can be categorized under the heading of neuronal intelligence. And quite notably, all the Time 2 conclusions remain exactly the same as the Time 1 conclusions. Scientists can still demonstrate with considerable confidence that, all other things being equal, A2 can expect greater success than his B2 and C2 peers in such areas as academics and career, and that the individual intelligence differences between A2, B2 and C2 can be attributed in large degree to their genetic background, and that these performance differences are largely quantifiable under the statistic of Spearman’s g and reflect corresponding levels of overall neural effectiveness. The steadfast similarity in these findings from Time 1 to Time 2 strongly suggests that the characteristics classified under the heading of neuronal intelligence remain absolutely stable over time, just as might be expected of a phenomenon heavily steeped in physiology, genetics and evolution. And indeed if this is all there were to say about the Time 2 findings—if the findings could be limited to just the domain of neuronal intelligence—then the proponents of a brain-based intelligence would now find themselves very much at ease, for there is nothing in any of these Time 2 findings as stated so far that would be at odds with the tenets of biology and evolution.
However that is not all there is to say about the Time 2 findings. Because just as has been taking place in the real world, this scenario has experienced a significant anomaly.
The anomaly has first appeared within the battery of tests. The initial tests offered to the Time 2 population were the exact same tests administered to the Time 1 population, but as it has turned out, the Time 2 population has found nearly all the Time 1 questions to be exceptionally easy. Few individuals score below 70% on the original tests, and the large majority of the Time 2 population manages to score well above 85%. With the scores so bunched together and bumping against the performance ceiling, the original exams are no longer serviceable for determining relative rankings within the population. Scientists discover that they need to alter the exams—by beefing up the questions to contain greater complexity, by including topics recently introduced into the human world, and by suffusing the exams’ content more generally with a greater amount of pattern, structure and form—and it is only after the scientists have made these alterations that the relative rankings similar to those evinced by the Time 1 population can begin to re-emerge. Thus the results presented above for the Time 2 population are not the results against the Time 1 battery of tests, they are instead the results against a much different battery of tests, tests that are in a very real and observable sense more challenging and more complex.
In one sense, the incorporation of this anomaly into the scenario is being driven by a desire to mimic happenings from the real world, where intelligence exams have been undergoing exactly the type of alteration as described above. But in a more compelling sense, the anomaly is being incorporated into the scenario because the very conditions of the scenario demand its inclusion. Recall that the contents of an intelligence exam serve as a proxy for environmental intelligence, and in this scenario environmental intelligence has significantly increased—doubled in fact—from Time 1 to Time 2. If the Time 1 battery of tests are serving as a perfect proxy for Time 1 environmental intelligence, then of necessity that same battery of tests cannot serve as an adequate proxy for Time 2 environmental intelligence. The beefing up of the questions’ complexity, the addition of topics recently introduced into the human world, the inclusion of a greater amount of pattern, structure and form—all these changes are absolutely essential in order for the content of the Time 2 battery of tests to be a more accurate reflection of Time 2 environmental intelligence.
