Chapter 6

The Information Economy

The information economy is generally understood to mean a particular moment in economic development (the knowledge society or the economy based on knowledge and innovation) or a particular sector of the economy (research and development, communication, education and training, cultural production, etc.). What I am calling the information economy here represents a much broader process. The semantic information economy indeed includes the traditional information economy, but it is not limited to one period or one sector, nor does it stop at the boundaries of the monetary economy. In fact, it encompasses the economy of meaning in its inexhaustible totality and the complexity of its circuits. When he describes the dynamics of exchange in certain primitive societies, Marcel Mauss, one of the fathers of anthropology, is actually speaking of this semantic economy: “Everything − food, women, children, property, talismans, land, labor, services, priestly functions, and ranks − is there for passing on, and for balancing accounts. Everything passes to and fro as if there were a constant exchange of a spiritual matter, including things and men, between clans and individuals, distributed between social ranks, the sexes and the generations”¹. I propose to model this semantic information economy as a circulation of symbolic energy flows (Mauss’s “spiritual matter”) in the channels of the IEML semantic sphere. As we shall see, these flows are regulated by “collective interpretation games” that categorize, evaluate and put into context the digital data the creative conversations have to process.

The purpose of this chapter, which completes Part 1 of this book, is to present what could be the object of a renewed human science; that makes full use of the all-inclusive memory and calculating power of the digital medium through the adoption of a common system of semantic coordinates. This unique but open object of the human sciences is none other than the information nature discussed in Chapter 2. It is an information nature that is reflected simultaneously in large numbers of collective interpretation games, with these games, each in its own way, attributing a value to information. In other words, the information economy is an information nature that is not only addressed in the space−time continuum but is also categorized and assessed in the IEML semantic sphere. The semantic information economy must therefore be understood as a common framework for modeling ecosystems of ideas, a convention that would not only provide tools for use in creative conversations, but also make it possible to provide a scientific account of their diversity and interdependence. This project is not only contemplative. The capacity to effectively model the semantic information economy in the digital medium will transform the Internet into a Hypercortex that reflects collective intelligence. By making the semantic information economy visible, and thus increasing the cognitive potential and cooperative capacities of creative conversations, the Hypercortex will take us to a new level of civilization.

The general plan of the Hypercortex, including a formal model of the semantic information economy, will be presented in Part 2 of this book. In this chapter, I will outline the philosophical orientations on which this formal model is based. Section 6.1 offers a reflection on the cognitive labor and knowledge capital of the information economy from the perspective of the cooperative management of knowledge considered as a common good. Section 6.2 provides a survey of some of the pioneering work on the information economy, the knowledge society and collective intelligence in the field of economics. It also discusses the inadequacy of the tools now available for modeling the processes of collective intelligence in their semantic and self-organizing dimensions. Section 6.3 deals with the flows of symbolic energy among ideas, or the semantic current, considered as the general equivalent of the information economy. Then section 6.4 discusses the concept of the ecosystem of ideas. The chapter ends with a discussion of the “global brain” and the information economy in the digital medium.

6.1. The symbiosis of knowledge capital and cognitive labor

6.1.1. The genealogy of capital

I believe that, far from being a mystery, the capacity of capital to grow and reproduce is a property that defines the very concept of capital in a way that is quite natural. My understanding of the word capital is based on its etymological meaning of “cattle” (in Latin, caput, capitis): several head of cattle. Capital originally consisted of a living domestic population that was capable of reproduction and could be improved by artificial selection. If the archetype of capital is the herd, that of labor is the activity of shepherds, cowboys or gauchos. To the tribe of herders that leads it to the best pastures, influences its development through careful crossbreeding, protects it from non-human predators and tends to its newborns, the herd in return supplies its fat, meat, bones, hides, hair, milk, manure, warmth and animal strength to carry people and goods. Capital and labor are in a relationship of interdependence: the life of one depends directly on the life of the other. We could say that the herd of animals and the human tribe form a symbiotic unit. Thanks to their association, they are able to survive and reproduce better in their common ecological niche than they could have done separately. Domestication has been beneficial to both partners − as in any symbiosis − and not only to the humans: the huge populations of the plant and animal species domesticated by humans now represent a burden for the biosphere.

Let us now substitute a knowledge network (an ecosystem of ideas) for the animal herd, and a community of communicating thinkers (a creative conversation) in the knowledge society for the tribe of herders. Bear in mind that capital and labor have a symbiotic relationship. In other words, knowledge itself, on one hand, and the activities of symbolic cognition that the members of the community engage in and that “give life” to this knowledge, on the other hand, are complementary aspects of a single autopoietic, self-organizing, evolving and fragile process: that of the semantic information economy.

The interdependence of knowledge needs to be seen in terms of its temporal dynamics. Knowledge is received from a tradition and must be retransmitted. The primary goal of the labor of collective intelligence is thus to reproduce the ecosystems of ideas. Then these ecosystems must be improved through controlled change by means of selection and cross-breeding. The criteria for this additional value or power, which is the purpose of selection, obviously depend on a variety of contexts and changing conditions. Despite this, the guiding principle remains relatively simple: the living knowledge maintained, reproduced and improved by a community must return useful information². This is the heart of the symbiotic process: a population of talking primates maintains and refines the reproduction of its cognitive capital in the semantic sphere only if the knowledge ecosystem in turn helps to reproduce and maintain the well-being of the actual human bodies living in the biosphere. Ecosystems of ideas must thus help maintain the biophysical ecosystems of the communities that support them (agriculture, industry, management of biological ecosystems), improve their material situation (safety, health, etc.) and satisfy their spiritual need for meaning in their lives and world (mutual trust, aesthetic or religious organization of life). Human development and collective intelligence are in a reciprocal relationship.

I spoke of tribes of herders to highlight the original, founding, ancient pact that links virtual knowledge ecosystems to human populations. The talking primates cannot survive without culture; similarly, the ecosystems of ideas that give shape to this culture can only be reproduced in symbiosis with the desiring, suffering and mortal bodies of the social mammals that support them. To look at this another way, maybe we should think of the ecosystems of ideas as the ones “raising” communities of talking primates by reproducing and diversifying them…

6.1.2. The commons: the interdependence of human populations, ecosystems of ideas and biological ecosystems

The symbiosis between knowledge capital (ecosystems of ideas) and cognitive labor can be viewed as an expanded loop of interdependence that includes the biological ecosystem.

