Much knowledge yet unused

A variety of scientific disciplines are concerned with understanding and modelling aspects of intelligent behaviour:

• The neuro-sciences are dedicated to the study of nerve cells, their inter-connections and the ways these connections can be modified by learning processes.
• Cognition psychology looks at algorithms transforming passive data into case-sensitive information and -at a higher psychic level- the role symbols play in the combination of such information according to the rules of logic.
• Psychology provides hints at how the psyche of man adapts itself to mastering a highly unpredictable and complex environment.
• The biology of evolution contributes striking examples of highly specialized and well-adapted organisms emerging without any intelligent intervention necessary to the feat.
• Genetics suggest a score of mechanisms implemented by biologically evolving organisms.
• The computer sciences are partly successful in modelling some of the results of the branches of science mentioned above as to produce quasi-intelligent results (genetic algorithms, neural networks, artificial intelligence).
• The „game theory“ points at difficulties and advisable strategies in dealing with potentially hostile competitors in an environment of limited ressources.
• Ethology and the social sciences observe and describe phenomena displayed by small and large groups of biological individuals as they try and adapt to the demands of their respective environments.
• Mathematics and physics have given birth to the the theory of chaos and order, which covers the border region between fickle transcience and barren inflexibility i. e. where intelligent life forms are found.
• The economic sciences -often without fully appreciating the fact- deal with intrinsically biological problems such as companies competing for limited ressources. Some of the solutions, such as benchmarking, conspicuously resemble biological counterparts.

Over the past two decades, many scientists have distilled from the empirical and theoretical data amassed by the classical sciences basic principles of successful and intelligent behaviour. Unifying concept such as „complex adaptive systems“, "systems sciences" and "cybernetics" seem to be particularly fruitful focii to this process, rallying and merging contributions from many different disciplines.

The metaphor of a global organism has gained new impetus with the continuous emergence of ever more striking analogies between the internet and nervous systems.

The idea

Large companies can be understood as „complex adaptive systems“, being capable of intelligently adapting themselves to a constantly changing environment. They are -at a certain level of abstraction- comparable with biological organisms. The question arises, in how far one can not only compare but actively transfer elements of intelligence from biological organisms, neural networks, genetic algorithms or whole societies to large companies:

• Could a single human or a well defined computer be treated as a neuron, reducing many ingoing signals to a few outgoing signals?
• Could „synaptic plasticity“ be remodelled within a future communication software so as to alter the probability with which information from a certain source can reach a certain recipient under certain cirumstances?
• Could the process of back-propagation, often used to teach neural networks, be imitated on a company scale by allocating communication resources according to the participation of certain communicators to succesful decision and projects? Would this give rise to a whole company acting as one neural network?
• Could future browsers within an intranet be equated to symbols described by psychologists in the way that they serve to collect specific information, using associations (links, key-words on the internet)?
• In how far could the avowedly important role emotions play in influencing the data-processing in our brains be copied by large companies? What would a company „limbic-system“ look like?
• Animal and human brains are spatially highly differentiated, thereby optimizing the use of the limited lines of communication. Should companies, too, try and reassess their spatial structure in order to minimize the demand on data-transfer infrastructure?
• Can the various instruments emerging under the name of data-mining be understood in analogy to the propensity of human brains to try and find causal relationships in whatever data they can get hold of?
• What would be the effect of successful companies not expanding (thereby probably discarding many of the qualities by which they achieved success) but duplicating themselves and thereby their reasons for success? Would this imitation of biological organsims lead to a more decidedly evolutionary economic environment? Could large investment-fonds and the stock-exchange initiate or force such a step on companies? Are chain-companies pre-adapted to this development? Could encoding standards such as ISO 9000, SAP-structures or clearly written-down company profiles be regarded as an incipient form of DNA, serving as a blue-print when a successful company is to be duplicated?

The vision

Future companies make maximum use of strategies of success provided by biology. Their communication structure will show distinct features of neural intelligence, a single human or computer being equatable to something on the level of a neuron or even below.

A large population of similar companies can be understood as a genetic population. Success will be defined in terms of reproduction (thereby sowing the seeds of their success) rather than growth. Genetic principles will be used to optimize the adaption of the population as a whole.

Any economic system redesigning its companies along these principles will be vastly superior to any other system.

A first-step: a one-year assessment phase

The wide range of potential contributors to these ideas and the naturally limited understanding the initiators of this scheme have of the sciences adressed make it unadvisable to look for partners at too early a stage. Instead, the initiators suggest the following step-by-step proceeding:

1. IBH first of all creates a vividly and distinctly modelled phantasy-company, including many features mentioned above. This will basically serve to make the vision communicable. Also, current literature is gathered and indexed in reference to the various points of interests. All results will be published on the internet, together with the procedure suggested below.
2. Intellectual Property Rights and other contractual issues will be settled at this stage, using http://www.cordis.lu/ipr-helpdesk.
3. Using the infrastructure of the European community (http://www.cordis.lu/fp5/src/ncps.htm)
4. The proposal will be announced publicly, calling for potential partners to come forward.
5. IBH prepares a two-day workshop at which the whole idea is to be presented and discussed. Participants should be recruited from as many different disciplines as possible, preferably from computer, biological and economic sciences. Their number should be above 6 but not exceed 12. The aim of the workshop is to formulate fundamentally executable forms of organization and the development of programmable software, transfering elements of intelligent biological systems to large companies.
6. In retrospect, all participants are asked to produce a written assessment of the project as a whole and a clear outline of their specific contribution. IBH will coordinate these acitivities.
7. All results will be documented and published on the internet by IBH. This will serve as a basis for further evaluation as to the continuation of the scheme as a full project.

Money granted by the FET-option of the „Fifth Framework“ of the European Union should cover for the period of the assessment phase:

• a one year salary of an academic employee,
• the costs incurred by the participants related to the workshop (travelling, accomodation),
• a pre-defined amount paid out to participants willing to further contribute to the scheme.