In good philosophy, any deduction that is based on
acknowledged facts or truth is to be preferred to one that is based only on hypotheses, however ingenious.
Diderot and D’Alembert - Preliminary Discourse
The preservation, transmission and dissemination of ideas and knowledge is not a new issue. It was addressed with flair by the Encyclopedists, and has fuelled much debate among librarians.
The arrival of information technology, however, changed the perspective on the management of knowledge. A number of “visionaries”, such as Alvin Toffler, with “Future Shock”, and then “Powershift”, and Jean-Jacques Servan-Schreiber with “The World Challenge” highlighted the growing place of knowledge in the production process and the decisive role that information technology would have to play in preserving and disseminating knowledge. This was in the late 1970s, computers were multiplying in universities and research laboratories, and were gradually revolutionizing knowledge processing.
Using computers to describe works implied a new technology: electronic document management, which allowed a growing number of books to be indexed and searched. Plans were made to develop large document databases capable of indexing whole sections of human knowledge. Vast projects to construct multidisciplinary databases were started.
At the same time, researchers in Artificial Intelligence were exploring an even more ambitious avenue, by trying to make different bits of knowledge interact. Using software that applies the principles of mathematical logic, they managed to simulate human reasoning on fragments of text. These are known as “expert systems” and can formulate conclusions by exploring a “knowledge base”. They seem capable of making diagnoses (Mycin), evaluating situations and more.
As the Internet emerged in the 1990s, large document bases lost their key position as the central access point to scientific news as researchers exchanged information with each other directly. Mailing lists, and then the Web encouraged new practices in the exchange of knowledge. News groups and other electronic forums spread well beyond scientific and technological circles. Some of them were closed, reserved exclusively for their members, and many others were open for altruistic or political reasons.
It was these experiences in knowledge sharing and free publication that would eventually inspire the theoreticians of business management. Knowledge management, a new discipline in management science, encompasses a set of formulas designed to allow a business take the maximum advantage of its employees’ skills and experiences.
We will take a brief look at these different concepts and how they evolved.
At the end of the 1970s, it seemed possible that an immense database could contain the document holdings of many libraries, maybe even all libraries, and that the database would be accessible from a distance thanks to “telematics ”. The idea was to index every document (book, map, article, and so on), that is, to describe with them keywords and a summary, or abstract. Such descriptions are now known as metadata .
It was thought that it would be possible to provide the user with absolutely all the information on a given subject as long as the works in the field had been indexed and the question could be formulated in the language of the database ... In France, a specialist institute was set up to process scientific and technical information  and development started on two vast databases to cover the whole of science and technology: Pascal , for exact and experimental sciences, and Francis , for human sciences.
Document database projects turned out to be very costly, and they were confronted by the tremendous growth in the number of scientific publications at a time when their own budgets were more or less stagnant . On top of that, it was difficult to find descriptors common to several disciplines, given that each school of thought was attached to a specific, generally very rich and very precise vocabulary. Given the growing complications, many projects were abandoned and others downgraded. In the end, only the most highly specialized databases intended for targeted scientific communities managed to assert themselves in the international scientific community. One of the most famous is “Medline”, which catalogues over 80 million articles in medical sciences.
In the 1990s, with the multiplication of websites, a growing number of documents were placed on line. The first search engines appeared, the most well-known being AltaVista. It was with Google though in the 2000s that Internet search engines started to usurp document databases.
The growing power of computers, the standardization of document formats and the effectiveness of digitization and automatic character recognition technology have enabled works to be preserved in their entirety in digital form. Manual indexing, which is very expensive and highly dependent on context, can be replaced by the automatic indexing of every word. These vast indices are exploited by increasingly sophisticated search engines that can take account of the user’ s profile, evaluate and summarize the content of each document, and list the results according to relevance.
As searching for a few documents in the mountain of information on the Web seems a bit like looking for ore in uncharted territory, it is known as “data mining”.
