Heylighen F. (1997): "Towards a Global Brain. Integrating Individuals into the World-Wide Electronic Network", in: Der Sinn der Sinne, Uta Brandes & Claudia Neumann (Ed.) (Steidl Verlag, Göttingen) [in press]

Contents

• Integrating Individuals into the World-Wide Electronic Network
• Introduction
• Society as a Superorganism
• The global network: a brain for the superorganism
• A learning and thinking Web
• Immersing individuals into the Web
• The senses of the superorganism
• Acknowledgments
• References

Towards a Global Brain.

Integrating Individuals into the World-Wide Electronic Network

ABSTRACT. It is argued that the future of the senses should best be studied through the metaphor of society as a superorganism. The precise correspondence of functions between society and a multicellular organism is outlined. The information processing functions (nervous system) of the social superorganism are strongly enhanced by the on-going network revolution. This leads to the view of the future world-wide web as a "global brain", encompassing many individuals.

Introduction

When studying the future of the senses, as this congress does, perhaps the first question we should ask is "The senses of what?". The simple assumption is that we are all speaking about the senses of ordinary human beings, about our own senses of sight, hearing, smell, taste, etc. However, as several participants in this conference have pointed out, it is likely that human beings as we know them will undergo profound alteration. The changes taking place in our society are so radical that they are likely to affect the essence of being human. Some contributors have suggested that humans will be replaced by robots (Moravec, this volume), others see people evolving into "posthumans" (More, this volume), still others see the emergence of "cyborgs", human-machine hybrids.

The point I want to advance here is that we may be looking at the wrong level of analysis when focusing on individual beings. The most important changes take place in the domain between individuals, in the technology, communication patterns and social relations which connect individuals together. To me, it seems that these bonds are becoming stronger and stronger, leading to the eventual integration of people into a supra-individual, cybernetic system. This system will be of an unheard of complexity, and have features so novel and abstract, that for the people we are now it is extremely difficult to imagine what they would be like. Therefore, I propose to study this emerging socio-technological system with the help of an analogy. The most complex cybernetic systems we know until now are living systems, and in particular advanced multicellular organisms, such as mammals or human beings. Therefore, this paper will look at society as if it were itself an organism, consisting of other organisms. This perspective will give us an alternative view of the future of humanity, and thereby help us to understand the future of the senses.

Society as a Superorganism

It is an old idea, dating back at least to the ancient Greeks, that human society is in a number of respects similar to a living system. For example, more than a century ago, the evolutionary theorist, Herbert Spencer (1969, original publication 1876-96), in his "Principles of Sociology", proposed detailed arguments for the thesis that "society is an organism". Many thinkers since then have discussed the analogies between the roles played by different institutions in society and the functions of organs, systems and circuits in the body (e.g. de Rosnay, 1979, 1986, 1996; Russell, 1996; Stock, 1993, Turchin 1977; see Heylighen, 1996 for a discussion of their contributions). For example, industrial plants extract energy and building blocks from raw materials, just like the digestive system. Roads, railways and waterways transport these products from one part of the system to another one, just like the arteries and veins. Garbage dumps and sewage systems collect waste products, just like the colon and the bladder. The army and police protect the society against invaders and rogue elements, just like the immune system.

The fact that complex organisms, like our own bodies, are built up from individual, living cells, led to the concept of superorganism. If cells aggregate to form a multicellular organism, then organisms might aggregate to form an organism of organisms: a superorganism. Biologists (e.g. Seeley, 1989) agree that social insect colonies, such as ant nests or bee hives, are best seen as such superorganisms. The activities of a single ant, bee or termite are meaningless unless they are understood in function of the survival of the colony.

Such initially vague analogies become more precise as the understanding of organisms increases. Systems theory (von Bertalanffy, 1968; Klir, 1991) provides a useful conceptual framework for establishing a precise correspondence between organismic and societal functions. Its abstract representation of the structures and functions of complex, adaptive systems is applicable as well to organisms as to societies. The analogy between society and organism is made more explicit in the tables below. These tables list general functions characterizing all "living" systems, and for each function give the corresponding subsystem in an organism and in society.

