Chapter 14

The Perspective of the Humanities:Toward Explicit Knowledge

The spread of the digital medium is already giving rise to a profound change in the public sphere. This is a change in the scale of civilization, and it will be thought out over several generations, as was the case for the invention of writing, the alphabet and printing. Just as previous changes in communication led to or brought about (without mechanically determining them) transformations in the forms of knowledge, the changes under way will likely lead to a scientific revolution. The exact contours of such a revolution are still difficult to predict, but the IEML model suggests certain intellectual and methodological horizons. In this chapter, I will explore how the Hypercortex could contribute to the renewal of the human sciences. As shown in the conceptual map in Figure 14.1, I will look at the culture studied by the humanities and social sciences, that is, human collective intelligence. If this intelligence can be reflected in the mirror of the Hypercortex, how will the landscape of the human sciences be changed?

14.1. Context

Chapter 5 outlined the general context of the transformation of the human sciences, in particular the stakes involved and the weaknesses and strengths of the contemporary human sciences. As regards the stakes, the question of human development is becoming increasingly important. It is clear that societies that fund public research and education in the human sciences expect “results” in terms of security, economic prosperity, public health, well-being, innovation, cultural productivity, transmission of heritage, etc. As regards the weaknesses, I noted the 324 The Semantic Sphere 1 disciplinary and theoretical fragmentation and the rarity of calculable models of the social production of meaning. Finally, regarding the strengths we can already see the growth of new forms of collaboration and observation (availability of data) made possible by the digital medium.

Figure 14.1. Position of Chapter 14 on the conceptual map

14.1.1. The increasingly transnational, transdisciplinary and democratic nature of the human sciences

I would now like to add a few elements to this description of the context. The material natural sciences are universal in the sense that they share the same scientific metalanguage (system of coordinates, units of measurement, atomic elements, molecules, etc.). It is clear that the human sciences have not yet reached this level of maturity. Nevertheless, there is a trend toward open universality, as indicated by three parallel thrusts that can be clearly felt in contemporary universities: transnational globalization, transdisciplinary collaboration and democratization. These three developments are already being, and will continue to be, accelerated by the expansion of the digital medium, a medium that is inherently global and Toward Explicit Knowledge 325 hypertextual, in which everyone can be author, reader, documentalist, interpreter, curator, publisher, etc.

Globalization is evident in student exchanges, mobility of professors, increased numbers of international conferences, the domination of international journals, support and grants for cooperative projects and well-known international researchers, etc. Although there are still traditions and references that are purely national or are linked to a particular language, the general trend is toward internationalization of references and theoretical currents.

The past three or four centuries were marked by disciplinary differentiation in the human sciences, starting with the liberal arts, philosophy and theology. Today we are seeing the reverse trend, favoring efforts toward multidisciplinary, interdisciplinary and transdisciplinary convergence. This is obviously only a trend rather than an irreversible abolition of disciplinary compartmentalization. We nevertheless observe that many universities are encouraging students to take transdisciplinary learning paths. In addition, there is a strong demand in programs in communications, education and management, which are transdisciplinary by nature.

The strongest trend is undoubtedly the democratization of the human sciences. This democratization is first of all demographic, since in every country an increasing proportion of each generation goes on to higher education, many of them in the human sciences. Democratization also involves gender, since in most rich countries the female student population now outnumbers, or is on its way to outnumbering, the male student population. Finally, the democratization of the human sciences, and of university in general, affects disadvantaged classes, “lower” castes, formerly colonized nations, oppressed “races”, and in general all ethnic, sexual, linguistic, religious and other minorities. Along with all these forms of de facto democratization, there is a theoretical or ideological democratization that promotes the memory and discourse of the oppressed, the conquered, first nations, and generally all subjectivities purported to have been suppressed by some orthodoxy or power.

