Illuminating Major Creative Innovators with the Model of Hierarchical Complexity

Michael Lamport Commons and Linda Marie Bresette^[1]

The development and improvement of a society and its culture depend on major scientific innovations. Societies with higher rates of major innovation generally provide better quality of life for their citizens. Over the long run, societies with the largest number of innovations will tend to dominate the world's economic scene. Still it is only an extremely small number of people who make such innovations. This chapter offers at least four cardinal reasons for why this is so. The major reasons posited for the shortage of scientific innovators are as follows: a lack of development of extremely complex thinking required to identify phenomenon and create and integrate paradigms, necessary personalities, sufficient education, and appropriate cultural conditions that support innovation.

CREATIVE INNOVATIVE CULTURAL CONTRIBUTIONS

Minimally, creativity must be original action. The methods, theories and techniques do not have to be original, only the manner in which they are used. In addition, creative acts become social memes of long standing (Dawkins, 1976, 1981; Feldman, 1980; Feldman, Csikszentmihalyi & Gardner, 1994). In a metaphorical sense, memes are to cultural evolution what genes are to evolutionary biology. Genes are the basic biological units of information that are transmitted from one individual to another in the form of DNA. Memes are the basic cultural units of information that are transmitted to other people in the form of behavioral patterns. In the course of positive adult development, major innovations are new memes that are extreme examples of generativity (Erikson, 1959, 1978). Some generative acts are not only important to ourselves but are useful to society as well. Innovative generative acts can lead to something new in society.

We approach this matter of creativity—of creative innovation—from the perspective of the Model of Hierarchical Complexity (MHC). The MHC of Commons and Richards (1984a, 1984b; Commons, Trudeau, Stein, Richards, & Krause, 1998) is a system that classifies development in terms of a task-required hierarchical organization of required response. The model was derived in part from Piaget's (Inhelder & Piaget, 1954, 1958) notion that the higher-stage actions coordinate lower stage actions by organizing them into a new, more hierarchically complex pattern. The stage of an action is found by answering the following two questions: a) What are the organizing actions? b) What are the stages of the elements being organized?

THE MODEL OF HIERARCHICAL COMPLEXITY

The Model of Hierarchical Complexity

The Model of Hierarchical Complexity (MHC) (Commons & Richards, 1984a, 1984b; Commons, Trudeau et al., 1998) is universal system that classifies the task-required hierarchical organization of “ideal” responses. Every task contains a multitude of subtasks (Campbell & Richie, 1983; Overton, 1990). When the subtasks are completed by the ideal actions in a required order, they complete the task in question. The classification does not depend on the content or context, so it is species, domain and cultural free. Tasks vary in complexity in two ways, either as horizontal (involving classical information), or as vertical (involving hierarchical information).

Horizontal (Classical Information) Complexity

Classical information describes the number of “yes-no” questions it takes to do a task. For example, if one asked a person across the room whether a penny came up heads when they flipped it, their saying “heads” would transmit one bit of “horizontal” information. If there were two pennies, one would have to ask at least two questions, one about each penny. Hence, each additional one-bit question would add another bit. Let us say they had a four-faced top with the faces numbered one, two, three, or four. Instead of spinning it, they tossed it against a backboard as one does with dice in a game. Again, there would be two bits. One could ask them whether the face had an even number. If it did, one would then ask if it were a two. Horizontal complexity, then, is the sum of bits required to complete a such tasks.

Vertical (Hierarchical) Complexity

Specifically, hierarchical complexity refers to the number of recursive times that the co-ordinating actions must perform on a set of primary elements. Actions at a higher order of hierarchical complexity: a) are defined in terms of actions at the next lower order of hierarchical complexity; b) organize and transform the lower-order actions; c) produce organizations of lower-order actions that are new and not arbitrary, and cannot be accomplished by those lower-order actions alone. Once these conditions have been met, we say the higher-order action co-ordinates the actions of the next lower order. Stage of performance is defined as the highest-order of hierarchical complexity of the task solved. Commons (Commons, Goodheart, and Dawson, 1997, March; Commons, Richards, Trudeau, Goodheart, & Dawson, 1997, March) found, using Rasch (1980) analysis, that hierarchical complexity of a given task predicts stage of a performance, the correlation being r = .92 (hierarchical complexity of the task that is completed).

Formulating the Postformal Orders of Hierarchical Complexity

Commons (Commons & Richards, 1978; Commons, Richards & Kuhn, 1982; (Commons, Trudeau, et al, 1998) showed that the postformal stages were true hard stages in the Kohlberg and Armon (1984) sense, but with some small modification. As Marchand (2001) summarizes, Kohlberg and Armon distinguish "hard" stages (in which development occurs in an invariant and universal sequence, e.g., the Piagetian stages) from "soft" stages (in which development is conditioned by particular experiences arising from differences in personality, upbringing, social class, and age). Commons (Commons, Trudeau, et al, 1998) used a mathematical system derived from Luce’s (e.g. Krantz, Atkinson, Luce, & Suppes, 1974; Krantz, Luce, Suppes, & Tversky, 1971) work on measurement. Each proposed stage was checked with the main three axioms. Again, these assumptions state that any given higher-stage action has to be defined in terms of an associated lower one and organize those lower-stage actions in an non-arbitrary way.

Commons’ and Richards' concerns lay with the general specification of any empirical task that possibly could be used to demonstrate either the presence of, or the development into, a postformal stage. They de-emphasize the reconstruction of the "reality" of a person "at a given stage." Instead, they attempt to develop a general way to specify the organization of tasks in any domain that a person "at a given stage" can do. Other attempts to specify what it means to be at a postformal stage can be found throughout the work reviewed here (e. g. See Table 2).

Postformal Orders of Complexity

We assert that highly creative innovations require postformal thought. Four postformal orders of hierarchical complexity have been proposed (Commons & Richards, 1984a, 1984b, Commons, Trudeau et al., 1998), beginning with systematic thinking and developing through metasystematic to paradigmatic and cross-paradigmatic thinking. The four postformal orders, according to the MHC, are displayed in Table 1.11. There is a growing consensus that these are the postformal stages as shown in Table 2.