The functions are loosely based on the set of critical subsystems proposed by James Miller (1978) in his Living Systems Theory, although I have left out some of the less important ones (e.g. "timer"), and added a few which seemed missing in Miller's list (e.g. "immune system" and "energy carrier"). I have also renamed some functions to more traditional system terms (e.g. "sensor" instead of "input transducer"). Similar correspondence tables (which follow Miller more literally) can be found in the work of Russell (1996) and of Chen and Gaines (1997).

Table 1 covers the analogy at the most general level, looking at the components of the system and at the boundary which separates it from its environment. An important characteristic of both multicellular organisms and social systems is the differentiation between the units of the systems. Our body contains many different cell types, e.g. neurons, red blood cells, skin cells and liver cells, which each perform their own specialized function. Similarly, individuals in society become specialized in different activities or functions. Such a division of labor is a fundamental characteristic of every complex, organism-like system (cf. Gaines, 1994).

Perhaps the most fundamental property of a living system is that it constantly rebuilds itself, thus maintaining an invariant organization in spite of wear and tear and the constant perturbations from the environment. Maturana and Varela (1980) have called this property "autopoiesis" (self-production). This constant production of components is clearly seen in society, whose intricate organization ensures that both its living (people, animals, plants) and non-living components (buildings, cars, roads, etc.) are constantly replaced. In order to produce such components, an autopoietic systems needs a constant input of energy and matter ("food"), which it converts into its own material. The part of the resources that cannot be converted needs to leave the system as waste. The complex organization responsible for processing matter and energy is called a metabolism. In addition to the functions for ingesting, converting, distributing and excreting material, part of the material needs to be stored as a reserve for situations where the supply might be too low. Moreover, the organism as a whole needs to be physically supported, so that it maintains its shape and can better withstand outside blows. Finally, it needs to be able to actively intervene in the outside world, and therefore it needs to be able to move (motor function). These different metabolic functions are summarized in table 2.

The most important set of functions for our present purposes are those which process information, rather than matter. In order to intervene efficiently in the environment (so as to counteract perturbations or locate food), a living system needs to be aware of what is going on in its surroundings. This is where the senses come in. The sensory organs provide the autopoietic system with stimuli, or "raw" data, which need to be interpreted by the nervous system. This interpretation requires different functions. There is the direct decoding, the transformation of data into more meaningful information. This is still part of the "senses": in order to see we need more than light sensitive cells in the retina, we need a visual cortex to process the pattern of activation of these cells in order to recognize figures and shapes. The thus perceived information needs to be compared with the information that is stored in the nervous system, the "memory". This memory is created by a learning process which continuously creates new rules and associations on the basis of perceptions. Miller (1979) has called this function the "associator". The final interpretation is made by the "decider" function, which compares the perceived situation with the system's goals and values, determines which discrepancies there are, and finally devises a plan of action to eliminate these discrepancies. This plan of action is implemented by the "effector" function, which gives the appropriate commands to the motor subsystem, so that the actions are taken in the most effective way. All these different functional components are connected by the "channel and net", the network of communication links which transmits information between all the components. These components of the nervous system are summarized in table 3.

Table 3: Functions of the nervous system (processing of information) in (higher) multicellular organisms and societies.

The global network: a brain for the superorganism

Although individual humans may seem similar to the cells of a social superorganism, they are still much more independent than cells or even ants (Heylighen & Campbell, 1995). This is especially clear if we look at the remaining competition, conflicts and misunderstandings between individuals and groups. Thus human society is still an ambivalent system, balancing between individual selfishness and collective responsibility. In that sense it may be more similar to organisms like slime molds or sponges, whose cells can live individually as well as collectively, than to true multicellular organisms. However, there seems to be a continuing trend towards further integration, driven by globalization, economic interdependencies and technological development (Stock, 1993). As social systems grow into a more closely knit tissue of interactions, transcending the old boundaries between countries and cultures, the social superorganism seems to turn from a metaphor into a reality.