Consequently, the basic corpus of the human sciences is no longer limited to the carefully selected classical works traditional elites have used to construct, reflect and refine their individual and collective subjectivities. This corpus is now expanding to encompass all the cultural productions of humanity. The new virtual corpus includes symbolic productions excluded from the list of objects worthy of study by universities (created by the Catholic Church in the late 12th Century) and by the sociocultural groups that for a long time dominated the legitimate production of knowledge about humanity. I note, finally, that the expansion of the corpus and the multiplication of points of view not only affects universities in the Roman Catholic tradition, it is also having an impact on all scholarly traditions, including the Chinese, Indian, Arabic-Islamic, etc.

14.1.2. Agendas and the stakes of power

The path of collective intelligence that I am proposing here for the human sciences recognizes the globalization that is currently under way in the community of students and researchers, the growing need for transdisciplinarity and the opening up of the corpus and perspectives. In the wake of this ideological democratization, I take for granted that any discourse in the human sciences can be interpreted as endorsing a conceptual, theoretical, emotional, subjective, identity-based, economical, social, political or other agenda. It is clear that the performative nature of discourse does not stop at the university gate: power is at stake in all symbolic production. Researchers and teachers, like their counterparts in the media, economics and government, can thus legitimately be subjected to this type of interpretation, whatever their ideological (in the broad sense) or political orientations. What distinguishes the human sciences is not their objective neutrality (what symbolic production could ever make such a claim?), but the explicit, systematic, modeled, reflexive, documented, conversational nature (citations, openness to debate) of their approaches and discourses.

Symbolic cognition is a totally interpretative process. This is the point the human sciences have now reached, and there is no longer any need for demonstration. The problem now for these sciences is to find the way to a reflexive interdiscursivity (a civilized dialog) among traditions or schools of interpretation and to ensure that this dialog, this open collective intelligence, serves human development¹. The IEML model of symbolic cognition offers a solution to this problem: it presents the human mind as a universal, symmetrical, free nature of inexhaustible complexity.

This chapter has two parts. As we will see in section 14.2, when the digital humanities adopt IEML it will become the methodological vehicle of the coming scientific revolution. Section 14.3 offers a philosophical meditation on my main thesis with regard to this revolution, namely that the augmentation of the collective intelligence (and thus the potential) of human communities will come about mainly through explicit self-knowledge.

14.2. Methodology: the digital humanities

14.2.1. The science of collective intelligence and the collective intelligence of the human sciences

Before the IEML model, there was no serious unit of measurement or rigorous scientific method for studying collective intelligence. The few efforts that had been made in this area² were usually limited to selecting a set of indicators and measuring quantities (a “collective intelligence quotient”), while what was needed was to describe the dynamics of systems, patterns of evolution, and models of transformations of forces and values in a universe of ideas in ecological interaction. It is precisely this lack of a scientific method developed to process the semantic dimension of collective intelligence that is remedied by the IEML model.

Most contemporary approaches maintain the traditional distinction between the object studied and the subject studying it, but the aim of the IEML model is reflexive knowledge of collective intelligences by themselves. If we reject the reflexivity of collective intelligence, there is no guarantee that the object being studied (a human group) has not developed cognitive dimensions that completely elude those who call themselves experts in measuring or evaluating it. In contrast, the IEML model incorporates an approach that is radically open, dialog-based and symmetrical (or reciprocal: the object and the subject exchange roles). Indeed, creative conversations are themselves the ultimate source of the functions of categorization, evaluation and association that govern their collective interpretation games³. The image presented to the observer is reflexive. A creative conversation “sees itself” by observing its collective interpretation games in the mirror of the Hypercortex. The different disciplines, hermeneutic traditions and schools of thought of the human sciences can be considered creative conversations organizing and exploiting the digitized data on the Web. Each of these schools, each of these disciplines has an original point of view that is processed symmetrically (without “favoritism”) by the IEML semantic machine. Thus a reflexive, perspectivist, collaborative science of collective intelligence necessarily calls for a collective intelligence of the human sciences.

Before I discuss its methodological vehicle, I will review the epistemological framework and theoretical orientation of the collective intelligence project that IEML offers for the human sciences.