Since the early 21st Century, in the conversations that are weaving together the new global public space, people have been speaking of a commons. This rather broad term designates both public goods whose consumption by some people takes nothing from others − such as sunsets and useful knowledge − and shared resources that could be depleted by overexploitation or damaged by lack of maintenance by some members of the communities involved – such as irrigation systems and public libraries³. This economic concept originally designated the unappropriated part of an ecosystem of a human community that used it for direct harvesting (hunting, gathering and wood cutting in forest) or herding (in pasture). British historians often speak of the “enclosure movement”, led by noblemen and large land owners starting in the 16th Century, the main effect of which was to reduce the British commons drastically and pave the way for capitalism.

The link between the concept of the commons and that of the ecosystemic environment has been confirmed in the present day. Drinkable water, breathable air, a livable climate and biodiversity are surely all common goods, and we urgently need to find appropriate methods of management for them. In this case, it is not only fences around private properties that are threatening the sound management of the commons of the biosphere, but also national boundaries.

There is another commons that is as global and essential to organized human life as the diversified balance of the biosphere: that of knowledge. To avoid any misunderstanding, I should say that I do not mean only scientific knowledge sanctioned by the academic establishment, but also the knowledge and know-how of many traditions or communities of practice⁴. In addition to their global transversality and the fact that they are an infrastructure essential to social life, I would like to point out a third characteristic shared by these two major types of commons: they are dynamic, evolving, interdependent systems made up of large numbers of autopoietic cycles and intertwining feedback loops. Indeed, the shared knowledge of human societies forms something like an inclusive environment within which many ecosystems of ideas interact. Like collective intelligence, of which it is one aspect, the community of knowledge may be viewed at many levels, from the small work team or personal social network to the entire species, including businesses, schools and universities, cities and regions, social media and virtual communities on the Internet.

I would now like to examine not only the similarities between ecosystems of ideas (the noosphere as manifested in the information economy) and biological ecosystems (the biosphere), but also their differences and their looped coproduction. Interaction with the biological ecosystem is obviously not unique to hunter-gatherer or agricultural societies. Industrial and post-industrial economies are also ways of managing and transforming the “nature” of the biosphere: what changes is the quantitative scale (much more massive) or the degree of refinement (bio- or nanotechnological) of its transformation and harvesting. This being said, one of the main differences between the biological ecosystem and the epistemic ecosystem is that the former provides us with drink, food, clothing, warmth and shelter (i.e. material, concrete things), while the latter provides us with information or even just methods of interpreting information. This observation needs to be corrected immediately by adding that most of the materials we extract from the biosphere can only be harvested through the mediation of our knowledge of it and our technical know-how on using it⁵. Granted, some of our shared knowledge (for example, literature and psychology) is not directly related to the exploitation of animal and plant species, the oceans, the soil and the subsoil. But knowledge is interrelated in the complex, interdependent network of culture, so that in the end the knowledge ecosystem as a whole contributes to the mapping of our material interactions, guiding our maintenance of the biological ecosystem and our modeling of our harvests of its flows and stocks⁶. The two major types of commons are thus closely interdependent.

The collective capital represented by the biological ecosystem is in fact defined by the epistemic ecosystem that enables us to analyze, maintain, improve and exploit it. We do not live in the same “nature” as hunter-gatherers because we do not decipher it according to the same codes and we exploit it in very different ways. As for the common capital of knowledge, it only becomes meaningful in the network of material, economic, technical, and other interactions we maintain with the biological ecosystem. Humans are in a way the central interface where the biological and epistemic ecosystems, the biosphere and the noosphere co-define each other. Seen from another perspective, our common capital of knowledge is the cognitive medium that gives us access to our physical/biological environment.

6.2. Toward scientific self-management of collective intelligence

6.2.1. Political economy and collective intelligence

The information economy largely inherits its objectives from the political economy. Economics deals, in general, with the mechanisms for the production, exchange and consumption of value in human societies. This science of exchangeable “goods” continues a whole tradition of ethical thought. For example, before The Wealth of Nations, Adam Smith wrote The Theory of Moral Sentiments⁷. Prior to the development of political economy, Medieval Latin theology at the time of Duns Scotus already saw itself as pragmatic, as the art and science of the production of “good” in the world⁸. In the writing of Adam Smith, the market is seen as a kind of autopoietic collective intelligence. Due to the spatial and temporal scale of this intelligence, and because humans are not equipped to integrate large quantities of disparate data into a coherent whole, the holistic or ecosystemic functioning of the market usually remains unknown to its agents (sellers and buyers); hence, the famous “invisible hand” of the market.

In a famous passage of Grundrisse, Marx speaks of a mysterious “general intellect” that seems to be based on Aristotle’s agent intellect⁹, Rousseau’s general will and Hegel’s objective mind: “The development of fixed capital indicates to what degree general social knowledge has become a direct force of production, and to what degree, hence, the conditions of the process of social life itself have come under the control of the general intellect and been transformed in accordance with it” (the words in italics are in English in the German text)¹⁰. Since fixed capital essentially designates the lasting material infrastructures of production, in particular machines, Marx seems to be saying here that the level of knowledge − or collective intelligence − achieved by a society, in being materialized in the complexity of its machines, organizes and reorganizes the process of production and, consequently, social functioning in its entirety. The concept of machine could obviously be extended today to include communication protocols and software, and the “process of production” could also be extended to processes of communication and distribution¹¹.

Beginning in the 1930s, Hayek, even more explicitly than Smith, analyzed the market as a system (an imperfect system), coordinated everywhere (but not centralized), for transmitting information on the knowledge, needs and behaviors of its actors¹². A computer scientist would recognize this as a system of coordination among agents possessing the same privileges but carrying different data. It should also be pointed out that while Hayek was a fierce defender of private property in general, he considered knowledge to be a common good. This is why he was in favor of the liberalization of intellectual property.

Starting in the 1960s, many economists began to speak of an information economy, and even a knowledge-based economy, to describe the contemporary economy. Fritz Machlup (1902-83), an economist of the Austrian School who made his career in the United States after fleeing the Nazis in 1933, was probably the first economist to undertake a thorough study of the production and distribution of knowledge as a specific economic sector¹³. After Machlup’s work, the second extensive study specifically dealing with the information economy (as opposed to the “material” economy) was carried out by Marc Porat and Michael Rubin in 1977. Porat is also credited with coining the term information economy¹⁴. During the same period, Czech philosopher Radovan Richta (1924-83) was one of the first generalist thinkers to describe, in a multidimensional and interdisciplinary way, the new era marked by the extension of intellectual labor and the acceleration of scientific and technical development¹⁵. Richta is also credited with the famous expression “socialism with a human face”, one of the phrases used in the Prague Spring in 1968.