The strengthening of the social superorganism is most visible in its nervous system. The processing, storage and distribution of information in society has become much more efficient since the introduction of the electronic media. This evolution shows subsequent stages, which are characterized by growing complexity and intelligence of the information processing system. The first electronic media, such as telegraph and telephone only allowed communication from individual to individual (one-to-one). Radio and TV, the next generation mass media, allowed communication from one to many. The present electronic networks allow many-to-many communication. On the horizon we see the next stages appearing (Heylighen & Bollen, 1996). First, the computer network will become able to learn, that is, change the pattern of its connections. Then, the network will become able to think, that is, autonomously create new information.

These stages parallel the evolutionary transitions which characterize the development of the human brain (Heylighen, 1995; Turchin, 1977). They lead to a nervous system for society which is much more efficient and intelligent than the basic system sketched in table 3. Instead of relying on the slow and unreliable processes of spoken and written communication, the nervous system of the electronic age will transmit, store and process information instantaneously, without loss or degradation. Such an intelligent network which spans the planet may be called the "global brain" (Russell, 1996; Mayer-Kress & Barczys, 1995).

The medium that seems best suited to implement such a brain-like, intelligent network is the World-Wide Web (WWW), which is increasingly being used as a unified interface to the Internet computer network. This universal acceptance is due to the Web's extremely simple, but powerful way of representing networked information: distributed hypermedia. It is this architecture that turns the Web into a prime candidate for the substrate of a global brain.

The distributed hypermedia paradigm is a synthesis of three ideas (Heylighen, 1994). 1) Hypertext refers to the fact that Web documents are cross-referenced by 'hotlinks': high-lighted sections or phrases in the text, which can be selected by the user, calling up an associated document with more information about the phrase's subject. 2) Multimedia means that documents can present their information in any modality or format available: formatted text, drawings, sound, photos, movies, 3-D 'virtual reality' scenes, or any combination of these. 3) Distribution means that linked documents can reside on different computers, maintained by different people, in different parts of the world. With good network connections, the time needed to transfer a document from another continent is not noticeably different from the time it takes to transfer a document from the neighbouring office. This makes it possible to transparently integrate information on a global scale.

A learning and thinking Web

The core analogy between the World-Wide Web and the brain is the one between hypertext and associative memory. Links between hyperdocuments or nodes are similar to associations between concepts as they are stored in the brain. However, the analogy goes much further, including the processes of thought and learning.

Retrieval of information can in both cases be seen as a process of spreading activation (Jones, 1986; Salton & Buckley, 1988): nodes or concepts that are semantically "close" to the information one is looking for are "activated". The activation spreads from those nodes through their links to neighbouring nodes, and the nodes which have received the highest activation are brought forward as candidate answers to the query. If none of the proposals are acceptable, those that seem closest to the answer are again activated and used as sources for a new process of spreading. This process is repeated, with the activation moving from node to node via associations, until a satisfactory solution is found. Such a process is the basis for thinking. In the present Web, spreading activation is only partially implemented, since a user normally selects nodes and links sequentially, one at a time, and not in parallel like in the brain. Thus, "activation" does not really spread to all neighbouring nodes, but follows a linear path.

A first implementation of such a "parallel" activation of nodes might be found in search engines, where one can type in several keywords and the engine selects those documents that contain a maximum of those keywords. E.g. the input of the words "pet" and "disease" might bring up documents that have to do with veterinary science. This only works if the document one is looking for effectively contains the words used as input. However, there might be other documents on the same subject using different words (e.g. "animal" and "illness") to discuss that issue. Here, again, spreading activation may help: documents about pets are normally linked to documents about animals, and so a spread of the activation received by "pet" to "animal" may be sufficient to select the searched-for documents. However, this assumes that the Web would be linked in an intelligent way, with semantically related documents (about "pets" and "animals") also being near to each other in hyperspace. To achieve this we need a learning process.