Epistemological foundation. The path of collective intelligence in the human sciences is laid out in a universal nature of the mind that is free and inexhaustibly complex. From the perspective of the IEML semantic machine that simulates collective interpretation games as flows of current in circuits, i.e. as symmetric operational variables, all games are equivalent, each one “equally distant” from the abstract center where the machine is located. Within this perspectivist nature, each cognitive system is in a position to reflect the others from its own perspective. If the IEML semantic sphere is seen as the political constitution of a state, and the cognitive systems as citizens simultaneously exercising their cognitive power in this state, we would have a democracy organized according to the strict principle of separation of powers. With respect to the individual freedom of the citizens, the only power authorized to intervene in the organization of a cognitive system (a method of interpretation or a school of thought) would be the cognitive system itself. With respect to deliberative dialog and collective intelligence, each citizen would have virtual jurisdiction over all the others through the capacity to reflect – and thus interpret – them in his or her own way. The computational power of the IEML semantic sphere makes the large-scale mechanization of this reciprocal interpretation possible.

Theoretical orientation. Once the environment in which the journey takes place has been established, what is the direction of the path the human sciences are being invited to take? I would first of all like to make clear that this is not a linear path from a point A to a point B, but rather the assembling and omnidirectional growth of a self-reflective cognitive state. We start from a situation in which reifying essentialisms fragment the nature of collective intelligence and struggle to interpret (transform into useful knowledge) the oceanic flows of data. Our aim is the expansion of an open public space energized by powerful schools of thought, or scientific creative conversations. These distinct – and even competitive – schools will be able to collaborate in interpreting data thanks to the calculable cognitive perspectivism offered by the IEML semantic sphere. The multitude of creative conversations will build a living hermeneutic memory on the topological framework of the semantic sphere, like the growth of a coral reef illuminating the ocean of data through its myriad intellectual perspectives.

Methodological vehicle. In order to advance this project of civilization, we need technology capable for automating – interoperably – the transformation of data into reflexive knowledge: production and transformation of semantic circuits, categorization of multimedia data, production of semantic currents, production and transformation of noumenal circuits, etc. The interoperability of the semantic automata will be ensured by the common metalanguage of IEML. The specific role of the digital humanities, and in particular of the IEML semantic engineering, will be to provide tools for the creative conversations, schools of thought and cognitive systems in their work of creating knowledge from data.

14.2.2. What are the digital humanities today?

The digital humanities combine computer engineering and the human sciences. They are concerned with methods of structuring and using digitized corpora for the humanities and social sciences⁴. These methods include encoding, applying metadata, data mining and representing data (for example, visually), as well as all forms of collaborative annotation that make it possible to maintain a kind of permanent virtual seminar around a given corpus. The digital humanities also reflect on the impact of their own methods on the cultural legacy and institutions for the conservation of memory, such as archives, museums and libraries. Finally, they study digital culture in general, i.e. the new social and symbolic environment that is developing in the digital medium. Researchers working in the digital humanities are particularly interested in exploring and analyzing the new forms of publishing and reading (for example, hypertext) made possible by the digital medium, including their consequences for research and teaching. It is easy to predict that in a generation – or less – the vast majority of research activities in the human sciences will be computerized, so much so that the expression digital humanities will be redundant.

14.2.3. A new writing that serves the human sciences

Until now, the digital humanities mainly just used or modified the tools provided by engineers to analyze, format and annotate corpora of texts assembled using static writing techniques. Some of the most advanced work in the digital humanities involves the transformation of the genres of book and article into fluid, interconnected, ubiquitous processes of collaborative reading/writing in social media suited to researchers’ needs. This is only the beginning of a process of cultural change that shows no signs of stopping. Indeed, as the digital medium evolves, we can envisage new writing systems that are much more powerful than the static writing inherited from tradition.