Place Table 1 about here

Table 1.11 Postformal Stages, as described in the General Model of Hierarchical Complexity

	What is done	How this is done	The end result
11 Systematic operations	Constructs multivariate systems and matrices	Coordinates more than one variable as input.	Events and ideas can be situated in a larger context. Systems are formed out of formal-operational relations.
12 Metasystematic operations	Constructs multi-systems and metasystems out of disparate systems.	Compares and analyzes systems in a systematic way. Reflects on systems. Creates metasystems of systems.	Metasystems are formed out of multiple systems
13 Paradigmatic operation	Fits metasystems together to form new paradigms.	Synthesizes metasystems	Paradigms are formed out of multiple metasystems
14 Cross-paradigmatic operation	Fits paradigms together to form new fields.	Forms new fields by crossing paradigms.	Fields are formed out of multiple paradigms.

Innovators functioning at each of the four stages do tasks of different hierarchical complexity that do not overlap with one another. They do the different tasks using skills that are increasingly rare. The end results are entirely different for society. People have been known to accept the expertise of people functioning at the systematic and metasystematic stage. The results of innovation become much more expensive at the paradigmatic and cross-paradigmatic stages. The results change the world culture and our very view of the world. In fact, at the cross-paradigmatic stage, so few people exist that societies have no mechanisms to encourage such activity, as far as we know. Yet it is the that change the course of civilization. For example, Copernicus changed our view of our place in the universe, making the earth just another planet revolving around the sun. Darwin changed our view on our origins and place within the world of animals make us one more animal. Copernicus lead to modern physics and astronomy, Darwin to modern genetically based medicine evolutionary biology and psychology, palenotology, and behavioral psychology.

Systematic Stage

This stage was introduced by Herb Koplowitz (personal communication, 1982).^[2] Kohlberg (1990) referred to this stage as consolidated formal operations and only much later saw his moral stage 4 as being the same. Fischer (1980) listed it as the third level in the fourth tier. At the systematic order, ideal task completers discriminate the frameworks for relationships between variables within an integrated system of tendencies and relationships. The objects of the systematic actions are formal-operational relationships between variables. The actions include determining possible multivariate causes—outcomes that may be determined by many causes, the building of matrix representations of information in the form of tables or matrices, and the multidimensional ordering of possibilities, including the acts of preference and prioritization. These actions generate systems. Views of systems generated have a single “true” unifying structure. Other systems of explanation, or even other sets of data collected by adherents of other explanatory systems, tend to be rejected. Most standard science operates at this order. At this order, science is seen as an interlocking set of relationships, with the truth of each relationship in interaction with embedded, testable relationships. Most standard science operates at this order. Researchers carry out variations of previous experiments. Behavior of events is seen as governed by multivariate causality. Our estimates are that only 20% of the US population now functions at the systematic stage. Our guess is based upon data that about 20% of the population are in professions requiring systematic stage action. These professions require graduate degrees. Hence, the percentage of graduate students and professionals are good examples. For example, in Plano Texas 2000 census, 17.6% of the population had graduate or professional degrees In Geneva New York, it was 19.5%.

Metasystematic Stage

At the metasystematic order, ideal task completers act on systems; that is, systems are the objects of metasystematic actions. The systems in turn are made up of formal-operational relationships. Metasystematic actions analyze, compare, contrast, transform, and synthesize systems. The products of metasystematic actions are metasystems or supersystems. For example, consider treating systems of causal relations as the objects. This allows one to compare and contrast systems in terms of their properties. The focus is placed on the similarities and differences in each system's form, as on well as constituent causal relations and actors within them. Philosophers, mathematicians, scientists, and critics examine the logical consistency of sets of rules in their respective disciplines. Doctrinal lines are replaced by a more formal understanding of assumptions and methods used by investigators.

As an example, we would suggest that almost all professors at top research universities function at this stage in their line of work. We posit that a person must function in the area of innovation at least at the metasystematic order of hierarchal complexity to produce truly creative innovations. By definition of the metasystematic stage, it means that they have to coordinate at least two multivariate systems. We find that true adult creativity depends on an adequate performance on other related tasks. This is because the solution to tasks the society deems creative quite often requires a new synthesis of systems of thought (the metasystematic stage) or even a new paradigm (the paradigmatic order) or a field (the cross-paradigmatic order).

Paradigmatic Stage

At the paradigmatic stage, actions create new fields out of multiple metasystems. The objects of paradigmatic acts are metasystems. When there are metasystems that are incomplete, and adding to them would create inconsistences, quite often a new paradigm is developed. Usually, the paradigm develops out of a recognition of a poorly understood phenomenon. The actions in paradigmatic thought form new paradigms from metasystems.

Paradigmatic actions often affect fields of knowledge that appear unrelated to the original field of the thinkers. To coordinate the metasystems, people reasoning at the paradigmatic order must see the relationship between very large and often disparate bodies of knowledge. Paradigmatic action requires a tremendous degree of decentration. One has to transcend tradition and recognize one's actions as distinct and possibly troubling to those in one's environment. But at the same time, one has to understand that the laws of nature operate both on oneself and on one’s environment—a unity. This suggests that learning in one realm can be generalized to others.

Examples of paradigmatic order thinkers are perhaps best drawn from the history of science. For example, the nineteenth-century physicist, Clark Maxwell (1873), constructed the paradigm of electromagnetic fields from the existing metasystems of electricity and magnetism of Faraday (2000), Ohm, (1927), Volta (1800), Ampere (1926), and Ørsted (1820). Maxwell’s equations for fields and waves, showed that electricity and magnetism could be united, thus forming the new paradigm. The wave fields can be easily seen as the rings that form when a rock is dropped in the water or a magnet is placed under paper that holds iron filings. This paradigm made it possible for Einstein to use notions of curved space to describe space-time to replace Euclidean geometry. The waves were bent by the mass of objects so that the rings no longer fit in a flat plane. From there modern particle theory has been able to add two more forces to the electromagnetic forces giving us the standard electromagnetic-weak force.

Cross-paradigmatic Stage

The fourth postformal order is the cross-paradigmatic. The objects of cross-paradigmatic actions are paradigms. Cross-paradigmatic actions integrate paradigms into a new field or profoundly transform an old one. A field contains more than one paradigm and cannot be reduced to a single paradigm. One might ask whether all interdisciplinary studies are therefore cross-paradigmatic? Is psychobiology cross-paradigmatic? The answer to both questions is “no.” Such interdisciplinary studies might create new paradigms, such as psychophysics, but not new fields.