In the human brain, knowledge and meaning develop through a process of associative learning: concepts that are regularly encountered together become more strongly connected. It is possible to implement simple algorithms that make the web learn from the paths of linked documents followed by the users. The principle is simply that links followed by many users become "stronger", while links that are rarely used become "weaker". Some simple heuristics can then propose likely candidates for new links, and retain the ones that gather most "strength". The process is illustrated by our adaptive hypertext experiment (Bollen & Heylighen, 1996), where a web of randomly connected words self-organizes into a semantic network, by learning from the link selections made by its users. If such learning algorithms could be generalized to the Web as a whole, the knowledge existing in the Web could become structured into a giant associative network which continuously adapts to the pattern of its usage.

We can safely assume that in the following years virtually the whole of human knowledge will be made available electronically over the networks. If that knowledge is then semantically organized as sketched above, processes similar to spreading activation should be capable to retrieve the answer to any question for which an answer somewhere exists. The spreading activation mechanism allows questions that are ill-posed: you may have a problem, but not be able to clearly formulate what it is you are looking for, but just have some ideas about things it has to do with.

We have tested this mechanism in practice with the associative network derived from our learning web experiment. There exists a TV game (called "Pyramide" on the French station France 2) where players have to guess words, using a minimum of different clue words provided by their partners. For example, if you have to guess "tree", your partner might suggest the clues "forest" and "plant". If that is not sufficient to make you guess correctly, depending on your answer your partner might add an additional clue, e.g. "wood". We implemented spreading activation in our experimental network so that it would be able to play this game. The user selects a combination of words from the network (e.g. "society" and "control"), and the spreading activation mechanism finds the word that is most closely related to the combined clues (e.g. "government"). Within the limitations of our data (the network contains at present only 150 words) the network seems to play the game about as well as a human player.

Immersing individuals into the Web

The mechanisms we have sketched allow the Web to act as a kind of external brain, storing a huge amount of knowledge while being able to learn and to make smart inferences, thus allowing you to solve problems for which your own brain's knowledge is too limited. In order to use that cognitive power effectively, the distance or barrier between internal and external brain should be minimal. At present, we are still entering questions by typing in keywords on our desktop computer, after contacting a specifically chosen search engine on the web. This is rather slow and awkward when compared to the speed and flexibility with which our own brain thinks. Several mechanism can be conceived to accelerate that process.

The quick spread of wireless communication and portable devices promises the constant availability of network connections, whatever your location. Presently, a lot of research is being done on "wearable computers", small but powerful processors which you can have on you continuously, for example attached to a belt (Starner et al., 1997). You would also wear special glasses or a light helmet which allow you to see the information from the computer superimposed on a normal view of the surroundings. Thus, the computer can constantly provide you with information about the things you see, and warn you e.g. when an important message arrives.

Such computers would use the multimedia interfaces which we already mentioned. This would allow them to harness the full bandwidth of 3-dimensional audio, visual and tactile perception in order to communicate information to the user's brain. The complementary technologies of speech or gesture recognition make the input of information by the user much easier. For example, the wearable computers would be connected to a small microphone, in which you can speak, and a glove or sophisticated trackball kept in your pocket, with which you can steer the cursor or manipulate virtual objects.

Yet, even more direct communication between the human brain and the Web can be conceived. First, there have already been experiments (Wolpaw et al., 1991) in which people steer a cursor on a computer screen simply by thinking about it: their brain waves associated with particular thoughts (such as "up", "down", "left" or "right") are registered by sensors and interpreted by neural network software, which passes its interpretation on to the computer interface in the form of a command, which is then executed. Research is also being done on neural interfaces, providing a direct connection between nerves and computer (Knapp & Lusted, 1992). If such direct brain-computer interfaces would become more sophisticated, it really would suffice that you just think about a problem to see the documents with possible solutions pop-up on your screen.