IEML is to my knowledge the first example of a new kind of writing (or encoding of meaning) expressly designed to exploit all the memory and calculation resources of the digital medium for the benefit of research in the human sciences. The explicit premise of the research program based on IEML is that the new corpus of the human sciences is nothing other than all the flows and stocks of data on the Web. Thus, IEML can serve as a metalanguage for the categorization of data, the automatic hypertextualization of the data categorized, the arrangement of information in semantic circuits and the automatic calculation of paths and distances among items of information. I recall here that IEML texts are called USLs (Uniform Semantic Locators) and that each USL is a variable of a transformation group the algebraic operations of which correspond to semantic operations. Writing in IEML thus means creating semantic circuits for channeling information flows or constructing data filters or even data mining tools. Reading in IEML means carrying out automated comparative analyses of semantic structures and extracting information on the flows channeled by these structures. In the new intellectual environment established by the IEML semantic sphere, collaboration in research will take the form of organizing collective interpretation games, games whose rules automate the categorization, evaluation and contextualization of data.

14.2.4. The encoding and semantic use of data

From the point of view of the humanities, most great civilizations – or intellectual traditions – are based on (i) a writing system, (ii) an open corpus of “classics” written using that system and (iii) a set of intellectual disciplines that allow the maximum relevant meaning to be extracted from the corpus. As I have already said, the Web is becoming the new corpus of the human sciences. But the Web expresses its data using a multitude of “natural” symbolic systems (languages, static writing techniques, video, music, interactive games, programs, etc.). We have seen that these symbolic systems are disparate, their automatic translation is problematic and their physical addressing (URLs) is semantically opaque. In addition, few of the systems of notation or representation in use today, because of their irregularities, can be processed except by using statistical methods. The main purpose of IEML is the semantic re-encoding of the data of the Web using semantically transparent USLs. This encoding needs to be done freely, openly and collaboratively. Coordinated by the IEML semantic sphere, the Hypercortex builds the operational unity of the new corpus of the human sciences. Far from being standardizing, it is a perspectivist unity, creating symmetrical relationships among a multitude of distinct points of view. IEML is a regular language, the syntax and semantics of which are calculable, which is automatically translatable into natural languages and opens up practically infinite possibilities for the notation of meaning. This symbolic tool should now be used to unify the new corpus of the human sciences (the content of the Web) and increase the possibilities for interrogating and interpreting data.

Logic and statistics are not enough. We will only be able to automate the creation and use of semantic information by drawing on the very ancient hermeneutic legacy of the human sciences⁵. Then, and only then, will humanity acquire some mastery of the symbol-processing potential of computers. Researchers in the digital humanities are thus invited to participate in the development of a new intellectual tradition. The tools and methods of this tradition could be much more powerful than those of previous traditions, because they are based on: (i) the calculating power and memory of the digital medium; (ii) the “social” capacities of human communication and collaboration opened up by this medium; and (iii) the combination – through IEML – of a universal system of notation of meaning and a hypertextual topology structured as a calculable transformation group. For the physical/biological sciences “the great book of nature is written in the language of mathematics”. Geometry is used as a method of decoding the natural phenomenal text. Similarly, for the human sciences progressing toward reflexive collective intelligence, the great opaque hypertext of the Web will be decoded into the transparent hypertext of the IEML semantic topology.

The reader can now glimpse the development of a new intellectual tradition. IEML will be the scholarly writing of that tradition. This intrinsically multilingual and calculable writing automatically weaves semantic relationships among its texts. The public data of the Web constitute the valuable corpus of classics of the new tradition. Finally, creative conversations will act as associated free hermeneuts extracting the maximum relevant meaning from the corpus. The ultimate goal of the new intellectual tradition is to domesticate the calculating power now available so that it serves the reflexivity of human collective intelligence, and thus to pave the way for the civilization of the future.

14.3. Epistemology: explicating symbolic cognition

14.3.1. Reflexive knowledge and non-reflexive knowledge

The civilization of the future that I spoke of above will be universal, but not in the sense of an authoritarian imposition of a doctrine or orthodoxy at the expense of other doctrines. This is an open, not a totalizing, universalism: all the ways of creating meaning belong to the same infinite virtual sphere of the thinkable generated by human symbolic cognition⁶.