This fourth order has not been examined in much detail because there are very few people who can successfully perform tasks of this order of hierarchical complexity. It may also take a certain amount of time and perspective to realize that behavior or findings are cross-paradigmatic. All that can be done at this time is to identify and analyze historical examples.

Copernicus (1543/1992) coordinated geometry of ellipses that represented the geometric paradigm and the sun-centered perspectives. This co-ordination formed the new field of celestial mechanics. The creation of this field transformed society—a scientific revolution that spread throughout world and totally altered our understanding of people’s place in the cosmos. It directly led to what many would now call true empirical science with its mathematical exposition. This in turn paved the way for Isaac Newton (1687/1999) to co-ordinate mathematics and physics forming the new field of classic mathematical physics. The field was formed out of the new mathematical paradigm of the calculus (independent of Leibniz, 1768, 1875) and the paradigm of physics, which consisted of disjointed physical laws.

René Descartes (1637/1954) first created the paradigm of analysis and used it to co-ordinate the paradigms of geometry, proof theory, algebra, and teleology. He thereby created the field of analytical geometry and analytic proofs. Charles Darwin (1855, 1877) co-ordinated paleontology, geology, biology, and ecology to form the field of evolution which, in its turn, paved the way for chaos theory, evolutionary biology and evolutionary psychology. Charles Darwin (1855) noted that finches had diverged into a wide variety of birds. If they had not been isolated in the closed environment of the Galapagos islands, these finches would have represented a wide number of species, as was the case of mainland species of birds. Many people had been exposed to just such novel situations but made nothing of it. Although Darwin discovered this phenomenon in the early 1800s, it was not until many years later that he himself made any sense of it when he devised his theory of evolution. Darwin saw that evolutionary forces had transformed the birds differently. But, while Darwin’s specific observations of finches did not have much impact on the direction of science, his evolutionary theory did. Darwin created a good deal out of three new interrelated paradigms: paleontology, evolutionary biology, and ethology.

Darwin’s theory constituted a radical innovation in the science of his time for three reasons:

1. He presented evolutionary evidence establishing the fact that human thought and action are continuous with animal thought and action;

2. He proposed an explanation for human evolution that was not teleological, that is one that did not claim an ultimate purpose; and

3. Darwin's theory brought together four distinct prior paradigms, those of: biology, ecology, animal behavior, and geology.

Albert Einstein (1950) co-ordinated the paradigm of non-Euclidian geometry with the paradigms of classical physics to form the field of relativity. This gave rise to modern cosmology. He also co-invented quantum mechanics. Max Planck (1922) co-ordinated the paradigm of wave theory (energy with probability) forming the field of quantum mechanics. This has led to modern particle physics. Lastly, Gödel (1931), co-ordinated epistemology and mathematics into the field of limits on knowing. Along with Darwin, Einstein, and Planck, he founded modern science and epistemology.

Table 2 summarizes most proposals for postformal stages (for a review, see Marchand, 2001). The columns represent the major adult developmental stages. The rows list the researchers and some key publications for the names and numbers of the stages.

Table 2

Comparative Table of Concorded Theories of Formal Stage

class=Section2>

Researchers	Abstract	Formal	Systematic	Meta-systematic	Paradigmatic	Cross- Paradigmatic	Transcen-dental
Bowman. (1996), Commons & Richards (1984a,b); Commons (1991); Commons & Rodriguez (1993); Commons & Wolfsont (2002); Rodriguez (1989)	9 (= 4a)	10 ( = 4b)	11 ( = 5a)	12 ( = 5b)	13 ( = 6a)	14 ( = 6b)
Sonnert & Commons (1994)	group	bureaucratic	institutional	universal	dialogical
Inhelder & Piaget (1958)	formal III-A	formal III-B	postformal	polyvalent logic; systems of systems
Fischer (1980); Fischer, Hand, & Russell (1984)	7	8	9	10
Sternberg (1984)		first-order relational reasoning		second-order relational reasoning
Kohlberg (1981)	3 mutuality	3/4	4 social system	5 prior rights/ social contract 6 universal ethical principles
Benack (1984)	4	5	6	7
Pascual-Leone (1984)	late concrete	formal and late concrete	pre-dialectical	dialectical			transcendental
Armon (1984)	3 affective mutuality	3/4	4 individuality	5 autonomy	6 universal categories
Powell (1984)	early formal	formal	stage 4a/ interactive empathy	category operations
Labouvie-Vief (1984)		intra-systematic	inter-systematic	autonomous
Arlin (1984)	3a low formal (problem- solving)	3b high formal	4a postformal (problem-finding)	4b relativism of thought 4c over-generalization, 4d displace-ment of concepts	4e late postformal (dialectical)
Sinnott (1984)		formal	relativistic/ relativize systems, metalevel rules	unified theory: interpretation of contradictory levels
Basseches (1984)	phase 1b: formal early foundations	phase 2 intermediate dialectical schemes	phase 3: 2 out of 3 clusters of advanced dialectical schemes	4. advanced dialectical thinking
Koplowitz (1984)		formal	systems	general systems		unitary concepts
Perry (1970) see West (in press)	Dualistic	Multiplicative	Relativistic	Committed )
King & Kitchener (2002)	4	5	6	7
Torbert (1994)	diplomat	technician	achiever	ironist
Kegan (1994)	3:interpersonal	3/4	4: institutional	5
Loevinger (1998)	conformist-conscientious	conscientious	individualistic	autonomous integrated ^[3]
Cook-Greuter (1990)	3/4	4	4/5	5	5/6		6
Gray (1999, June, personal comm.)	early formal	formal	systematic	metasystematic
Bond (1999, June, personal comm.)	early formal	formal	systematic	metasystematic
Dawson (2002a, b)	9	10	11	12	13	14
Kallio (1991, 1995)	formal 1	formal 2	formal 3 generalized formal	postformal
Demetriou (1990; Demetriou & Efklides, 1985)
Broughton (1977; 1984)	3: person vs. inner self	4. dualist or positivist; cynical, mechanistic	5. inner observer differentiated from ego	6. mind & body experiences of an integrated self