In many respects, this analysis reveals how the content of an intelligence exam serves as the linchpin for an understanding of human intelligence, and in particular for an understanding of the Flynn effect. It has been too common within the scientific literature to overlook the importance of the content of intelligence exams, and it has been too common within the scientific literature to treat the changing nature of intelligence exams as little more than a trivial side effect—somewhere between an annoyance and a curiosity—but these assessments are extremely short-sighted. The fact that intelligence exams must be regularly altered, and altered in a particular way, is perhaps the most important piece of information there is regarding the nature of human intelligence. It indicates that intelligence exams of necessity must reflect the structural nature of the external world, and it indicates that the structural nature of the external world is in a constant state of accumulation, and it indicates that this constant state of accumulation is playing a fundamental role in determining overall human intelligence. Consider what the content of an intelligence exam would have been like if presented in Mesopotamia around five thousand years ago. With language much simpler than it is today (and nearly always spoken), and with mathematics virtually non-existent, and with only a handful of abodes of just the simplest construction, the contents of an IQ exam from that era would of necessity been practically childlike compared to the exams offered today, and yet the majority of the Mesopotamian population would have found such “childlike” exams to be extremely challenging. By five hundred years ago, with language now more elaborate and transmitted in a greater variety of forms, and with basic arithmetic more well known and its impact more suffused throughout the surroundings, and with edifices reaching the height and breadth of Gothic cathedrals, the content of a sixteenth-century intelligence exam would have been far more complex than possible in ancient Mesopotamia; while on the other hand, with modes of transportation almost entirely non-mechanical, and with science and logic still in their infancy, and with electronic communication not even yet a dream, the content of a sixteenth-century intelligence exam would have been utterly simplistic compared to what is offered in exams today, and yet the sixteenth-century population would have still found those “simplistic” exams to be extremely challenging. The content of an intelligence exam must change over time because that content is a reflection of the structural complexity of the surrounding world, a structural complexity that in recent human history has been always increasing.
The impact of the anomaly becomes apparent also when comparing absolute intelligence scores. As was done at Time 1, it is now possible to calculate absolute intelligence scores for each of the Time 2 individuals, and for A2, who has answered 80% of the Time 2 questions correctly—and with the Time 2 battery of tests assumed to be a perfect proxy for Time 2 environmental intelligence, and with the level of Time 2 environmental intelligence measured at 400 EIUs—A2’s absolute intelligence score is calculated to be 320 EIUs, the result of multiplying 400 EIUs by 80%. For B2, the calculation produces an absolute intelligence score of 280 EIUs (400 EIUs x 70%), and for C2, the calculation results in an absolute intelligence score of 240 EIUs (400 EIUs x 60%). In each case, these scores reflect a twofold increase over the absolute intelligence score of the equivalent Time 1 individual. In each case, these scores reflect a twofold increase in the amount of demonstrated intelligence. The results can be incorporated into the summarizing chart:
|Raw Test Score||Normed Population Rank||Absolute Intelligence Score|
|A2||80%||High Intelligence||320 EIUs|
|B2||70%||Medium Intelligence||280 EIUs|
|C2||60%||Low Intelligence||240 EIUs|
A comparison of the above chart with its Time 1 equivalent reveals that variation in human intelligence needs to be understood across two separate and independent domains. For the characteristics associated with neuronal intelligence—characteristics that find their basis in physiology, genetics and evolution—there is variation across the population but there is stability over time. For the characteristics associated with environmental intelligence—characteristics that find their literal home within the human surroundings—there is stability across the population but there is variation over time.
If the statement is offered suggesting that the Time 2 individuals are more intelligent than their Time 1 ancestors, it can be seen that there is inherent ambiguity in that statement. In the context of neuronal intelligence, referring to human neural capacity, the Time 2 individuals on average evince exactly the same level of neural capacity as do their Time 1 ancestors. But in the context of environmental intelligence, referring to the types and amounts of intelligence actually demonstrated, the Time 2 individuals, in a very real and observable sense, demonstrate a significantly greater level of intelligence than do their Time 1 counterparts. These assessments are not contradictory. They simply reveal the dual-aspect nature of human intelligence. Human intelligence is composed fundamentally of both neuronal intelligence and environmental intelligence, and it is only after these two orthogonal influences are both taken fully into account that the characteristics of human intelligence can be fully understood, including the notion of a general intelligence captured by Spearman’s g, and including the Flynn effect.
In his book What is Intelligence?, James Flynn outlines four paradoxes he associates with the Flynn effect—the intelligence paradox, the mental retardation paradox, the identical twins paradox, and the factor analysis paradox. But seen in the light of both neuronal intelligence and environmental intelligence, it becomes apparent that what Flynn is describing are not really paradoxes at all. Instead, what Flynn is describing are unjustified conflations of neuronal intelligence and environmental intelligence, conflations motivated by the scientific dogma that everything associated with human intelligence must be invariably linked to the human brain.