This open universalism represents a path of cognitive fecundity that contrasts with two sterile attitudes: a standardizing monism and a divisive pluralism. A totalizing, excluding or imperial monism would “homogenize” the human mind and claim to deduce from the unity of the playing field (symbolic cognition) the exclusive legitimacy of a single rule of the game (a single way of knowing). At the other extreme, a divisive pluralism “essentializes” historical, cultural or existential differences, whether racial, religious, sexual, national, political, theoretical or other. By compartmentalizing humanity, this rigid pluralism excludes certain points of view and impedes reflexive dialog and reciprocal interpretation.

The open universalism supported by the IEML model of the mind is intended to be reflexive, i.e. each step, each operation of the cognitive process can be described explicitly, shared and recognized for what it is: a choice, a freely acknowledged decision among a multitude of other possible choices. Reflexive knowledge corresponds to a perspectivist attitude. In contrast, non-reflexive knowledge, instead of considering the singularity of its own cognitive functioning, projects that functioning on the object of its cognition and declares: “this is the essence of this object”. Non-reflexive knowledge is manifested as essentialist belief. Non-reflection implies a hardening, an ossification of cognition that limits its flexibility, its power, its capacity for adaptation, evolution, learning, innovation and creation, and ultimately weakens or endangers the human group (or individual) that maintains the opacity and the essentialist illusion of its own cognitive processes. In addition, an essentialist attitude increases the number of obstacles to interdisciplinary and transdisciplinary dialog, which everyone agrees the sciences of the mind urgently need in order to solve the problems of human development.

14.3.2. The cognitive process

The truth of a representation consists in the conformity of that representation with reality. We have seen that what characterizes symbolic cognition (at least in the IEML model) is that it creates its reality, particularly the meaning of that reality, on the basis of selection of data and interpretation programs. Within the framework outlined above, a hermeneutic school, creative conversation or collective interpretation game thus cannot claim to hold “The Truth” or even aim for an asymptotic approach to truth understood as conformity with reality. I am not speaking here of the accuracy of data (truth with a small t ), which is obviously a key concern of researchers. I am talking about truth of meaning or interpretation, which necessarily involves conceptual, axiological, narrative and practical decisions. If objective truth cannot be used as a criterion of science, what remains? Are we condemned to sterile relativism? Is there no difference, then, between knowledge and ignorance?

In the new orientation I am proposing here for the human sciences, it is in fact possible to distinguish between scientific knowledge and ordinary knowledge, and even to improve scientific knowledge asymptotically. All that is needed is to adopt reflexivity – instead of truth – as a criterion of knowledge. The IEML model of symbolic cognition makes it possible to break down the cognitive process into steps and examine the degree of reflexivity of each step. In what follows, I will analyze the steps of the cognitive process as logical phases and not as a chronological Toward Explicit Knowledge 333 succession. If I were to adopt a chronological point of view, I would have to describe a looped self-organizing process in which it would be impossible to assign an absolute priority either to the movement of virtualization or to the movement of actualization (see Figure 14.2).

Figure 14.2. The degrees of the cognitive process

14.3.3. Essences: the power of symbolic cognition

Let us first consider the pure and simple capacity to identify symbols or symbolic arrangements. Suppose that for each distinct symbolic arrangement perceived by the senses, the mind conceives a corresponding distinct “essence”. Essences have no particular determination a priori; they are only distinct “places” in which forms or concepts can be distributed. They may be compared to points in a system of coordinates, markers in a symbolic memory or squares in a gigantic intellectual game. Essences are formalized in IEML as sets of sets of sequences of a handful of primitive symbols (USLs). At this stage, essences do not yet have meaning. They are only identification codes. They are, by nature, devoid of any particular interpretation. This is essential because otherwise the human mind would be unable to use a countless number of different symbolic systems or collective interpretation games. With the squares of this cosmic chessboard comes what is, in principle, an unlimited capacity for the interconnection and tracing of paths among their addresses, as well as a programmable mechanism for manipulating the contents of the squares. The gigantic chessboard of essences and the mechanisms associated with it represent a source of inexhaustible but computable complexity. Each essence may be seen as an intellectual micro-mirror that can reflect any concept, and the basic playing field of the mind as a macro-mirror that can reflect or project any system of relationships among essences. Essences are in a sense the pixels of a huge intellectual retina. It is thanks to this retina that symbolic cognition is possible.