Expert systems or knowledge-base systems
This is another branch of the electronic data processing of knowledge. The purpose of expert systems (ES) is not only to find information but to assess it. An ES is made up of an “inference engine” and a set of highly structured pieces of information called a knowledge base. The engine applies mathematical logic to the knowledge base so as to reach conclusions. The logical principles used are usually slightly haphazard in order to simulate the uncertain nature of human reasoning, whilst the knowledge base is formed of rules that constitute expertise in a given field. One rule for example might state that “if the patient has a high temperature and a reddish throat, they probably (0.8) have a throat infection”. The ES will start a dialogue with the user according to the context: “does the patient have a fever?”, “is the patient allergic to a specific drug?” and so on, so as to provide a diagnosis and suggest treatment.
It is in the medical field that ES have had the most impressive results. The first experiments (Mycin, DENDRAL, and so on) were very promising . Ultimately though, researchers found it hard to develop systems that could process a large quantity of knowledge. An ES is more efficient the more restricted its scope. The ES of today are highly specialized and integrated into diagnostic and decision support software.
ES are disturbing because they model decision-taking, thus raising the issue of responsibility for the decision.
The term sounds good. It fits in with the logic of marketing taught in business schools. It treats knowledge as the property of the business, a capital of knowledge that must consequently be exploited to the hilt.
On the technical level, KM combines documentary methods: digitization, indexing, possibly expert systems and above all distribution lists for communities involved in the same practices or interests. It can be considered that KM recycles for capitalist businesses Internet technologies and usages born in the communities of scientists and activists that had made them so effective.
KM cannot be reduced however to the use of various aspects of technology. The objective is mainly to make the most of employees’ knowledge by setting it all out clearly and adding value to it. KM is to immobilized skills what financial management is the monetary assets of a business. The idea is to make as much profit as possible. Thus, KM enables improvements in the management of all the skills of employees and in particular allows full use to be made of all talents, notably extra-professional. The linguistic, technical, and cultural knowledge that employees have acquired through their personal history or in their free time can be catalogued, and those concerned registered in the appropriate “community of practice”. This knowledge is what André Gorz calls human capital  “Firms must accommodate the creativity of their staff, channel it towards pre-determined actions and goals and obtain their acquiescence”.
KM is the instrument for this channelling. It requires the managers who have to contribute to the databases to observe strict standards enabling experience to be compared. They must highlight the lessons learnt, difficulties encountered and deduce good practices from them. All notes, marks, and reports are recorded, indexed and archived. The database is consulted on a systematic basis to prepare each mission. Recording the business’ s experience forms a sort of intellectual mould to which everybody must conform. KM thus reinforces the business culture in that it is the outcome of practices and a collective history. Whilst KM can prevent the same mistakes being made, it also encourages conformism and discourages original initiatives - managers have to develop a very solid argument to justify a change in attitude.
Let us note that British Petroleum (BP) was one of the first businesses to commit itself to a vast KM project, and the World Bank set up a large service “... motivated by a decision to increase the speed and quality of service delivery, lower the cost of operations by avoiding rework, accelerate innovation and widen the Bank partnerships to fight poverty ”.
KM for development?
Following the World Bank’ s lead, several development agencies became interested in KM, including Bellanet  with its knowledge sharing project  and ¬Oxfam, which has just published a re-edition of a comprehensive guide to the subject .
We must question the relevance to the management of public services and NGOs of concepts that have come out of business schools. We have shown how KM is part of the “management” palette of the capitalist business where it aims to optimize human productivity. Can the management methods of private businesses, whose aim is profit, be transposed to a body responsible for a mission of general interest funded by public money, national, or international?
We shall take a closer look at the introduction of KM at the World Bank. In June 1995, James D. Wolfensohn, new President of the World Bank Group, had to counter the charges of inertia and bureaucracy levelled by some members of its Board of Executive Directors. He wanted to speed up the Bank’ s adaptation to “the extraordinary change taking place in the global economy, with explosive growth in worldwide trade and private investment.”  He aimed to extend the management methods of private business and make the institution a reactive and competitive body that could take markets from other international development institutions.
He introduced KM and launched an extensive reorganization of hierarchical structures  and staff performance appraisal. In order to reconcile the principle of KM, aimed at the egoistic enhancement of a firm’s human capital, with the altruistic mission of the international institution, he introduced the notion of Knowledge Sharing (KS) and launched the “concept” of the Knowledge Bank, to enhance the knowledge of the South to combat poverty.