Two of the paradoxes—the ones labeled the intelligence paradox and the mental retardation paradox—state the apparent incongruity that if the Flynn effect were literally true, then humans from one generation would be too implausibly dumb or too implausibly smart compared to humans from a different generation. In Flynn’s words:
“If huge IQ gains are intelligence gains, why are we not struck by the extraordinary subtlety of our children’s conversation? Why do we not have to make allowances for the limitations of our parents? A difference of some 18 points in Full Scale IQ over two generations ought to be highly visible.
“If we project IQ gains back to 1900, the average IQ scored against current norms was somewhere between 50 and 70. If IQ gains are in any sense real, we are driven to the absurd conclusion that a majority of our ancestors were mentally retarded.”
The resolution to these two paradoxes is to recognize that Flynn is confusing the two different components of human intelligence; he is confusing environmental intelligence with neuronal intelligence. In particular, he is using the changed levels in one component (environmental intelligence) to infer a corresponding change in the other component (neuronal intelligence). That inference is entirely unwarranted.
Consider the individual named A1 in the scenario. At Time 1, A1 is assessed to be highly intelligent. He demonstrates an above-average ability to absorb and respond to environmental intelligence by correctly answering 80% of the test questions presented to him, and as A1 adroitly navigates through his Time 1 world, it can be anticipated he will experience relatively greater achievement in such areas as academics and career compared for instance to his B1 and C1 peers. But when A1’s absolute (raw) intelligence score of 160 EIUs is compared to the population of Time 2, A1 suddenly appears to be much less smart. 160 EIUs scores well below the 240 EIUs of C2, a person assessed to be of low intelligence at Time 2. If 240 EIUs is considered to be of low intelligence at Time 2, then A1’s score of 160 EIUs seems to mark him as a borderline imbecile.
So which is it? Is A1 highly intelligent or is he an imbecile? This paradox is resolved by recognizing that A1’s neuronal intelligence is not subject to change. A1’s absolute intelligence score of 160 EIUs has as much to do with the time period during which it was registered as it has to do with A1’s biological capacity. If A1 could be magically transported forward in time and raised in the Time 2 world, he would absorb and respond to about 80% of the Time 2 environmental intelligence and would score correspondingly on a Time 2 intelligence exam, making it clear once again that he is a highly intelligent individual. A1’s apparently low score of 160 EIUs has nothing to do with A1’s neural capacity; it has everything to do with the change in environmental intelligence from Time 1 to Time 2.
This works exactly the same way going backwards in time. Consider C2, who is assessed at Time 2 to be of low intelligence. But when C2’s absolute (raw) intelligence score of 240 EIUs is compared to the Time 1 population, where a score of 160 EIUs is considered to be highly intelligent, C2 suddenly comes across as a Mensa candidate, and one wonders if C2 simply had the misfortune of being born too late.
So which is it? Is C2 of low intelligence or is he a Mensa candidate? Once again, the resolution is to recognize that C2’s neuronal intelligence is not subject to change. If C2 could be magically transported back in time and raised in the Time 1 world, he would absorb only about 60% of the Time 1 environmental intelligence and would score relatively poorly on the Time 1 intelligence exam. The timing of one’s birth does not alter one’s personal intellectual ability.
In addition to these examples from the scenario, Flynn provides a real-world occurrence that brings out both the paradox and its resolution in the most enlightening of ways. After noting that the average raw intelligence score from around the year 1900 would translate to an IQ of about 50 to 70 on today’s scale, Flynn raises the specter of the following tableau:
“Jensen relates an interview with a young man with a Wechsler IQ of 75. Despite the fact that he attended baseball games frequently, he was vague about the rules, did not know how many players were on a team, could not name the teams his home team played, and could not name any of the most famous players.
“When Americans attended baseball games a century ago, were almost half of them too dull to follow the game or use a scorecard? My father who was born in 1885 taught me to keep score and spoke as if this was something virtually everyone did when he was a boy. How did Englishmen play cricket in 1900? Taking their mean IQ at face value, most of them would need a minder to position them in the field, tell them when to bat, and tell them when the innings was over.”