14.3.4. Concepts: intellectual cognition

In the second logical phase of cognition, the empty, reflecting squares of the heaven of essences are “occupied” by concepts and are interconnected in a determined way. As we have seen above, no specific concept has meaning in isolation, outside its interdependence with other concepts, whether this interdependence is paradigmatic or syntagmatic. A concept shines like a constellation in the night of essences. In the IEML model, the interdependence of concepts is shown in graphs of explicit relationships or semantic circuits. As soon as essences (cognitive pixels) are semantically defined and interconnected, they reflect concepts. Generally, it is linguistic or other symbolic systems that determine concepts and organize their relationships. The display of meanings determined by the cognitive process results from a conceptual projection against the reflective background of essences. This initial projection establishes the conceptual calendar of a cognitive system: fractal networks and cycles of constellations of meaning. In fact, the determination of the intellectual agenda of cognition often results from a synthetic or syncretic combination of many symbolic systems.

At the level of intellectual cognition, cognitive reflexivity consists in explicitly recognizing the structure of the symbolic system that organizes relationships among meanings. In contrast, non-reflexive knowledge does not recognize its own act of conceptual cognition. The most opaque non-reflexive knowledge imagines that each concept has a meaning separately, independently of its relationships with other concepts, outside the intellectual constellations that define it. Concepts are “essentialized”. Non-reflexive knowledge that is a little less opaque recognizes that the meanings of concepts are interdependent but does not take responsibility for choosing the symbolic system that conditions this interdependence. In this latter case, it is the symbolic system as a whole (for example, a language) that is essentialized, i.e. considered “true”, “objective”, “normal”, etc. In all cases, nonreflexive knowledge consists of imagining that essences spontaneously express determined concepts instead of realizing that they simply reflect the activity of some cognitive system. Each symbolic system – each distinct language – projects different intellectual figures on the retina of essences.

In the IEML model, intellectual cognition is fully explicated by the semantic machine. In particular, the STAR dialect makes it possible to reflect the projection of concepts in natural languages on essences (USLs) with maximum explication, since the process is automated. Thanks to this semantic computability, the conceptual constellations here take the form of a hypercomplex fractaloid – but symmetrical and formally determined – graph: the semantic sphere.

14.3.5. Ideas: affective cognition

Concepts projected by essences in the phase of intellectual cognition are projected in turn on sensory or multimedia data, which I have named with the very general term percepts. This second phase necessarily involves an affective force that functions as binding energy (repulsion, attraction or neutral) between a concept and a percept. It should be recalled that affective force is represented in the IEML model by a current in the circuits of the semantic sphere.

The affective stage of cognition corresponds to a highly complex process that comprises: (i) the production or selection of the percept that gives the idea its sensory content; (ii) the selection of the concept that gives the idea its semantic address; and (iii) the determination of the affective energy that connects the percept and the concept. These three sub-processes are logically simultaneous. The result of this second logical phase of symbolic cognition – an idea – is thus the combination of a percept and a concept under the effect of an affective force.

Some readers will perhaps raise doubts about my modeling of affects using numbers, based on the intuition, which is quite justified, that what is usually called an emotion may be manifested in infinitely subtle or nuanced ways and could thus elude numerical modeling. This doubt originates in the fact that what, in my technical vocabulary, I have called idea is in ordinary, non-technical vocabulary called affect or emotion. In fact, it is impossible for the human mind to feel a “pure” emotion, without any perceptual or conceptual aspect⁷. When we want to emphasize its affective force, we tend to call an idea an “emotion” although it also includes conceptual and sensory aspects. It is the concept and percept of the idea that confer on this “emotion” the 1,000 qualitative and existential nuances that are not contained in the intensity and polarity of the affect. In my technical vocabulary, the affect only designates the force, or semantic energy, of an idea. I recall that the idea is designated in the IEML model by a semantic information unit (see Figure 11.5).