Building on Simon’s work¹⁶ and game theory¹⁷, the new school of cognitive economics represented in France by Bernard Walliser, takes the cognitive activity of economic agents as the starting point for its theories. It seeks to explain the economy as a whole, including the role of institutions, through games of coordination and convergence¹⁸. At the other end of the political spectrum, the work of Yann Moulier Boutang on “cognitive capitalism” attempts to describe (from a Marxist, but enlightened and critical, perspective) the new “mode of production” based on creativity and the intensive use of knowledge, and is thus consistent with work on the knowledge society¹⁹.

The increasing importance of research on cooperation in the maintenance and management of shared knowledge capital was emphasized by the awarding of the Nobel Prize for Economics²⁰ to Elinor Ostrom²¹ in 2009. Finally, I must mention one of the foundational works in the recognition of a new economic era based on information management, The Information Age, by sociologist Manuel Castells, published at the end of the 20th Century²².

6.2.2. The autopoiesis of collective intelligence

As we have seen, there has been a whole tradition in political economy that revolves in one way or another around the question of collective intelligence, a tradition passing through Hayek and going back to Adam Smith, which analyzes the market itself as a particular form of collective intelligence. Other economists consider the shared capital of knowledge and its collaborative management as an essential dimension of economic prosperity. Many economists, sociologists and philosophers have perceived the emergence of a new knowledge economy since the 1960s. Human development in general, and economic prosperity in particular, require the intensive use of knowledge. In other words, the collective capacity to create, exchange, assimilate and apply knowledge is one of the main engines of development. This is the watchword of the knowledge society. Finally, as we saw in section 4.2, the new field of knowledge management (KM) is being actively explored in management sciences, and since 2005 there has been a shift toward the open, collaborative and “bottom-up” forms of KM developing in the social media.

The period beginning in the 1960s was marked by the proliferation of electronic media world-wide as a result of the acceleration in the pace of production and obsolescence of knowledge, the international explosion (still under way) of universities, the ongoing growth in the volume of information exchanged and stored and, accordingly, the critical role of knowledge and information management in economic, social and cultural life. The more the success (whatever its definition) of a community depends on its creative management of knowledge − as is the case today − the more crucial the capacity to think together becomes²³. Consequently, there is a causal relationship between the effectiveness of a community’s collective intelligence and its capacity to solve problems of human development according to its own point of view. I would wager that, in the global civilization that is now emerging, collective intelligence − or wisdom − will be recognized increasingly explicitly as the driving force of human development, and human development − the improvement of people’s lives and the fulfillment of their potential − will be seen as the essential condition for the growth of collective intelligence²⁴. I therefore postulate that there is an intrinsic relationship between collective intelligence and the information economy, both in the general meaning of this term and in the special sense of a traditional monetary economy especially oriented toward the processing of information in the knowledge society. From the more general perspective, the two terms are almost equivalent: for each form of the information economy there is a specific corresponding organization of the collective cognitive system. The information economy is to human symbolic cognition what ecology is to the biosphere. From the more limited perspective, which is also more practical, the power or richness of collective intelligence is becoming the main factor of success in the information economy²⁵. In this case, the main aim of collective intelligence is creation, invention, discovery, innovation and learning, i.e. everything that contributes to maintaining and growing the shared capital of knowledge, which in turn sustains human development²⁶.

6.3. Flows of symbolic energy

6.3.1. The problem of the general equivalent

We have seen that, unlike the animal societies that preceded them in evolution, human societies maintain complex cultural worlds − ecosystems of ideas − that connect large numbers of symbolic systems: languages, technologies, kinship systems, religions, laws, political systems, organized knowledge, skill traditions, music, literature, etc.²⁷. These symbolic systems communicate to conduct (as we say a copper wire conducts electrical current) the meanings that connect and support speaking beings. These meanings go through interlinked cycles that disintegrate or become amplified depending on whether they are approaching or moving away from the constraints of viability and balance of the ecosystems of ideas in which they participate.

If we want to study this economy or ecology and trace its circuits of transformation and exchange in a shareable way, we must assume that in all the transformations and movements of meaning, something, some value, a force of attraction or repulsion²⁸, is preserved, created or lost. If this were not the case, we would not be able to talk about ecology or economics. No systematic or general knowledge would be possible, because no evaluation, no measurement, no proportion, no transformation, no exchange could be established. What then is the nature of this equivalence relationship − which is something like a currency of meaning − among the forms of symbolic human life? What is this energy whose circulations and metamorphoses generate the evolving diversity of cultures?

6.3.2. The power of mana

Nietzsche, and after him Foucault, spoke of the circulation of this power, which they saw as directed naturally toward growth. I will explore this question by drawing on another tradition, that of French anthropology going back to Émile Durkheim (1858-1917) and Marcel Mauss (1872-1950), and its most distinguished contemporary representative, Claude Lévi-Strauss (1908-2009). In Lévi-Strauss’ remarkable Introduction to the Work of Marcel Mauss, which summarizes the main teachings of his predecessor, the master of structuralism presents the hypothesis that any society can be analyzed as a complex symbolic system of circulation and exchange, producing “the fundamental terms of an equilibrium, diversely conceived and differently realized according to the type of society under scrutiny”²⁹. I want to emphasize here the concept of equilibrium, which clearly shows the analogy with the approach used in the natural sciences, and in this context refers to the dynamics of an economy or an ecosystem. For Lévi-Strauss, one of the goals of scientific anthropology is to describe social functioning as “a system, among whose parts connections, equivalences and interdependent aspects can be discovered”³⁰. His approach in scientific anthropology is not far from that of the semantic information economy. If the very essence of the social system is symbolic exchange and its interlinked cycles of reciprocity, then the parts of the system should be as mutually comparable, substitutable and transferable in our scientific models of culture as they are in culture itself.

Inspired by advances in linguistics (which he continually cites as an example of scientific process in the human sciences), fascinated by the birth of information theory and cybernetics³¹, confident about the contribution computers could make to research in the social sciences³², and firmly convinced of the unity of human nature, Lévi-Strauss maintained that it was possible to discover regularities in the symbolic universe. If I translate Lévi-Strauss’s conviction into my own language, it would mean that unity of the human sciences is possible. It should be possible to reduce the objects and operations of the systems of symbolic exchange that constitute human cultures to a small number of operations and universal types specific to the ecology of ideas − or the information economy − opened up by language. Just as physics has its elementary particles and chemistry its elements, just as all the diverse forms of life are encoded using the four nucleobases of DNA, just as a language can “say anything” by combining a couple of dozen phonemes according to complex rules at many levels of articulation, just as the various languages of the world use common syntactic universals that define the human capacity to articulate thoughts, in the same way, every culture must combine a finite number of symbolic universals according to shared rules to produce the inexhaustible combination of arrangements, rearrangements and permutations that generate cultural diversity.