This is a quintessential example of mistaking a change in raw intelligence scores as the evidence of a change in neuronal intelligence, when in fact it is only the evidence of a change in environmental intelligence. Think about incorporating questions dealing with baseball rules into an intelligence exam. If such questions had appeared on an exam in say the year 1800, no one at all, including the smartest people who then lived, would have been able to answer such questions correctly (other than by random luck). By contrast, if such questions were to appear on today’s intelligence exams, many individuals, including those of low-to-average intelligence, would be able to answer such questions correctly—baseball and its rules have become an established part of the human environment, their widespread presence and influence are now thoroughly encountered and absorbed by a large percentage of the population. As Flynn indicates, it would be only those with an IQ of around 75 or under who would have limited potential to answer such questions correctly.
So does any of this mean that the smartest people from the year 1800 had the same intellectual capacity as Jensen’s young man? It of course does not mean that at all.
The critical moment in time would have been around the year 1900. If questions regarding baseball rules had appeared on intelligence exams at that time, the results would have been decidedly mixed. Some people would have been able to answer such questions correctly, but many others would not, including those of otherwise average-to-high intelligence, and this only because baseball had not yet become widely entrenched within the human environment (it was just then catching on). But after the exam was finished, if one of those baseball-ignorant, question-misanswering persons of average-to-high intelligence had been taken to the ballpark, bought a ticket, sat with in the grandstands, explained the rules, given a scorecard and a pencil, a perfectly capable set of behaviors would have swiftly emerged. After all, this is a person of average-to-high intelligence, this person can absorb and respond to baseball rules just fine, they will give this person not the slightest bit of trouble. And around the year 1900, this scene would have actually been taking place, again and again and again—an example of additional pattern, structure and form being inserted into the human environment, an example of an increasing amount of environmental intelligence. And should a scientist of that era have found the need to add something new to the standard battery of intelligence tests—something that would have helped make the questions more challenging and more discerning than the now too easy nineteenth-century exams—the inclusion of a few baseball-inspired problems might have neatly done the trick.
The widespread increase in raw intelligence scores from 1900 to 2000 has everything to do with the increasing amount of environmental intelligence (including the addition of baseball rules). It has nothing to do with individual neural abilities. It has nothing to do with neuronal intelligence.
Another Flynn paradox is the one called the identical twins paradox. Flynn’s words again:
“There is no doubt that twins separated at birth, and raised apart, have very similar IQs, presumably because of their identical genes. Indeed a wide range of studies show that genes dominate individual differences in IQ and that environment is feeble. And yet, IQ gains are so great as to signal the existence of environmental factors of enormous potency. How can environment be both so feeble and so potent?”
The short answer to Flynn’s question is to say that environment, despite Flynn’s doubts, is indeed both feeble and potent. It is feeble when considering individual and group intelligence differences that manifest across the population—the domain in which neurology and genetics hold sway. And environment is potent when considering intelligence differences that manifest across time—the domain in which neurology and genetics possess no influence at all. But although this short answer does manage to resolve the paradox precisely, it does not address what is actually at issue here—namely why does Flynn think this is a paradox.
There are several different analogies one might use to illustrate this essay’s dual-component model of human intelligence with its orthogonal influences of neuronal intelligence and environmental intelligence. For instance, Lewontin’s example of the batches of seed corn would do quite well. Also, one might think of the heights of ships floating in a harbor, heights that differ from one another because of each ship’s inherent characteristics (individual differences at a particular moment in time) and yet that can also deviate in toto because of the rising and falling tide (an environmental influence across time). Flynn of course would not find either Lewontin’s example of the seed corn or the example of the rising and falling ships to be paradoxical, and yet when that exact same mechanism is suggested for human intelligence he seems to find himself in total disbelief. The question is why.