Second, the search process itself should not require you to select a number of search engines in different places of the Web. The new technology of net "agents" is based on the idea that you would formulate your problem or question, and that that request would itself travel over the Web, collecting information in different places, and send you back the result once it has explored all promising avenues. A software agent is a small message or script embodying a description of the things you want to know, a list of provisional results, and an address where it can reach you to send back the final solution.

Using our experimental network, we have simulated an agent that searches for information in the network using associations. The agent gets a target word that it needs to find, and a random starting position. From that position, it explores the available links by selecting the one with the highest association to the target. It repeats this proces when it reaches the new position, until the target is found. In most cases, the target is reached very quickly, in a way similar to the way a human user would select hypertext links.

In the future intelligent web, such agents could play the role of "external thoughts". Your thought would initially form in your own brain, then be translated automatically via a neural interface to an agent or thought in the external brain, continue its development by spreading activation, and come back to your own brain in a much enriched form. With a good enough interface, there should not really be a clear boundary between "internal" and "external" thought processes: the one would flow over naturally and immediately into the other. Thus, the user would become completely immersed into the network.

The senses of the superorganism

Until now, we have basically discussed the decoder, channel and net, associator, memory and (to a less degree) decider functions of the global brain (see table 3). However, the sensor and effector functions of the social nervous system too will be greatly enhanced by the emerging global network. The sensor is what brings information from the outside world into the network. In first instance, this is done by the millions of individual people who enter data into the Web. These people receive that information basically through their own senses. However, the fact that so many people enter that information in parallel adds a whole new dimension to the global brain's sensing capacity. It is as if the global brain sees simultaneously through millions of eyes and hears through millions of ears. This allows it to gather an amount of information much larger than any individual could ever sense. The superhuman processing power of the global brain moreover allows it to interpret that ocean of data in a way no person could, for example by looking for subtle, recurring patterns in huge collections of data (this is called "data mining", see Fayyad & Uthurusamy, 1995).

But the global brain does not even need human users to gather information. Already now there are hundreds of cameras, pointing at different places on the globe, that are constantly transmitting images live to the Web. Such mechanical input devices also include sensors covering domains that no person can observe. For example, satellites constantly provide images of the Earth and the stars to the Web. These sensing devices are not limited to the channels of human perception. For example, many of the satellite or telescope images on the net are derived from infrared, ultraviolet, or Röntgen radiation, for which our eyes are insensitive. All possible physical sensing devices can be attached to the network, such as sophisticated vibration sensors able to detect far-away avalanches or explosions. All this information is useful for the global brain, and will be decoded and interpreted, e.g. to predict tropical storms, produce a better picture of the galaxy, or monitor the risk for earthquakes. Thus, the global brain becomes more and more aware of its surroundings (cf. Stock, 1993).

The last function is the effector, the subsystem which transforms information into physical action. Some examples of this function are already available on the World-Wide Web. Thus, it is possible to remotely steer a robot arm to dig for artefacts in the earth, or to water and plant flowers in a garden, just by pushing some buttons on a web page. In the near future, we can expect that practical home functions, such as setting the temperature on the thermostat, prepare coffee or fill the bath, will be carried out over the network, so that your home will be ready to welcome you as soon as you leave your work. On a larger scale, it is likely that automatized factories will be controlled over the network, so that additional demand for a particular product in the shops will immediately lead to the production of the requested number of items in the factory.