The Elementary Structures of Kinship (1949) is Lévi-Strauss’s response to The Elementary Forms of the Religious Life (probably Émile Durkheim’s masterpiece, published in 1912). The lineage is obvious in the quest for the elementary, and it continues in the study of the relationships among elements. Since social reality is a structure of exchange – exchange of women, exchange of goods, exchange of messages, but always exchange of value – it is essential to understand the nature of this value that can take so many different forms. In The Gift, Mauss, returning in a sense to before the separation of the disciplines of the human sciences, shows that the cycles of circulation of gifts in certain primitive societies constitute a “total social fact”. The value transferred in operations involving gifts, in Mauss’s analysis, is indissociably moral, economic, political, legal, religious, etc. The Gift thus gives us a glimpse of an elementary, or fundamental, operation that did not emerge from any particular sphere of cultural life, but that weaves together the social fabric in its entirety.

The quest to identify the universal operation of symbolic life repeatedly encounters the strange concept of mana. Indeed, Mauss and Durkheim, in their explanations of religion, magic or gifts, use a variety of terms borrowed from indigenous languages – mana, hau, wakan and orenda – terms that all have the same general meaning: a vital elementary energy or power of a magical or religious kind. Taking up the concept of mana, Lévi-Strauss claims that all cultures – including the most evolved and the most contemporary – have concepts of this kind and that they correspond less to “archaic beliefs” than to the idea of a neutral symbolic value that precedes any qualification. In French, for example, the word truc, according to etymologists, is derived “from a medieval term which signifies the lucky move in games of skill or games of chance, that is, one of the precise meanings given to the Indonesian term in which some see the origin of the word ‘mana’”³³. As for the French word machin, behind it there is “machine and, further back, the idea of force or power”³⁴. In his reflection on mana, Lévi-Strauss distances this term from its association with “primitive mentalities”. It is no longer the multiform spiritual force that animates the cosmos of the archaic societies described by Mauss and Durkheim, but a symbolic value that has not yet been qualified, a quantum of informational energy. The function of notions like mana is “to enable symbolic thinking to operate despite the contradiction inherent in it”³⁵. Since any symbolic value has meaning only in exchange, it would therefore designate an indeterminate capacity for exchange, an unknown in the relationship system. Not such-and-such a value, but value itself, a “floating signifier”, to use Lévi-Strauss’s term. Mana is in a sense “whatever”, x, the fundamental variable for the calculation of exchanges in the information economy: something as its monetary value.

At this point, I myself am taking up the concept of mana, which the author of The Savage Mind took from Mauss and Durkheim and gave another meaning, and I am making an additional hermeneutic translation by posing the question of measurement. If the quantum of symbolic energy were to be measured, the unit of measurement – the currency of account – would have to transcend the established (conventional) social distinctions between economic value, moral value, political value, religious value, aesthetic value, etc., precisely in order to be able to describe the circulation among the different spheres of value. Let us return to the classical example of the gift. At least at first glance it involves a double transfer of value: a transfer of economic value in one direction and a transfer of sociopolitical value – prestige – in the opposite direction. The act of the gift itself establishes a difference of potential, an imbalance, an asymmetry (debt, difference of prestige) that calls for new flows of mana, complementary movements that can be direct, transitive or deferred along invisible, complex paths. Cultural life can be described as a symbolic economy – or ecology. Thus we can justifiably say that peoples that practice potlatch are circulating mana in their society by exchanging their ritual gifts, not because their “belief” in the existence of magical/religious forces associated with the gifts is “true”, but because this circulation of energy in a network of semantic transformations provides the thread that weaves the fabric of the human society.

6.3.3. The complete circuit of information

The economy of material goods is only part of the circuits of the symbolic economy of exchanges of qualities and quantities of all kinds in a complex system of reciprocal cycles in a metastable equilibrium. The classical monetary economy is fuelled by an open totality that it fuels in turn. Contemporary research into the close correlation between social capital (sociopolitical values) and education level (cognitive values), on one hand, and economic prosperity (market values) and public health (well-being values) on the other, seems to confirm that all the types of values are expressed and exchanged within a single symbolic ecology.

What should this mana, this energy, this affective current that flows and is transformed in the transverse circuits of the symbolic ecology be called? Always identical under the infinite multiplicity of the changing meanings it carries or crosses, this strange fluid may be called the force of meaningor symbolic energy, or in more traditional economics language, service, value or good. We may also conceive of it as a force that shortens (attraction) or lengthens (repulsion) the links connecting the nodes of the semantic sphere: the energy of meaning distorts a semantic topology.

Indigenous peoples called this joker or chameleon that takes on different qualities depending on the semantic zones in which it circulates mana. We can also draw analogies with the energy of karmic causality in the traditional philosophies of India, which clearly cuts across established separations. Traditional Chinese philosophies also recognize a unitary life force, whose unceasing flow crosses the cosmos, the meridians of the human body and the library of scholars simultaneously: the qi that links yin to yang, and sky to earth.

Rather than use the term mana, qi or symbolic energy for this currency or general equivalent of symbolic exchanges, I have chosen to call it semantic current, because the type of calculable modeling that characterizes the information economy calls for a neutral expression.

6.4. Ecosystems of ideas and the semantic information economy

As we saw in the introduction to this chapter, the semantic information economy must be distinguished from the information economy in the narrower sense used by economists³⁶. Economists study the role of information and knowledge in the traditional monetary economy: the production and communication of information as a sector of the economy or the contemporary economies of the most developed countries, which are based on the optimal use of information and knowledge. In contrast, the semantic information economy is concerned with the modeling of social processes of symbolic cognition, in the sense of the dynamics described in Figure 5.1.

6.4.1. An “eco” paradigm for thinking about semantic informatione

6.4.1.1. Etymology and general approach

To understand the semantic information economy, we need to remember the etymological meaning of the word economics. In Ancient Greek, oikonomia means law or rule (nomia) of the house (oikos). The word house here should not be understood only in the sense of materials, physical space and architecture. The “house” whose laws the science of oikos aims to understand is a symbiotic unit, a network of interdependent, perishable coexistences whose survival and growth depend on following certain rules. Eco-nomics and eco-logy are the two major sciences of the “house”. For both, the rules governing them ultimately involve (i) mechanisms of growth and differentiation and (ii) constraints on viability. In continuity with these sciences, the economics of semantic information aspires to the level of the new object now observable in the digital medium of human symbolic cognition. The goal of this general economics is to model, observe and understand the functioning of the “houses”, the information environments and digital environments inhabited by creative conversations. Thus, the agents of the semantic information economy are also its inhabitants, and it is impossible to dissociate the two, except conceptually.