The existential meaning of an idea comes from the affective activity that generates it; an activity in which, according to the IEML model, several distinct hermeneutic functions converge (see Figures 13.3, 9.3 and 7.5). Just as a concept cannot be known independently of the symbolic system that determines it and connects it to other concepts, an idea has no autonomous existence. It gets its reality from the affective cognition that selects, categorizes and evaluates percepts. In the IEML model, affective cognition is described as hermeneutic functions. These functions establish the norms for the categorization and evaluation through which ideas are produced.

At the level of affective cognition, reflexivity consists of explicitly recognizing the functions of perception and thought⁸ that generate ideas. In contrast, nonreflexive knowledge reifies acts of affective cognition. It imagines that things and events, including their meaning, sensory texture and affective value, “exist” in this way (and not differently) independently of the cognitive processes that construct them. In this regard, we could speak of an existential essentialism. Non-reflexive knowledge fails to recognize that essences – which are never anything but empty squares, simple cognitive pixels related symmetrically – reflect ideas dynamically produced by its own semantic and hermeneutic functions. By separating the existence of ideas from the process that brings them to life, non-reflexive affective cognition merges reified ideas with the essences that display them, creating an illusion.

14.3.6. Stories: narrative cognition

Until now I have only described the static aspect of cognition. As we have seen, intellectual cognition determines the conceptual contours of ideas, and affective cognition fills these ideas with sensory content and symbolic energy. In the phase of narrative cognition, ideas are in motion. This third phase corresponds to the functions of thought in Figures 13.3, 9.3 and 7.5). Here, the mind traces virtual journeys or paths of transformation among ideas. This is not movement in ordinary space, but virtual movement in the non-linear, rhizomatic time of memory⁹. Associative links among ideas are constructed by narrative or theoretical mechanisms¹⁰, theory ultimately being only one particular narrative genre. By telling stories, narrative cognition creates a new layer of meaning, a dynamic meaning that could not emerge without an organizing narrative.

At the level of this third logical phase, the reflexivity of knowledge consists of recognizing that the virtual movements of narration – like the functions of thought that drive these movements – are created by the cognitive process itself. A story, in itself, has nothing “true” and has no independent existence outside the cognitive system in which it develops. Narration is a meaning-generating activity and not a neutral recording of “reality”. This is precisely why we cannot do without it. The narrative perspectivism I am advocating here maintains that it is impossible for humans to live in a world without narrative, because only narratives¹¹ allow them to organize their memory, imagine their future as much as possible and orient their action. In contrast, non-reflexive cognition dreams that its narratives are “true” and “represent reality”. Essentialism of narrative or theory results from the opacity of narrative cognition to itself. In this case, a cognitive system refuses to take explicit responsibility for the processes of thought that organize its memory, influence its predictions and push it to make specific practical decisions.

14.3.7. Autopoietic cognition

In the sequential order that starts from the most abstract virtuality and ends with the most embodied actuality, symbolic autopoiesis¹² is the last logical phase of cognition. In its autopoietic moment, cognition identifies itself, designating its biological, technical, social and cultural media. In the case of individual cognition, this medium, the self, consists of the person and his or her attributes: body, possessions, sociocultural networks, genealogy, history, etc. In the case of social cognition, the cognitive process is supported by a complex collective identity, a plural self, or “we”, including both material (organizations, territories, artifacts, etc.) and symbolic (languages, narratives, rules, power centers, etc.) aspects.

Autopoietic cognition circulates in a loop in which the self and the cognitive process generate each other. On one hand, the self conditions the cognitive process, since there can be no cognition without a biological, technical or sociocultural medium. On the other hand, it is through the cognitive process that there is a “self” or a “we” that stands out against the meaning-filled phenomenal world being computed. In determining the identity that is its medium, cognition structures a primordial figure/ground relationship. It draws a circle around part of the dynamic totality it generates and declares: here I am.