HIERARCHICAL COMPLEXITY IN HUMAN SOCIETIES

The development of complexity in human societies depends on innovations by single individuals. The innovator has the tendency to discern and discriminate relationships among elements that are extremely complicated. Making an innovation is much more difficult than learning about it after it is made. Major cultural innovations require paradigmatic complexity (Commons & Richards, 1995) because there is no support whatever from within the cultures themselves. The level of support represents the degree of independence of the performing person’s action and thinking from environmental control provided by others in the situation. We define 6 levels of support: (-3 level) Manipulation, which is literally being moved through each step of how to solve a problem; (-2 level) Transfer of stimulus control is being told each step; (-1 level) Pervasive imitation is being shown, which includes delayed imitation or observational learning (Gewirtz, 1969). The imitated action may be written, depicted or otherwise reproduced. Fischer and Lazerson (1984) call this form of control the optimal level; (0 level) Direct is being given no help or support in problem-solving or hacking (without support). Fischer and Lazerson (1984) call this the functional level. Most of Piaget’s work was at this level. (+1 level) Problem finding is in addition, to not getting help, one must discover a task to answer a known question. Persons may be given an issue and they are asked to give a example of a problem that reflects that issue. Arlin (1975, 1977, 1984) introduced postformal complexity (systematic order) by requiring the construction of a formal-operational problem without aid or definition. “Finding” a given problem increases complexity demand by one order of complexity over solving a posed problem with no assistance; (+2 level) Question finding is in addition to not getting help, one must discover the question not just the problem to address a known issue. With a known phenomenon, people find a problem and an instance in which to solve that problem. One has to discriminate the phenomenon clearly enough to create and solve a problem based on that discrimination; (+ 3 level) Phenomenon finding offers no direct stimulus control, which is not possible without a description of phenomenon. This requires the discovering a new phenomenon so there is no reinforcement history with phenomenon. The difficulty of an action depends on the level of support in addition to the horizontal information demanded in bits, and the order of hierarchical complexity. Each increase is the level of support reduces the difficulty of doing a task by one stage. Each decrease in the level of support raises the difficulty of doing a task by one stage (Commons & Richards, 2002).

There is little support for major innovations in culture because the history of the necessary hierarchical complexity surrounding the task is absent. Nor is there a history of reinforcement that would induce the subject to detect new phenomena. Therefore, even if understanding--or using the innovation, once it is created--requires only formal operations, to the individual who creates the advance requires two more levels of and, therefore, roughly paradigmatic complexity. In order for an innovation to be absorbed by/assimilated into the culture, the culture must perform at the formal order with respect to the innovation.

The Stage of an Inventor and the Stage of a Culture Differ

Individual and cultural development have a straightforward relationship to one another. The stage of cultural development is limited by the highest stage of performance of a member. But it is usually lower in stage than that of that persons performance. As new hominid species came into existence, that led eventually to Homo Sapiens, some of those species had at least a single individual who could solve problems at one higher stage than the species that they eventually replaced. Mutations and stage of performance both have a probabilistic distribution in a population. We might assume that because some exceptional Chimpanzee perform at the concrete stage 8 (Commons & Miller, in press), our common ancestor would have likewise performed at the concrete stage. Commons and Miller argued that there was a progression in top performance of the common ancestor to the homo sapiens though the abstract, formal and systematic stages. Only with a very large population, would one find paradigmatic and cross-paradigmatic performing individuals. Our best estimate from Dawson’s (2002) data on stages of moral development is that each stage is spaced one standard deviation apart. At some time after the first Cro-Magnon Homo sapiens, we argue there were enough people in the population that there was a member who behaved at the paradigmatic stage. The requirement is for only one such member. Only one member at a time invents, even though the invention might be a joint enterprise in other regards. Even in a co-operative behavior, one person has the behavior first, even if only a millisecond before the other. Yet that inventing behavior is totally dependent upon others’ past inventions. Inventions can only build upon the last inventions and may be limited to advance just one or two stage beyond those inventions. Because an individual may only limited to one or two stages above the stage of invention in a culture, The stage we assign to cultures can be so much lower than the stage attained by the most developed individuals. Dictatorships may limit the stage of the society to preoperational (Stalin in his paranoid period, functioned at the primary, concrete; grinding bureaucratic governments limit the society to formal).

Even though individuals might act at the highest stages--for example, paradigmatic--societal development tends to lag behind individual development because at each stage of cultural development the cultural innovators outpace their contemporaries, at least within their domain of innovation. In order for a culture to progress, there must be a supply of innovators who work with minimal support from their culture. And it is the size of this supply that seems to be the largest bottleneck in cultural development.

Truly Creative Acts Change Culture

To be “truly creative,” an act has to reach and influence a large enough group within the world that it survives in the culture and has influence. Otherwise, no memes are created. Sometimes potential creative acts are not communicated, either because the society is not proficient enough to receive them, or simply because the acts themselves are either not transmitted at all or are inefficiently transmitted. For successful transmission and dissemination of innovation to take place, the culture must be able to absorb the discovery. A discovery may be regarded as a new pattern of behavior performed by an individual or individuals in various situations. Formal and informal education are the means by which memes are acquired (Cavalli-Sforza, Feldman, Chen, Kuang-Ho & Dornbusch, 1982). Most people cannot possibly understand an innovation on their own because they do not reason at a high enough stage. Increasing support through teaching and training, insures that they come to understand and possibly utilize a higher stage behavior (Fischer, Hand, & Russell, 1984), including a discovery. Thus, it follows that the innovator must be some form of teacher in order for the new memes to be acquired by others. One incentive in having lots of graduate students, is that some might follow-up and build upon ones own work. It is necessary to publish, present and promote much innovative work because otherwise it gets lost in the huge number of publications. It may also help to get material into text books and reviews.

Discoveries and findings need to be spread by infection of memes (Commons, Krause, et al, 1993; Trivers, 1985). The difficulty in spreading memes has dramatically slowed the process of discovery. Many discoveries have to be made repeatedly before they take hold. People have to engage in activities that require the new cultural information. The transmission of memes usually requires that the uninitiated individuals receive some degree of support in order to learn the new memes. In learning the new actions required by the innovation, an individual is thereby infected with the memes of the innovation. In carrying out the activities associated with the innovation, as well as in teaching others to do likewise, the individual is further infected. The more thoroughly an innovation is learned and taught, the greater the degree of infection by memes. Learning innovations increase employability in the present culture.

To learn one innovation, such as computer programming, puts one into an educational system that transmits other memes as well. The larger set of infecting memes become part of the participants' resulting behavior. All effective educating, training, and communicating result in a transmission of memes. The rate of transmission depends upon increasing contagion so that the potential innovators come into contact with the most advanced forms of the present culture. A demand for the innovation also has to exist so that innovation pays off.