The semantic economy provides a dynamic representation of the circuits of production and use of information in shared meaningful contexts. As the agents of this economy (the creative conversations) are also its inhabitants, however, its modeling only takes on its full meaning in a reflexive loop, a little as if the informational “house” that contains them were holding up a metalinguistic mirror of the actions of communities in real situations and the effects of those actions on the communities.

6.4.1.2. Distinction between unity and uniformity

The ecosystem paradigm of the semantic information economy offers many advantages for the study of human symbolic cognition. The first is that it highlights the unity of the human phenomenon. As we saw in Chapter 5, sciences such as economics, sociology and psychology each study an aspect of cultural life. Specialization is obviously indispensable for any scientific work. It imperceptibly directs thinking toward the reification of divisions originally created for reasons of method or practical utility, however, and we come to believe that there is objectively “an economy” (for example), when originally we only intended to analyze the economic dimension of the “total social fact”³⁷. I therefore do not believe that it is this useful disciplinary division that prevents effective cooperation among the human sciences, but rather the absence of a principle of modeling or a common metalanguage that would enable the different subjects to come together and coordinate their activities. There is a caveat. Unification does not mean uniformity. This is where the second advantage of the ecosystem paradigm becomes evident: the concept of an ecosystem makes it possible to think simultaneously about interdependence in a single territory (unity), the diversity of species (multiplicity) and evolution (change). When we talk about the unity of an ecosystem, we mean that changes affecting one species affect the others. Changes have impacts on various balances, over complicated cycles, at many temporal and spatial levels. The fact that the Atlantic Ocean or the Amazon rainforest forms an ecological unit in no way implies that they are biologically uniform; quite the contrary. The functioning of an ecosystem implies dynamics of interrelations within the diversity of organisms and species. What would we think of a biologist who attempted to explain a whole ecosystem by studying only the plants? Or one who placed insects and birds at the center of the forest? Or one who only looked at mammals? Well, this is exactly how things stand in the study of human societies, because each discipline only explores a certain kind of idea, a certain portion of the general cycle of the transformation of information.

While studies today are most often limited to analyses of small bits of the disciplinary circuits as divided up by the human sciences, the perspective opened up by the semantic information economy makes it possible to follow the totality of the cycles of transformation in the symbolic universe. By taking all the objects of the human sciences as its field of observation, the information economy could redistribute the bodies and functions of culture and reveal its living unity and abundant diversity. That would in no way prevent its researchers from defending rival theories or studying different objects.

6.4.2. Ecosystems of ideas in epistemology

The ecological paradigm emphasizes the evolving, systemic, self-organized nature of distributed cognitive processes. The notion of an evolving ecosystem of ideas, which is very close to our concept of the semantic information economy, was developed by important contemporary thinkers. Alfred North Whitehead (1861-1947) devoted his books Science and the Modern World and Adventures of Ideas to the subject³⁸. In Les Idées, Volume 4 of La Méthode, Edgar Morin analyzed ideas as living entities in ecological interaction³⁹. In the same vein, the great epistemologist Karl Popper (1902-94) postulated the existence of three distinct worlds: (1) that of material phenomena; (2) that of mental states; and (3) an objective universe of scientific ideas, where problems, theories and empirical tests come together and vie with each other. According to Popper, scientists’ problems, conjectures and refutations are part of an evolving dynamic in which problems may be seen as environments in transformation, new hypotheses as cognitive changes, and refutations as agents of selection⁴⁰. This “World three” of intelligence, which stands above the worlds of souls and matter but obviously draws from them, leads us to think of distributed human cognition as the circulation of information between (1) material phenomena, (2) mental states of talking primates and (3) a world of objective ideas that follows symbolic, conventional rules.

In comparison with the theories I have cited, the modeling of ecosystems of ideas based on the IEML semantic sphere is distinguished by its calculability and its much more precise relationship with observable phenomena. This modeling is calculable because the ecosystems of ideas, properly encoded in information circuits between USLs, become completely explicit and can be used in open source, shareable computer simulations. The phenomena represented by these semantic circuits are none other than the public data of the Web. Here again, the relationships between URLs (the “physical” addresses of data on the Web) and USLs (metadata or semantic forms of ideas in IEML) are completely explicit and can be represented by functions⁴¹. The formal modeling of ecosystems of ideas in the Hypercortex coordinated by the IEML semantic sphere will be dealt with in Part Two of this book. Before coming to that, I would like to discuss the general characteristics of ecosystems of ideas in terms of the research program on the semantic information economy. This will permit me to review certain concepts discussed in Chapters 2 and 3 and thus dissipate any remaining theoretical misunderstandings that could interfere with the reader’s comprehension.

6.4.3. General characteristics of ecosystems of ideas

6.4.3.1. Ecosystems of ideas live in interdependence with human populations

Ecosystems of ideas can only endure, reproduce and evolve in symbiosis with societies of talking primates. A car, a poem, a queen or a company has an ideal dimension, because such entities cannot exist in the cognitive systems of other primates and because they play an active role in human society. There is no queen for an ant as there is for a subject of the United Kingdom. The ant certainly has a form of phenomenal inner life that allows it to reflect visual, auditory, tactile and olfactory forms. But the ant does not obey a queen (the category itself depends on complex systems of cultural categories); it is controlled by muscle reflexes responding to the sensory reception of pheromones, somewhat as our neurons, taken in isolation, respond to electrical and chemical excitation in ways that are complex but reflexive, almost automatic. Thus an ant no more has ideas than a neuron does. Ideas exist in the metareflexive loop opened by linguistic symbolization, of which only human beings participating in a culture are capable.

6.4.3.2. The world of ideas is not separate from the sensory world

Ideas belong fully to nature. Of course, they are not material things (at the same level of encoding as bodies or neural dynamics)⁴², but nor do they exist “elsewhere”, as if the ideal world were “another world” completely separate from the sensory world. I say that ideas participate fully in nature⁴³ because they exist among the information circuits generated by the cognitive activities of living human beings; activities that they in turn condition.