Symbolic autopoiesis involves a double suture¹³: “horizontally” between identity and otherness, and “vertically” between body and mind. Horizontally, it distinguishes and unites the self and the not-self. Vertically, it projects itself in the phenomenal or actual world (embodiment of individuals) and in turn expresses its identity in the abstract or virtual noumenal world (individuation of thought). Autopoietic cognition provides the link of interdependence between the development of a human community (at the very least, a single person) and that of its system of interpretation. In other words, autopoietic acts tie the development of cognition to the person who is responsible for the thought: in thinking and acting symbolically, a subject engages him- or herself. If we began to explore the cognitive loop starting from its autopoietic phase, we would see semantic energy spring from autopoietic acts, become virtualized in organized memory through narratives, be analyzed in ideas and outlined in conceptual circuits until it was reflected on the clear, empty surface of essences.

In the phase of autopoietic cognition, the reflexivity of knowledge consists of recognizing a twofold interdependence: one that intertwines the self and the not-self, and one that forms a loop linking the evolution of the cognitive process and development of the self. The reflexivity of autopoiesis, we might say, corresponds to the wisdom discussed in section 13.6. In contrast, non-reflexive autopoietic knowledge essentializes the subjective identities it determines (as if these identities were not computed by the cognitive process itself) and reifies its own cognitive system (as if the main goal of a cognitive system was not to learn to govern the destiny of the subject that produces it). Non-reflexive knowledge imagines here that the practical development of the “self” is independent of its own cognitive activity.

In my view, absolute relativism is a form of essentialism: instead of freezing and naturalizing the image of a “true” cognition or “neutral mirror of reality”, it idolizes a static multiplicity of supposedly equivalent socio-semantic systems without thinking about the interdependence among them or the level of development of the human society in which they exist. Even if relativists acknowledge the open perspectivist horizon in principle, they refuse to explicate the autopoietic dimension of cognition, because that would cause them to break with a status quo elevated as an ideal symmetry and to evaluate their own cognitive choices and those of other human communities in practice. Like a belief in the absolute truth of our own interpretation, absolute relativism ultimately comes down to “that’s the way it is”. It rejects both open complexity and responsibility for a choice rooted in presence.

14.3.8. The dark side of power

In this chapter I wanted to explore some methodological and epistemological dimensions of what could be a “revolution in the human sciences” based on the new tool for observation and coordination that is the IEML semantic sphere. In a sentence: the scientific model of cognition based on IEML, and the hypercortical observatory that uses this model as a tool, are intended to facilitate the reflexivity of symbolic cognition. This does not mean declaring total war on essentialism or opacity. It is probably impossible for human symbolic cognition to be reflected in its totality. If the advancement of knowledge is seen as the gradual extension of a luminous sphere over the complete darkness of ignorance, essentialism represents the shadowy, only partly reflexive edge of the light projected by the fire of symbolic cognition. The dark depths of the unknown are first conquered through a nonreflexive thrust of essentialist projection. It is only starting from this initial cognitive half-light that knowledge opens up into a semantic field in which each light wave reflects all the others.

1 On the concept of human development, see section 5.1.

2 See the work of the Center for Collective Intelligence at MIT: http://cci.mit.edu/'.

3 On the concept of reciprocal anthropology, developed by Alain Le Pichon, see the Transcultura journal: http://transcultura.jura.uni-sb.de/english/index.html.

4 See, for example, [SIE 2004].

5 On this point, see Chapter 13.

6 See my book Cyberculture [LÉV 1997], in which I develop the concept of universal without totality.

7 Just as it is impossible to experience a “pure” concept or percept. Only ideas exist in the mind.

8 Again, see Figure 13.3.

9 See [BER 1896].

10 Once again, these narrative mechanisms are formalized in the IEML Hypercortex as functions of thought; see section 13.5.

11 Whatever their forms and genres, including the elaborate types of narratives we call theories.

12 Remember that autopoiesis is production of the self. The term was used by the Chilean philosopher/biologists Humberto Maturana and Francisco Varela [VAR 1974, VAR 1979].

13 On the concept of symbol as the unifying interface between a more virtual reality and a more actual reality, see section 2.3.4.