NOVELTY AND MORE HIERARCHICALLY COMPLEX BEHAVIORS

Novelty has two aspects that are important to creativity. First, novelty spurs the development of more hierarchically complex behaviors and, second, creativity requires an original response to novelty. People who are overwhelmed by novelty are precluded from creative discovery. They avoid confronting novel and anomalous findings and observations. In this section, we will discuss how novelty is involved in stage change a particular form of learning. Such stage change quite often is necessary for the truly creative act.

Novel behavior is the psychological dimension of an individual's response to a new or strange situation. Such a situation may consist of a sudden or unpredictable change in a known state of affairs. It has been shown that novelty greatly aids, if not induces, continuous intellectual development within domains and discontinuous development across domains by forcing transitions between lower and higher stages (Grotzer et al., 1985). Furthermore, this development is dependent upon “new” more hierarchically-complex behavior obtaining outcomes that the individual prefers. Novelty in ordinary problem-solvers often produces some development. Strikingly similar in some aspects, but just as strikingly different in others, is the problem-solving of ‘truly innovative’ thinkers. The former type of novelty leads to development that is ordinary in the society of the time and to actions that are also ordinary in that society. The latter, by comparison, is characterized by originality and not limited by the hierarchical complexity of thinking that is near the social norm. A tangible and full-bodied historical example of this latter type can be found in the creative work of Charles Darwin (e.g. 1855, 1969, 1872, 1877).

Novelty and the Creative Behavior

Creative behavior is always novel. The behavior responds to some novel aspect of the environment that others have missed. Take the example of Darwin’s observation of finches, as discussed earlier. This is an example of discovering a phenomenon. The discovery itself did not have much impact upon Darwin’s conceptualization, but years later he made sense of the phenomenon by proposing his theory of evolution. The finches had evolved and now filled the same niches that mainland species of birds of much greater variety had filled. In one case, the niches were filled by a variety of finches (system one) and in another by many separate mainland species (system two). Darwin saw that evolutionary forces had transformed the birds differently (a metasystematic comparison of systems one and two). But, he understood this phenomenon without support. Hence, this is cross-paradigmatic. Creative innovations, to have social impact, must be a part of a chain of transformations in which later ones progressively build upon earlier ones. The progressive nature of such transformations distinguishes such creative innovation from mere stylish variations. Styles come and go, but science tends to be progressive.

THE PERSONALITIES AND TRAITS OF MAJOR INNOVATORS

Necessary but not Sufficient Traits of Environments and History that Allow for True Creativity

Many tendencies to act in particular ways can be directly related to major innovation. In traditional personality theories, when tendencies are somewhat stable over time, they are called traits. Although some of these tendencies are partially inherited, some portions are acquired (Bouchard, Lykken, McGue, Segal, & Tellegen 1990). When we are assessing these tendencies, we cannot tell which it is without doing twin studies or similar studies. In either case, in the present no one has access to what it is that created these tendencies. Traits are not causes of behavior, however. They are just intermediate results. Behavioral-analytic theories would tend to explain these tendencies with respect to the individual’s history and present circumstances. Behavioral momentum theory (Mace, Charles, Lalli, Shea, & Nevin, 1992; Nevin, Tota, Torquato, & Shull, 1990) describes two types of histories that produce persistence and independence, a resistance to influence by social controls and high risk-taking. The first history is one of plenty or independent wealth. Let us take the case of Darwin again; he was independently wealthy. Darwin’s quest for the truth was unfettered by concerns for employment. Although some were extremely upset by what he was doing, he could not be fired and lived quite well. Einstein described the life of a patent officer as ideal, getting paid for doing what one likes. There was little work in that position that he did not enjoy. And, it left him with plenty of time to work on his own theories. Hence, again, his discovery behavior was not under the control of an employer or social institution.

Personalities that Withstand Social Conformist Influences

Innovators do not have non-conforming personalities in general, but they do withstand social conformist influences. To spread their innovations they are highly connected to society as opposed to the non-conformist, who, may chose to live outside of society, such as Raskolnikov in Dostoyevsky’s (1914) Crime and Punishment. Dostoyevsky presented the criminal-minded student Raskolnikov who was mired in poverty. He nevertheless thinks well of himself. That young man used Periclean/Platonic justifications to murder an innocent businessman – a money lender – in a tenement. He used those rationalizations to support "greatness" -- to financially support "Raskolnikov's greatness" -- to support his "elite-wannabe" parasitisms. Of his pawnbroker he takes a different view, and in deciding to do away with her he sets in motion his own tragic downfall.

Ambition and curiosity

One definition of ambition is a strong preference to achieve great things. This seems essential to creative behavior because many creative acts require persistence and enthusiasm for the enterprise. There is very little research on such ambition. It is not clear that ambition can be learned but it is clear that it can be dampened. A major trait of the great discoverers was that they were extremely curious. This would be reflected in extremely high scores on the Holland (1996) factor called investigative (I) if it ever assessed. This means that discovering was extremely reinforcing for them.

The great curiosity of people presses for their own development. Having high investigative interests should also propel stage change. Interest raises the reinforcing value, which in turn increases the rate of self presentation of problems because such self presentation is reinforced. The increased rate of attempting problems would raise the probability of solving them. This is because the number of attempts at solving a problem probably matter. Great discoverers would also have more resistance to giving up in their continued confront of problems. Doggedness means that one sticks to finding a solution, does not get stuck in relativism as discussed below. So much so they behaved in a determined dogged manner in their pursuit of their burning questions. Note that decentration comes in again. People who are worried about themselves and their reputation and standing cannot take the risks to be creative. People who have a great deal of interest in their burning issues are generally more worried about the problem than themselves. The ambition is towards solving the problems, not becoming acclaimed, respected or powerful.

Cognitive Styles

Witkin, H. A., Oltman, et al. (1971) in their Group Embedded Figures Test Manual (GEFT) defined as an example of field independence a paper and pencil test, where subjects are required to recognize and identify a target figure within a complex pattern. The more figures found, the better the individual is at the process of separation and, is said to be more field independent. Field independence is associated with creative functions in adults (Minhas & Kaur, 1983). This classically defined cognitive style has been measured by the rod and frame] task (Witkin, 1949; Witkin, Lewis, Hertzman, Machover, Meissner, Wapner, 1954). The degree to which people are field-independent correlates with their ability to resist social pressure and the influence of social cues. Field-independent people are more likely to exhibit creativity and are more likely to resist the social pressure to conform to tradition.