Plato, the great inventor of the world of ideas, contrasted eidos (“idea”) with eidolon (“image”), and intelligible reality with illusory perception. The Greek language, however, reveals the proximity of idea and image: both are “forms”. The former is a structure grasped by reason, the human discursive faculty, logos; while the latter is a structure apprehended by the senses. We know today that discursive cognition and phenomena are closely intertwined and interdependent. Even the most abstract concept only becomes meaningful within a logical, semantic and, especially, pragmatic ecosystem in which sensory intuitions abound. Likewise, there is no perception that is not primed by expectations, projections and hypotheses. The phenomena we perceive are thus saturated with concepts, ideas and theories, and they are scripted through our narratives. The sensory images of our everyday experience are organized by learning, habits and categories; a whole cognitive and cultural infrastructure.

The same brain, at the same instant, computes abstract meanings and sensory images, the meaning of a text and the radiance of a smile. The living idea that emerges in our cognitive systems thus interweaves categories, emotional intensities and sensory data in a single complex information circuit.

The ideas of the semantic information economy link sensory data and discursive cognitive processes. Modeled in IEML in the Hypercortex, ecosystems of ideas circulate a symbolic current between a virtually infinite semantic sphere, on the logos side, and the practically unlimited multimedia memory of data on the Web, on the sensory side. I will go into greater detail on the Hypercortex of the semantic information economy, which weaves together discursivity and sensory activity, in Part Two of this book. For now, let us bear in mind that the semantic information economy implies no metaphysical separation. It does not choose mind (i.e. symbolic manipulation) over matter, or matter over mind. It models their reciprocal implication, the indissoluble link that reflects the symbiosis between societies of talking primates and their information economy.

6.4.3.3. Ecosystems of ideas evolve

Ecosystems of ideas are constantly evolving. Memetics⁴⁴ tends to focus on a short-term selection of small units: the ideas that reproduce are those most capable of attracting the attention of humans. Thus memeticists often cite the example of hit songs, refrains and jingles that we are unable to get out of our heads once we have heard them. I would tend, instead, to emphasize the long-term (the unit of time being a generation), macro-level selection of ecosystems of ideas. Cultural evolution selects the ecosystems of ideas that enable the human populations that maintain them to better survive and prosper in a given historical and geographic context. Of course, according to this approach, there are no “good” ecosystems of ideas – much less “good” ideas – in an absolute sense. The competitive advantage one idea has over another is necessarily related to its role and its interactions in a given ecosystem: one idea is “better” than another insofar as it is more cooperative in the ecosystem in which it participates, i.e. if it increases the reproduction of ideas in the same culture. Neither general relativity nor human rights would have been good ideas in Pharaonic Egypt.

Certain ideas can be very successful in the short term (they are reproduced massively in minds) even though they drag the populations that adopt them into economic impoverishment, military disaster or cultural sterility in the long term: we could say that they are not sustainable. Moreover, an ecosystem of ideas that gives a competitive advantage to the population that maintains it in a given historical context could cause it to lose that advantage in a different context. For example, the writing, architecture, religion and political system in Egypt in the time of the Pharaohs gave the populations living on the shores of the Nile a competitive advantage over the nomadic and less organized tribes around them. After 3,000 years of successful symbiosis with a human population, however, the ecosystem of ideas of Pharaonic Egypt was not able to withstand⁴⁵ its encounter with Greek, and then Roman, civilizations, both of which were based on other writing systems, political systems and religions.

6.5. The semantic information economy in the digital medium

6.5.1. The prophets of media and the “global brain”

In the past 40 years, and increasingly in the past 15 years as a result of the development of the Internet and growing recognition of the knowledge economy, and independently of the work of anthropologists, epistemologists and economists, there have been many books on a semantic information economy describing the functioning of human societies in terms of a distributed cognition that is reflected and unified in the digital medium. As early as 1964, Marshall McLuhan wrote: “If we expanded our central nervous system to the electromagnetic technology, it is only one step more for the transmission of our consciousness also into the world of the computers”, and “our current translation of our entire lives into the spiritual form of information seems to make of the entire globe, and of the human family, a single consciousness”⁴⁶.

I myself came to the semantic information economy through the investigation of collective intelligence, i.e. the structure of the collective cognitive system, or cognitive ecology, formed by human culture in its media environment⁴⁷. The emerging collective intelligence of the digital network has also been discussed by Joël de Rosnay (the cybiont)⁴⁸, Kevin Kelly (the hive mind)⁴⁹, Derrick de Kerckhove (connected intelligence)⁵⁰, Francis Heylighen (the super-brain)⁵¹, Howard Bloom (the global brain)⁵², Steven Johnson (emergent intelligence)⁵³, Howard Rheingold (smart mobs)⁵⁴, etc. Although the terms vary, a common theme seems to emerge. These authors have done a lot to draw public attention to the fundamental stakes of the new medium of digital communication. Unfortunately the models presented are frequently based on biology, technology or systemics, but without much depth from the perspective of the human or cognitive sciences. They rarely include the inherently symbolic, linguistic and meaning-creating – or hermeneutic – nature of culture, in their analyses of the “global brain”. To sum it up in one sentence: if the digital medium with its binary electronic flows does indeed constitute a kind of planetary fractal brain, we still do not have the symbolic system – the metalanguage of explication – that would give that brain something like the power of speech, and thus reflexive consciousness. As we will see in Part Two, while we may speak poetically (as do Teilhard de Chardin and Marshall McLuhan) of a superconsciousness or global consciousness, the only possible consciousness of human collective intelligence is, strictly speaking, the one that is reflected in the individual consciousnesses of living people.

6.5.2. Semantic information economy and the commons in the digital medium

Let us now suppose that public digital data⁵⁵ have in one way or another acquired the status of a commons. How could this commons be managed sustainably? What would an information economy capable of using, cultivating and developing such a commons be like?

The new economic conditions created by the digital medium can be summed up in two main points. First, once information is created it can be duplicated and transmitted at negligible financial cost. Second, all the agents of the information economy have virtual access to the other agents (and, increasingly, in P2P mode). The consequences of these two fundamental features of the new digital economy are twofold:

– First, an original, good piece of information that exists in a single copy at a single Web address is potentially available everywhere in unlimited quantities at negligible cost⁵⁶. Under these conditions, the consumption of information is not destructive, and its appropriation is not exclusive. The open-source software movement, copyleft and Creative Commons licensing⁵⁷ have begun to give legal form to this concept of non-exclusive appropriation. Of course, it is important to clearly distinguish between duplication and transmission, on one hand, and creation, on the other. Creation requires hard work, the physical maintenance of creators, a long process of training, and political, social and educational infrastructure – all of which are far from free. This is why the debate on intellectual property in the digital world revolves around a way of freeing the reproduction, use and communication of information, a way that does not kill the goose that laid the golden egg of the original creation. One of the problems in the management of shared information goods may be formulated as follows: how can we optimally use information that has already been created to promote human development, while not drying up – and even stimulating – the source of creation?