In a 17-page paper translated into several languages, “Knowledge for Development” , the Bank tells us very clearly how KM is supposed to promote development. “Developing countries need not reinvent the wheel (...) Rather than re-create existing knowledge, poorer countries have the option of acquiring and adapting much knowledge already available in the richer countries. With communication costs plummeting, transferring knowledge is cheaper than ever” and a bit further on, in the section on national strategies to narrow knowledge gaps, the Bank tells us that “three key means of facilitating the acquisition of knowledge from abroad are an open trading regime, foreign investment, and technology licensing”. Noting however that “developing countries can take advantage of the large global stock of knowledge only if they develop the technological competence to search for appropriate technologies and to select, absorb, and adapt imported technology”, it proposed “corporatizing research institutes”. Reading this paper written when KM was being introduced at the Bank, one cannot help noting that the knowledge proposed is heavily coloured by ideology.
Could that be why expert consultancies consider the introduction of KM at the World Bank to have been a total success? In 2004, and for the fifth year in a row, the World Bank was listed as one of the top 20 Most Admired Knowledge Enterprises , alongside BP, Royal Dutch/Shell, Ernst & Young, HP, IBM, and Microsoft. Of course, it is harder to find out whether the best clients of the World Bank, that is, the least developed countries, are satisfied with the Knowledge Bank.
These same experts note that the World Bank is both an enterprise knowledge-driven culture, and open to enterprise-wide collaborative knowledge sharing. This is a specific feature that can be found in similar terms at Oxfam . The particularity of KM for development is both as a set of measures for enhancing internal knowledge and a programme for transferring skills to clients and partners.
What could be more generous than for the Bank to share its knowledge capital, its internal culture? This approach is nothing new or surprising, fitting into the tradition of North-South relations. Donor countries are generally moved to impose their own culture on countries receiving aid. KM is merely new packaging designed to mask the relationship of domination. The expression emerged at a good time to renew worn-out or paternalist terms such as “technical assistance”, “capacity-building” and “capacity development” .
What is to be done with KM?
Is KM an essentially neo-liberal notion? Is it possible to put in practice an alternative KM whose objective would be neither André Gorz’s exploitation of human capital, nor the contemporary form of neocolonial type relationship analyzed by Kenneth King?
We should note first of all that the term “knowledge” creates an ambiguity. “Knowledge is experience. Everything else is just information”, said Albert Einstein. Knowledge cannot be drawn up like water from the bottom of a well. It is not made up of independent pieces that can be picked out as in a spare parts shop. It comes from experience and learning in a complex process that includes a relationship of trust between teacher and pupil. It comes necessarily with the acceptance of shared values that legitimize the knowledge.
Let us move on to the improper use of the word “knowledge” for marketing purposes and see what the key ideas of KM are:
Managing information related to experience and skills: recording that information in document databases; ensuring that is available through sophisticated arrangements for seeking out information (data mining); possibly adding to other tools for the conservation of expertise, such as expert systems;
Furthering the emergence of networks of colleagues sharing knowledge and motivation (communities of practice); using computer applications based on mailing lists, online forums and group-enabling technologies , to run the networks;
For knowledge sharing (KS), we shall add information (knowledge) sharing among several donors and information (the same information?) sharing among donors and their clients or partners.
It must be noted that these practices of collective expertise, or even collective intelligence  were devised by communities whose mission is to share knowledge, typically scientific communities, as basic research cannot develop without the free movement of knowledge. They also include communities of developers of free software. One of the essential features of these communities is that they operate using a non-market mode of exchange which is in growing opposition to the excesses of the liberal economy , even though the concept of KM is built on an exactly inverse logic. It consists in recuperating the non-contractual knowledge of the employees of a business, marshalling it and making it part of the official culture of the business. The objective is not sharing but comparative advantage in commercial competition.
In conclusion, let us then leave KM to business schools and choose instead to use a less ambiguous and more meaningful vocabulary: experimentation, learning, concertation, cooperation, publication, management and sharing of free contents, open source intelligence.