The combination of the sensor and effector functions over the network allows the remote manipulation of objects by a person. This is called telepresence. The person sees, hears and feels everything going on in a different place via a high bandwidth, "virtual reality" type of communication link. Inversely, the actions of the person in response to these perceptions are transferred over the network to a remote effector which executes them as precisely as possible. For example, you could let a robot carry out a difficult job in a dangerous environment (e.g. a nuclear reactor or the surface of the moon), while seeing and feeling the robot's actions as if it were your own. Another application is surgery at a distance, where the doctor's hands guide a robot arm which performs the operation. Thus, an emergency operation can be carried out even if the only specialist capable of executing it is thousands of miles away from the patient.

These examples of sensing-effecting loops still involve an individual person. However, in many cases, the intelligent network itself can take all the necessary intervening decisions. In the example of the automatic factory, the sensor which registers how many items of a particular type need to be produced, can work without supervision. Each time a client orders a particular item (which can be done via the network), a counter is increased with one unit. If the counter exceeds a certain value, an order for a new batch of products is transmitted to the factory. At the same time, the prices can be automatically adjusted according to the laws of supply and demand. Thus, the economy as a whole can be controlled directly or indirectly by the electronic nervous system (Heylighen, 1997).

Although such developments may still seem more like science fiction than like hard technology, most of them already exist in embryonic form. Given the incredible speed of evolution in the domain of information and communication technologies, it is likely that most of them will be generally used in the coming 10 to 20 years. Time will tell whether the resulting changes in society will be best understood through the superorganism model or through an alternative view of individuals and society.

Acknowledgments

The author has been supported during this research by the Fund for Scientific Research-Flanders (FWO), as a Senior Research Associate.

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Biography of the author:

Dr. Francis Heylighen is a Senior Research Associate for the Fund for Scientific Research-Flanders (FWO). He works at the Free University of Brussels (VUB), where he is a member of the council of the transdisciplinary research Center Leo Apostel. The main focus of his research is the evolutionary development of higher levels of complexity, and in particular the development of knowledge. He tries to apply these ideas to the integration of knowledge from different disciplines into an encompassing, computer-supported conceptual framework or "world view". Heylighen has published over 60 scientific papers, mainly in cybernetics and systems theory, a book (his PhD thesis, "Representation and Change"), and he has edited books on 'Self-Steering and Cognition in Complex Systems' and 'The Quantum of Evolution'. He is editor and publisher of the world-wide Principia Cybernetica Project for the collaborative development of an evolutionary-systemic philosophy, and member of the editorial boards of the 'Encyclopaedia of Life Support Systems', the journal 'Informatica' and the 'Journal of Memetics'. He has organized and chaired many international conferences and seminars, and regularly gives invited lectures in different parts of the world.

Selected publications:

Heylighen F. (1990): Representation and Change. A Metarepresentational Framework for the Foundations of Physical and Cognitive Science, (Communication & Cognition, Gent), 200 p.

Heylighen F., Rosseel E. & Demeyere F. (eds.) (1990): Self-Steering and Cognition in Complex Systems. Toward a New Cybernetics, (Gordon and Breach Science Publishers, New York), 440 p.

Heylighen F., Joslyn C. & Turchin V. (1995) (eds.): The Quantum of Evolution.(Gordon and Breach Publishers, New York) (volume 45, numbers 1-4 (special issue) of "World Futures: the journal of general evolution"), 244 p.

Heylighen F. (eds.) (1997): The Evolution of Complexity (Kluwer, Dordrecht).

Heylighen F. (1990): "A Structural Language for the Foundations of Physics", International Journal of General Systems 18, p. 93-112.

Heylighen F. (1991): "Design of a Hypermedia Interface Translating between Associative and Formal Representations", International Journal of Man-Machine Studies 35, p. 491-515.

Heylighen F. (1992): "A Cognitive-Systemic Reconstruction of Maslow's Theory of Self-Actualization", Behavioral Science 37, p. 39-58.

Heylighen F., Joslyn C. & Turchin V. (eds.) (1997): Principia Cybernetica Web (electronic publication, URL: http://cleamc11.vub.ac.be/default.html), ca. 1200 cross-linked hypertext documents.