– Second, the existence of any good, shared information online can be known by all agents, ideally instantaneously. The market for information in the digital medium tends toward transparency. Even in the case of material goods or traditional services, information on prices, quality and characteristics of products is becoming increasingly accessible. This information is also widely discussed in the creative conversations of consumers, designers, producers, marketing experts, etc.⁵⁸ The rules regarding face-to-face commerce in material goods and services are thus also changing, since every market has a corresponding information market in the digital medium that, as in a fair or bazaar, often takes the form of a conversation.

There is so much information available in the digital medium that the biggest obstacle to accessing it is, in fact, this very abundance: how do we find the needle of relevant information in the gigantic haystack of digital data? Another way to view the problem is in terms of the measurement of value. Since all information goods are technically abundant once they have been produced (the supply is practically infinite), we can no longer measure value by scarcity or the simple tension between supply and demand. Since the availability of information is no longer a constraint to be overcome, shared information goods gain and lose value mainly according to their meaning and relevance for the communities – or creative conversations – that use them. For example, they can lose value when the knowledge in them becomes obsolete. Conversely, they can gain value through the proliferation of interpretations, resulting in increased interest, or because translation makes them relevant to a broader audience. From an economic point of view, we can say that the value of semantic information depends on the service rendered, which is necessarily contextual. In any case, its value for some will not be the same as its value for others, and this value will increasingly be measured collaboratively in creative conversations⁵⁹. To avoid a loss in value of its main good, the information economy must become a semantic information economy. Since the value of information depends on its meaning, the information economy must be capable of modeling the meaningful contexts and practical environments in which meaning is determined. We therefore have to imagine a socio-technical mechanism capable of answering the user’s key question: where is the information that has the greatest value for me?

For the information economy coordinated by the IEML semantic sphere, the measurement of the value of intellectual or cultural goods and the formalization of the contexts in which these goods are evaluated must be left open to the greatest possible number of (self-managed) collective interpretation games, while the way is paved for exchanges and collaboration among these games through the use of a shared framework for modeling and calculation. We can already glimpse the actors in these many different games grouping themselves in virtual communities of producers, consumers, marketers, readers, viewers, publishers, fans, critics, authors, artists, researchers, students, teachers, patients, doctors, etc. To each type of collective interpretation game there is a corresponding specific semantic universe (a certain way of organizing or “tagging” the shared memory), as well as a unique model for the measurement of value. Each creative conversation has its own ecosystem of ideas. We can imagine that creative conversations will ensure their sustainability by establishing circuits for redistributing value (monetary or other) to creators as well as to those who operate and maintain the communication infrastructure. Through the common grid of the IEML semantic sphere, collective interpretation games could enter into explicit relationships of cooperative competition and could exchange and recombine elements of their universes and their rules, while reflecting the values, choices and interests of infinitely diverse communities. I propose to consider the collective interpretation games of creative conversations as the varied, evolving and changing agents of the semantic information economy, since it is they that produce, transform and distribute value. There would thus be, in the virtual universe of human memory, as many games of collective intelligence interacting as there are creative conversations endeavoring to optimally use and enrich the common resource from original perspectives.

In Part 2, I will go into detail on the reflexive modeling of human cognitive activities in a digital medium perfected in the Hypercortex by the IEML semantic sphere.

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1 The Gift [MAU 1990], p.18.

2 The concept of usefulness is obviously contextual and conventional, and depends on the collective interpretation games. We have to think about this usefulness not only for the short term, but also over the time scale of generations.

3 See Elinor Ostrom and Charlotte Hess (eds.), Understanding Knowledge as a Commons: From Theory to Practice [OST 2006], p. 9.

4 On the concept of the community of practice, see the work of Étienne Wenger [WEN 1998], and on the more general concept of the ecology of practices producing its unique ways of knowing that cannot be reduced to official science, see Isabelle Stengers, Cosmopolitics [STE 2010].

5 I do not want to defend here the existence of an exclusively determining symbolic infrastructure as opposed to an ultimately determining material infrastructure, but rather the perspective of a systemic interdependence of all the layers of information nature. On the key role of geographic and bio-geographic factors in human history, see the fascinating book by Jared Diamond, Guns, Germs and Steel [DIA 1999].

6 Claude Lévi-Strauss often pointed out the role played by classifications of the natural physical environments of cultures in the formation of their social, religious, and other categories, see The Savage Mind [LÉV 1966].

7 See [SMI 1776, SMI 2007].

8 See Prologue de l’Ordinatio [DUN 1999].

9 The agent intellect, which Medieval commentators such as IbnSina, IbnRoshd and Maimonides considered to be common to all of humanity; on this point, see my Collective Intelligence [LÉV 1997].

10 Karl Marx, Grundrisse [MAR 1973], p. 706.

11 On the concept of collective intelligence in Marx, see also the analysis of cooperation in Chapter 13 of Book I of Das Kapital [MAR 1867].

12 See works by Hayek already cited [HAY 1937, HAY 1979].

13 See The Production and Distribution of Knowledge in the United States [MAC 1962] and Knowledge, Its Creation, Distribution, and Economic Significance [MAC 1982].

14 See The Information Economy [POR 1977]

15 In particular in Civilization at the Crossroads [RIC 1969], which he edited.

16 See Models of Bounded Rationality [SIM 1982]. Herbert Simon, a pioneer in artificial intelligence and the detailed study of cognitive phenomena in economics, received the Nobel Prize in economics in 1978.

17 This can be traced back to von Neumann and Morgenstern [NEU 1944].

18 See Cognitive Economics [WAL 2000].

19 See L’Abeille et l’Économiste [MOU 2010] and Le Capitalisme Cognitif [MOU 2007], [FOU 2007] in its augmented second edition, which includes the remarkable article by François Fourquet, “Critique de la raison cognitive” p. 265-276, in which he argues that the economy has always been an information economy.

20 Actually, the Sweden Prize in Economic Sciences in Memory of Alfred Nobel.

21 See Elinor Ostrom and Charlotte Hess (eds.), Understanding Knowledge as a Commons: From Theory to Practice [OST 2006].

22 [CAS 1996].