Flynn’s disbelief arises from an ingrained assumption common to nearly every intelligence researcher—each has become entirely convinced that every intelligence characteristic, every intelligence difference, must be ultimately portrayed as a neural characteristic, as a neural difference. In other words, if an influence has no tangible impact upon the human brain, then it cannot be an influence associated with human intelligence. Thus when Flynn considers environmental forces, which he can see full well have the perfect potential for explaining the Flynn effect, he stops short when he does not see how those environmental forces can cause the supposedly requisite change in human genetics or human neurology. This would be the equivalent of Flynn stopping short because he does not see how the nitrates in the soil can impact the seed corn’s genetic structure, or stopping short because he does not see how the water level in the harbor can alter the ships’ physical characteristics. Flynn does not make this mistake when considering the seed corn or the ships in the harbor because he understands that the actions of the nitrates are orthogonal to the seed corn’s genetics, and he understands that the water level in the harbor is independent of each ship’s physical characteristics. But in the field of human intelligence, where it has become dogma that every influence must ultimately deliver its impact within the folds of the human brain, Flynn cannot countenance this kind of orthogonality, cannot countenance any degree of independence.
And yet that countenance is all that is required. When one drops the dogma that everything associated with human intelligence must be invariably linked to the human brain, and when one correspondingly accepts the orthogonal relationship between neuronal intelligence and environmental intelligence, then the supposed conflict between biological and environmental forces quickly loses its bite, and the dilemma of the identical twins paradox swiftly disappears.
The remaining Flynn paradox is the factor analysis paradox:
“How can intelligence be both one and many at the same time or how can IQ gains be so contemptuous of g loadings? How can people get more intelligent and have no larger vocabularies, no larger stores of general information, no greater ability to solve arithmetical problems?”
The first question in Flynn’s statement can be answered in the most straightforward of ways: IQ gains across time can be so contemptuous of g loadings because IQ gains across time have absolutely nothing to do with neuronal intelligence, and therefore have absolutely nothing to do with Spearman’s g. In fact, contemptuous may not be the right word for it; utter indifference would more precisely capture the relationship.
The second question in Flynn’s statement—why are intelligence gains differential across various aspects of intelligence—that question is more intriguing and allows for a deeper investigation into the characteristics of environmental intelligence. In this essay so far, and with the intent of keeping the discussion basic, environmental intelligence has always been taken as a whole, with an emphasis on the principle that taken as a whole, environmental intelligence is always increasing over time. But when environmental intelligence is examined under its various aspects, it can be seen that within these aspects varying rates of increase can frequently occur. Flynn’s example of arithmetic provides a case in point. By the time the first intelligence exams were being administered in the early 1900s, arithmetic was already a well-established and deeply plumbed subject, and its impact had already become widely infused into the human surroundings. Thus there would be only minimal gains in arithmetical knowledge and influence throughout the twentieth century, a fact reflected in the corresponding minimal gains in arithmetic-based intelligence scores. But this would not have always been the case. As was noted previously, if there had been intelligence exams in Mesopotamia around five thousand years ago, arithmetic would have scarcely made an appearance, since much of the subject was still unknown; and yet at some point in human history, arithmetic must have become more deeply and widely established, infiltrating both the environment and the population, and if intelligence exams had been available during that period, the corresponding rapid increase in arithmetical ability would have been quite conspicuous. During this past century, while changes in vocabulary, general information and arithmetic have remained relatively quiet, rapid advances in electronic communication and modes of transportation have been producing tremendous amounts of embodied graphical structure and logical formulation into the human environment, leading to corresponding surges in associated intelligence scores. Thus the overall increase in environmental intelligence remains inexorable, even if the pace across its various components remains not entirely uniform.
Plus Flynn’s concern regarding the differing rates of intelligence gain seems to be mostly a neural concern—otherwise why attempt to tie it to Spearman’s g. But as noted already, intelligence gains are not produced by changing neural abilities. Intelligence gains require something that is far more malleable, something that can indeed be altered at differing rates and in differing ways. Intelligence gains require something with the characteristics of environmental intelligence.