Minhas and Kaur (1983) support the idea that field-independent individuals display a penchant for novel types of acts. They also find an overlap between field independence and intelligence. Ohnmacht and McMorris (1971) found that neither field independence nor lack of dogmatism alone is useful in explaining variations on a task presumed to reflect creative potential. However, when considered together, these variables become significant. Using the proclivity to produce transformations of visual information as a measure of creativity, Ross (1977) also found a high correlation between creative behavior, locus of control, and field independence. Locus of control is a personality construct referring to an individual’s perception of the locus of events as determined internally by their own behavior versus fate, luck, or external circumstances.

Detachment from the Social Order

But traits are not enough. The major innovators act in ways that insulate them from social pressures rather then just resisting the social pressure to conform. Major innovators tend to be non-competitive with others because they do not use others as a frame of reference. They are not really concerned with other people’s opinions of them and do not compare their own activities and "success" with others’. Instead, in terms of social comparison theory, the comparison may be to one’s own performance or the performance of some historical figure. Therefore, creative actions often require that there be a certain detachment from the social order and from social approval. Surprisingly, Attention Deficit Disorder is associated with creativity (Cramond, 1995) possibly because there is inattention to social signals of condemnation and ,therefore, interfere with social conformity.

To be creative, individuals also must be able to withstand rejection. Smith, Carlsson, & Sandstrom (1985) found that creators use fewer compulsive or depressive defenses and are free from excessive anxiety. They also found that creative individuals have access to their dream life and to their early childhoods. More often than noncreative individuals they tend to remember both positive and negative qualities of these life experiences. Finally, creativity requires one to separate oneself from one’s creations. Otherwise one would rarely be self-critical of one's creative output. If one were always satisfied, there would be no development, no reaching for more. Being challenged by, rather than upset at, not knowing the details or the direction of one's enterprise seems essential, as does the ability to withstand and overcome disconfirmation or failure at a particular step in the enterprise. All of these require risk-seeking behavior. The passion involved is for the enterprise of discovery, not for the self, a particular act, or a need for social approval. This independence may lead to a sense of isolation from others, while, though painful, may also prove to be surprisingly necessary.

Timing of Creative Acts

Even with all of the personal traits mentioned above, creative acts require a certain timing. Timing of creative acts may have three sources, each conflicting with the others. First, development of higher-order hierarchical complexity takes time. As we show, some of the most integrative and highest-order acts may not take place until middle age or later as was the case with both Copernicus and Darwin. Second, one needs a lot of time to develop one’s own ideas, and in an arena within which those ideas will not be demolished before they can attain integrations. Third, there is, a long social agenda of the work one is supposed to carry out rather than doing the work that takes one down one’s own creative path. This social agenda entails diversion of a certain amount of time and energy to work on other people’s problems. One might then simply adopt their frame of reference rather than pursue one’s own.

Tolerance of Ambiguity, Risk Taking and Interests

Tolerance of ambiguity, interest in the novel and anomalous, and the taking of risk are necessary for creativity. Students doing research often ask why the professor does not simply give them the right method for understanding a new problem the first time. The professor then says that “if I knew the right method for solving this problem, I would have learned it from somebody who had already answered the question.” Other data says otherwise. Ambiguity is more tolerable for older adults, making the ambiguity in the creative process less of a threat. Gisela Labouvie-Vief (1985) noted that older adults were at ease when working with ambiguity creatively (also see Arlin, 1984; Labouvie-Vief, Adams, et. al, 1983). Younger adults focus on reaching a conclusion that makes sense when presented with logically inconsistent statements, whereas older adults concentrate on the problems inherent in the premises. They comment on the inconsistencies, question them, and sometimes introduce ideas that might resolve them. They go beyond the information given in the problem on the basis of their own personal experience and knowledge.

The Integration of Postformal Scientific Actions with Adult Social Actions

The exposure to a broad range of societal ideas through integrating career with societal activities prompts greater creativity based upon higher stages. Integration of social and scientific acts primarily occurs in early adulthood and after. Whereas people meet the peak of their stage development in early through late middle age, some great innovators reach the highest orders of development earlier in life (Stevens-Long & Commons, 1991). For example, mathematicians often reach their peak in their twenties. For active individuals, developmental stage peaks between the 50s and late 60s. Generally, it is not until middle age (40s or so) that people can recognize that they are not only underneath a social structure and climbing within it, but that they also create and maintain that system. Active people engage in the process within their families, work places, professions, and communities. They come to see themselves as responsible parts of society. It is at this time, for example, that many men become more active in their families by exhibiting more nurturing behavior. Many women become more active by pursuing careers and additional education. Both genders will thus become more similar to each other.

Attaining Postformal Stage Performance

Commons and Miller (1998) and Commons and Richards (2002) have described both stage transition and reasons why transition takes place or fails to take place. The first three steps (deconstruction) start with initially high loss of perceived reinforcement opportunity. But, during the advance through these initial steps, more reinforcement is obtained. Psychologically, the results are consistent with Jesus Rosales-Ruiz and Donald Baer's (1997) work on behavioral cusps. A cusp, as defined by Rosales-Ruiz and Baer, is “a behavior change that has consequences for the organism beyond the change itself, some of which may be considered important” (p. 537). For example, a child learns to walk with great difficulty, moving slower to the place they are moving towards than if they crawled (a perceived loss of reinforcement). Then that child gains access to environmental stimuli and contingencies (interactions with siblings or with the family pet that are reinforcing) that would be otherwise unavailable. They posit more cusps than there are stages, however. Most of the proposed psychological mechanism of transition seems to be consistent with these theories. Despite this, most Piagetian or Neo-Piagetian theories do not operationalize clearly the steps in transitions or the empirical basis for transition.

Practice of the previous stage behaviors until they are automatized seems to increase the rate of stage transition, speeding up the movement through the steps. As old-stage tasks are completed near the maximum rate and errors almost disappear, the actions are said to become automatized. Such over-learning leads to automatization. The task stimuli are said to become “chunked.” That is, each individual stimulus in the task no longer has to be discriminated individually, but now as a whole. Both within many neo-Piagetian accounts (e.g. Case, 1974, 1978, 1982, 1985) and Precision Teaching (e.g. Binder, 1995) accounts, automatization of previous-stage behavior (elements) is predicted to improve the rate of obtaining next-stage performance (combinations). From the data from Precision Teaching, fluency in previous -stage tasks greatly enhances the rate of acquisition of the next-stage tasks.