23 Yochai Benkler discusses networked social production; see The Wealth of Networks: How Social Production Transforms Markets and Freedom [BEN 2006].

24 Figure 5.1 can also be read as a description of the internal dynamics of collective intelligence.

25 This basic capital could result from interaction among the six capitals in the model in Figure 5.1.

26 I am referring here, among other possible references, to my philosophical book Collective Intelligence [LÉV 1997], to the more economical synthesis by Surowiecki, The Wisdom of the Crowds [SUR 2004] and to the multidisciplinary collection Collective Intelligence: Creating a Prosperous World at Peace, edited by Marc Tovey [TOV 2008].

27 See Chapter 3 and section 6.4.

28 Empedocles, in his poem, speaks of the love (attraction) and strife (repulsion) that drive the four elements.

29 Introduction to the Work of Marcel Mauss [LÉV 1950], p. 39.

30 Introduction to the Work of Marcel Mauss, p. 38. This unity of symbolic exchanges was recently pointed out by Henri Atlan in De la Fraude, le Monde de l’Onaa [ATL 2010], which clearly shows the circulation between exchanges of words, monetary exchanges of economic goods and relationships mediated by technology.

31 In a note in his book on Mauss, p. 70 (and in many other places), he cites the major works of Wiener (Cybernetics [WIE 1948]) and Shannon (The Mathematical Theory of Communication [SHA 1949]). He often cites Von Neumann and Morgenstern, Theory of Games and Economic Behavior [NEU 1944], for example in “Social structure”, in Structural Anthropology [LÉV 1963], p. 337.

32 For example, as early as 1951, in the article “Langage et société” (reprinted in Anthropologie Structurale, p. 70 [LÉV 1958]), he criticizes Norbert Wiener for underestimating the possible computerization of the social sciences.

33 Introduction to the Work of Marcel Mauss [LÉV 1950], p. 55

34 Ibid. [LÉV 1950], p. 55

35 Ibid. [LÉV1950], p. 63.

36 See Porat, The Information Economy [POR 1977], or Machlup, Knowledge, Its Creation, Distribution, and Economic Significance [MAC 1982], for example.

37 The “total social fact” is a well-known expression from Marcel Mauss, which he developed in The Gift, initially published in L’Année Sociologique, Paris, 1923-1924. See the collection of articles in Sociologie et Anthropologie [MAU 1990].

38 Science and the Modern World [WHI 1925], Adventures of Ideas [WHI 1933]. On Whitehead, see Isabelle Stengers, Penser avec Whitehead, Une Libre et Sauvage Création de Concepts [STE 2002].

39 See Edgar Morin, La Méthode [MOR 1977-2004].

40 Karl Popper’s summary work, Objective Knowledge, is characteristically subtitled “An evolutionary approach” [POP 1972].

41 For example, functions of categorization, evaluation and contextualization; see Chapter 13.

42 On the levels of encoding, see section 2.3.

43 But it is obviously an information nature; see Chapter 2.

44 The term meme was coined by Richard Dawkins [DAW 1976] on the model of gene to designate a self-reproducing cultural entity that circulates among humans. Memetics, which is based on Dawkins’s hypothesis (see Robert Aunger, ed., Darwinizing Culture: The Status of Memetics as a Science, with a preface by Daniel Dennett [AUN 2000]), and Dan Sperber’s ecology of representations (Explaining Culture: A Naturalistic Approach [SPE 1996]) are among the schools of thought that have most explicitly adopted the ecosystem paradigm for the study of culture. Focusing only on memes cannot provide an adequate explanatory framework for an economy (or an ecology) of culture. Myriads of small, self-reproducing memes are not sufficient to explain the Temple of Shiva in Chidambaram, the Zhuangzi, the Sistine Chapel, the Napoleonic Code, the Constitution of the United States or the Theory of Relativity. Only the cultural equivalents of organisms, i.e. complex ecosystems of ideas evolving interdependently, can account for the forms of the life of the mind, their persistence and their metamorphoses. In addition, according to memeticists, memes – or representations – directly reproduce in the brains of humans, i.e. in biological organisms, like viruses, and not in a cultural equivalent of organisms. While ideas are maintained by the mental states of subjects who themselves are embodied physically, however, they do not reproduce directly in brains. Cultural memes and biological brains simply do not belong to the same layer of information encoding (see section 2.3). Finally, unlike molecular biology, which has deciphered the genetic code, memetics has deciphered no “memetic code” or alphabet of representations.

45 Hieroglyphic writing was no longer practiced in the 4th Century.

46 See in Understanding Media, the chapter on computers, p. 464, in the 2003 critical edition edited by Terrence Gordon [MAC 1964]. Here McLuhan expresses his intuition (correct, in my opinion) regarding the direction of the evolution of the emerging global civilization. However, I will not adopt the concept of a “single consciousness”, a phrase that should be understood in a poetic sense rather than literally.

47 See Les Technologies de l’Intelligence [LÉV 1990], Collective Intelligence [LÉV 1997], Qu’est-ce que le Virtuel? [LÉV 1995], in which I introduced the concept of Hypercortex, and World Philosophie [LÉV 2000], which predicts a reflexive actualization of the noosphere in the digital medium.

48 See Symbiotic Man [ROS 2000].

49 See Out of Control: The New Biology of Machines, Social Systems and the Economic World [KEL 1994].

50 See Connected Intelligence [KER 1997].

51 See “The World-Wide Web as a super-brain: From metaphor to model” [HEY 1996].

52 See Global Brain: The Evolution of Mass Mind from the Big Bang to the 21st Century [BLO 2000].

53 See Emergence: The Connected Lives of Ants, Brains, Cities and Software [JOH 2001].

54 See Smart Mobs: The Next Social Revolution [RHE 2002]. Howard Rheingold (@hrheingold on Twitter) is a pioneer thinker on the digital revolution and virtual communities. His most recent work is on digital literacy.

55 I am emphasizing the word public in order to preserve all legitimate rights of privacy.

56 The cost is obviously not zero. It is necessary to maintain and update software, servers and networks. In addition, the operation of the digital medium requires the consumption of raw materials and energy.

57 See Lawrence Lessig (inventor of the Creative Commons license), Free Culture (freeculture.org) [LES 2004].

58 This was clear by the end of the 20th Century; see Levine, Locke, Searls and Weinberger: The Cluetrain Manifesto: The End of Business as Usual [LÉV 1999].

59 We see this in the increasingly refined collaborative systems of filtering and recommendation in the digital medium. See Herlocker et al., “Evaluating collaborative filtering recommender systems” [HER 2004].