Of the many theories that have been proposed to explain the Flynn effect, the one most similar to the model being presented here is the notion that gains are being driven by an increased exposure to environmental and social complexity. Schooler (1998) and Greenfield (1998) provide introductions to the subject, and in general it is not uncommon to hear it suggested that everything from urbanization to the widespread use of such items as puzzles, graphics and games must have something to do with the increased levels of human intelligence. These suggestions are certainly on the right track, but when they are examined in detail it can be seen that in at least two crucial respects their ability to account for the Flynn effect remains ultimately inadequate.
The first difficulty with these proposed notions of increased exposure to environmental and social complexity is that their proponents tend to focus on certain things within the environment, and miss the impact of the environment as a whole. For instance, two commonly touted examples of the type of environmental complexity that can lead to increased human intelligence are the widespread use of video games and the growing complexity and multivariate plot lines in television shows and movies. Others will highlight the expanded task demands that have come with increased urbanization, and some might point to the denser presence of visual symbols and graphical puzzles within everyday life. But no matter what thing or set of things is being proposed, it quickly becomes clear that these items by themselves cannot account for the ubiquitous and inexorable reach of the Flynn effect. The Flynn effect was working its magic long before there even were video games and television sets, and the Flynn effect remains prominent in locations where visual symbols and graphical puzzles have yet to take much hold, and the Flynn effect can even be noticed in rural as well as urban communities. Of course other instances of environmental and social complexity might be offered up instead, but inevitably each instance must fall victim to the shortcoming of having only limited spatial and temporal reach. The Flynn effect is a population-wide and time-persistent phenomenon, and so any explanation must have population-wide and time-persistent effect. A specific instance of environmental and social complexity will never fit that bill.
The second difficulty with the proposed notions of increased exposure to environmental and social complexity is that their proponents, like nearly everyone else, insist on tying these explanations to human neurology. Playing video games for instance might be characterized as expanding the capacity of working memory. Modern movie plots will be described as spawning a larger number of parallel connections within the logical neural circuitry. The increased task demands of urbanization are embraced as a type of ongoing cerebral training. It would seem that complexity by itself is rather useless, that its only real purpose is to prompt a restructuring within the neurons, to spark a rewiring between the ears. Such ideas run amok within modern science, but they lack parsimoniousness and plausibility, begging plasticity miracles within the confines of the human head.
This essay’s description of environmental intelligence, while similar to the notions of increased exposure to environmental and social complexity, avoids the shortcomings of those notions by incorporating two significant improvements. First, environmental intelligence embraces a more comprehensive context than do the notions of environmental and social complexity, comprehensive enough to have population-wide and time-persistent impact, eschewing the focus on particular things within the human environment and incorporating instead nothing short of the total amount of non-biological pattern, structure and form tangibly contained within the human environment. Second, environmental intelligence, unlike the proposed notions of increased exposure to environmental and social complexity, severs the tie to human neurology, allowing environmental intelligence to accumulate without biological restriction, and without having to make resort to biological miracle.
One consequence that should be readily apparent from this essay’s dual-component model of human intelligence is that the Flynn effect cannot be regarded as just a recent phenomenon. Tracking the historical increase in environmental intelligence, the Flynn effect will have begun near the time of the human great leap forward and will have been shadowing human existence ever since. And there is no reason to expect the Flynn effect will end anytime soon.
This essay has presented a new description of human intelligence, a description that retains the commonly accepted brain-based understandings, but a description that augments those understandings with an equally essential partner, with environmental intelligence, the total amount of non-biological pattern, structure and form tangibly contained within the human environment. This equally essential partner greatly expands the context of human intelligence and frees human intelligence from the confines of the human brain. Environmental intelligence places the structural complexity that is the hallmark trait of human intelligence into a far more observable domain, and it is the changing characteristic of that domain, the accumulating amount of artificial pattern, structure and form, that provides the most straightforward and non-paradoxical explanation of the Flynn effect. It is environmental intelligence that serves as the Flynn effect’s unseen hand.
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