Although all tasks must have an order of hierarchical complexity, performance on such tasks depends on many other task characteristics. They include, level of support (Fischer, Hand, & Russell, 1984); Commons & Richards (1995), horizontal complexity, fluency of performance on the component tasks, “talent,” interest and other factors. Hence, one may expect complex interrelationships between measures of performance on tasks and conditions of measurement. As discussed previously level of support alters measured stage linear manner. But the stage of performance should be curvilinear when plotted against the subjects’ chronological age (Armon & Dawson, 1997; Dawson, 1998) and linear when plotted against log age. This more complex relationship is due to the fact that the orders of hierarchical complexity are spaced with equal difficulty. But development with age slows down logarithmical with age (Backman, 1925). The conceptual basis of Backman's function of growth, is the postulate that the logarithm of growth rate is negatively proportional to the square of time's logarithm, log H = k₂ log2T. Constant k₂ is always negative. Also variability should increase with age, and it does. Yet, there is some evidence that at the higher stages, there is less spread. The proclivity to integrate relationships and systems and even paradigms from many domains probably increases with postformal stage.

Precursors of the Higher Stages

Commons-Miller (2003) found a number of things that were predictive of intergenerational success of the most highly successful scientists. In the examples studied, the younger generation associated with adults to a large extent. As children, the younger generation were part of a family enterprise that involved science. They were treated respectfully, their opinions sought and challenged. They started their scientific work early, as was the case for Jean Piaget (1952; Vidal, 1994) who was son of the Arthur professor of medieval literature at the University. In many cases they worked with one or more of their parents. Richard Leaky (son of Mary and Louis) and Walter Alvarez (1987) was the son of Louis Walter Alvarez. Louis Walter Alvarez’s father left his very successful medical practice as an internist in San Francisco to join the staff of the Mayo Clinic in Rochester, Minnesota, as a research physiologist. Walter Alvarez and his team, which included his father Dr. Luis Alvarez, Frank Asaro, and Helen Michel, proposed that an asteroid hit the earth, throwing up a dust layer that encircled the earth and lead to the extinction of the dinosaurs.

These precursors are rarely met. Adult stage of development is normally distributed with a mean stage of formal and a standard deviation of one stage in our educated society (Dawson, 2002a; 2002b). Therefore, it not surprising that adult-developmental researchers find very few individuals who engage in the metasystematic performance necessary for creativity. Some examples are as follows: Armon (1984), found 9% (3 out of 32) on the Good-life Interview, and 15% (5 out of 32) on the Moral Judgment Interview. Richards and Commons (1984), found only 14% (10 out of 71 participants) on the Multisystems Task, Demetriou and Efklides (1985), found 11% (13 out of 114) on the Metacognitive Task. Kohlberg (1984; Colby & Kohlberg, 1987a, b), found 13% (8 out of 60 participants aged 24 and older), who used stage 5 reasoning on the Moral Judgment Interview. Powell (1984), reported 9% (4 out of 44 participants) performed metasystematically.

There are personality characteristics associated with getting stuck in a stage change step during stage transition (Commons & Richards, 2002). These are described in the transition table.

Relation

Name

Personality

Description

1. Step 0

a = a' with b' where a' and b' previous stage actions

Temporary equilibrium point (thesis

Fault finders

At low orders of performance in the social domain, this may result in antisocial behavior. These people perceive tremendous unfairness. People get stuck here because much of their current order behavior is maintained by “punishment” that reinforces the failure behavior. They have experienced a huge drop in perceived reinforcement rate because they see the failures of their behavior of the present order to obtain what others do. They quite often have unshakable negative depressive scripts. They deny the value of new ideas.

Step 1

Negation or comple-mentation (antithesis)

Nay sayers

This may consist of persons who enter therapy, as well as rebels, radicals, and discontents. They have given up their old ways. If “a” is wrong, then the opposite of “a” is right. This step is associated with the second largest drop in reinforcement rate because people may drop their previous successful behavior “a” and substitute behavior from “b” for it.

Step 2

a or b

Relativism (alternation of thesis and antithesis)

Relativists

Clinically at its worst, such persons may be Narcissists (Situationalists) or Borderlines (That nothing works proves no one loves them). In this culture, it is quite often the largest group of people in transition. They fill academia. They stop progress by insisting that there is more than one way to look at things but cannot even decide which ones are more likely to be true or good. There is some gain in reinforcement, but the conflict between whether to choose “a” or “b” produces anxiety, angst, mood swings, and uncertainty about roles and values.

Step 3

a and b

Smash (attempts at synthesis)

Movers

Such persons are moving from smash to consolidate. They create great trouble for themselves and others by throwing ideas and actions together in a creative, haphazard way, taking a great deal of risk.

Step 4

a with b

New temporary equi-librium (synthesis and new thesis)

Unshakables

To these persons, everything is OK even if it is not OK. They avoid conundrums, apparent contradiction and comparisons to people they look up to. Everything is good enough.

Social Control

A society that not only tolerates but promotes creativity produces more creative acts. This can be seen in Nemeth & Kwan’s (1985) study on originality in word associations that found that participants who are exposed to persistent minority views tended to re-examine issues and to engage in more divergent and original thought. On the other hand, participants who were exposed to persistent, fairly exclusive, majority views tended to concentrate on the position proposed, to display convergent thinking, and to be less original. One might assume that all creativity depends upon originality and divergent thinking.

General Characteristics of “Truly Creative” Individuals

A creative innovator will not have done society’s bidding for long. One has to work on one’s creative acts early on. Delaying work on ones creative program means that the other intervening activities will be reinforced lowering the probability of ever competing ones own creative acts. True adult creativity requires building upon current knowledge and then transcending it. It requires that innovators or creators have novel insights into complex problems. This often requires that there be created a new synthesis of systems (metasystematic), or a new paradigm (paradigmatic order) or field (cross-paradigmatic order) on the part of such an individual.

IMPLICATIONS OF VALUING THE HIGHER STAGES

Genetic evolutionary forces have generally increased the stage of reasoning from the concrete stage in the common ancestor of Homo Sapiens and Chimpanzees to the cross-paradigmatic in humans, we may wonder whether such forces will actually increase the number of people functioning at the cross-paradigmatic stage over time. How soon might this begin to happen? Might someone even function at stages beyond the cross-paradigmatic? But of the two forms of evolution, genetic and cultural, the impact of cultural evolution as it impacts postformal stages and will be discussed first.

As revealed in introductory psychology books, a self-reflective understanding of postformal stages is developing widely. In this context, we find tremendous differences arising among social groups--differences that seem to be related to education levels and the power of reasoning (Kegan, 1994). Will this trend continue? Given the degree to which certain peoples and groups seem to value higher stage development, one must wonder how far some might go in their efforts to produce intellectually advanced individuals – those who, for example, could function at the cross-paradigmatic stage. Might the trend in this direction be illustrated in part by the fact that people are now paying huge sums to educate their children at top research universities, graduate and professional schools? The are encouraging their children to obtain postgraduate education. Might some go even further in this direction and attempt to push the limits of evolution and natural selection through humanly engineered means? How far will people go in this direction? The power and influence are highly selected for--both genetically and culturally.

Where might this tendency lead us? Some extremely controversial predictions are to be made in this context. We the authors are not advocating these scenarios, but are merely describing their possibility and pondering their implications. At the same time, we believe we must marvel at the degree to which some people might just push the envelope of selection in their efforts to achieve some kind of competitive edge, creative transformation or some unique version of self-transformation. As we write about these things, we are aware that some of these ideas might sound like the plot lines from various science fiction novels. When we push the limits of this kind of thinking--and translate it into practice, we might obtain very interesting, but sometimes sobering or even frightening, results. For example it was sobering and frightening to find that clones aged at a much more rapid rate, reflecting the age of the DNA.

As stated earlier, evolution itself is not teleological. The direction is not evitable. The direction of the forms of evolution are not emergent. It is not directed by moral or ethical considerations. For this and related reasons, people should pay attention to the tremendous ethical controversies surrounding these issues. Our entire society should wrestle with these ethical dilemmas and address them. There is the daunting task of showing respect for all, while at the same time recognizing the inequities promulgated by the interplay of nature and nurture. How these differences should be handled in the future should be widely discussed. The consequences of such matters should be vigorously debated and ethically-informed policies must be formulated. With these ethical considerations in mind, we would like to review three mechanisms through which one can imagine that the number of higher-order creative innovators might increase: a) cultural evolution; b) biological evolution; and, c) computer and robotic hardware and software evolution.

Cultural Evolution

Cultural evolution now promotes people who reason at the highest stages. Could cultural evolution also produce biological evolution? With the increase in demand for people with the highest stages of postformal reasoning, certain forces have come to bear. Our society is rapidly acquiring the technological know-how that will permit experts to engage in human engineering and cloning. Commons-Miller (in press) suggests that people have begun to use a variety of mechanisms to produce intellectually superior individuals. Historically, these include primarily assortativeness. Assortativeness means that there is a demand for separation from the rest of the population. It is accomplished by means of clubs, zoning, rules promoting intragroup marriage and blocking intergroup marriages, and career specialization by groups. Assortativeness has always been a force in human cultural and biological evolution. The evidence suggests that many will be tempted to move in this direction, as those with high intelligence already do in the Mensa organization.

Biological Evolution

Commons-Miller (in press) think that the heavy demand describe by David Baltimore, a Nobel laureate who heads the California Institute of Technology, will encourage the rapid development and utilization of germline engineering. This in turn will lead to speciation as Dyson (1999) thinks. He states that the speciation of humans into different groups is inevitable -- and it would be a disaster to allow such diversification without restraint. Biological evolution, as described by Darwin, requires isolation among individuals, within species. Mayr (1942) stated that a new species develops if a population that has become geographically isolated from its parental species acquires during this period of isolation characters which promote or guarantee reproductive isolation when the external barriers break down. Mate choice, also known as sexual selection also may drive the speciation process (Higashi, Takimo & Yamamura, 1999). Assortativeness might be the required force for selection. It is predicted that speciation in humans is likely soon, however controversial it is. That is, we might begin to find the differentiation of humans into more than a single species. Some groups might begin to engage in genetic engineering in order to isolate their group from the rest of humanity. It is this isolation from the rest of humanity that can cause speciation.

If these individuals are sufficiently different enough and brighter, and can survive inbreeding, some would argue that a new species might evolve. This new species might have a greater proclivity for creativity in general and especially in science, if some of the relevant traits discussed above, as well as highest postformal stages, are selected for.

Computer and Robotic Hardware and Software Evolution

There is another way that people might attempt to create the extra-human or super-human levels of achievement – by somehow linking advanced humans with superior reasoning and creative proficiencies with hierarchically complex stacked neural-net computers (Commons & White, in press). The "product" or "offspring" might be able to solve problems in science that are not solvable by ordinary high-functioning humans. The motivation for “supercomputers,” on the other hand, would seem to differ from speciation. The development of computers is relentless with most people cheering the changes. Computers, like all technology can be used for good and evil--remember “Hal” in Arthur Clarke’s (1968) book and movie 2001. Such super computers likely could be built from stacked neural-nets, and in turn, reason like humans but limited in the number of layers. This is an important consideration, because we speculate that the number of layers of interconnected neural networks is related to the order of hierarchical complexity at which such machines will perform. It might be interesting to assess their stage of development with our MHC scoring system.

Again, the consequences of all these possibilities must be thoroughly debated and policies formulated with an ethical standard in mind. Furthermore, we argue that the debate must be spirited and it should begin soon. The doggedness with which individuals and groups might pursue such revolutionary intellectual and creative transformations as these may prove to be truly remarkable. Could Darwin have had any idea where some of his early theorizing might lead?

CONCLUSION

The creation of major cultural innovations is multidimensional. These innovations are often accomplished by distinct groupings of individuals who display an assortment of specific traits. Charles Darwin was chosen as an example of one with the requisite traits. Most major innovators display the essential traits or characteristics discussed throughout this chapter. There were a few characteristics that have been found to be absolutely necessary. Most important was the order of hierarchical complexity of tasks with which such a person could deal. This included the complexity in the area of the work as well as commensurate complexity in the social system. When these two dimensions work together, the likelihood of a major creative innovation is enhanced.

ACKNOWLEDGMENT

Some of this material comes from Commons and Goodheart (1999) and from Commons and Bresette (2000). Dare Institute staff members have edited the manuscript and made major suggestions for change.

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