DO YOU MASTER KEYWORD THINKING ?

If you wish to become a scientist, a scholar, a research worker, or a technical engineer, you will have to confront the Big Science of today. It is often the case that young scientists took a liking to science as teenagers, by reading books about popular science or biographies of great scientists of the past. But throughout the XX^th century, the thinking modes of Science have undergone a complete metamorphosis, something like the industrial revolution, and there is no mention of the new modes of thinking in these books, which generally relate the life of great minds who in solitude thought over the deep problems of the universe, and had to fight with the prejudices of their times. Moreover, the new ways of thinking are never taught, neither in undergraduate nor in graduate curricula. Therefore young scientists must face the conditions of our time without any preparation. In order to remedy these omissions some analysis of the new thinking modes are necessary. And the most important and useful among these new standards is keyword thinking.

1. Historical and social grounds of keyword thinking.

Nowadays Science has become gigantic and complicated. It is the reason for which it is now called Big Science. In the times of Galilei or Newton, a single person was able to understand the whole scope of knowledge. The great minds of the ancient Greek civilization, Arabian Middle Ages, or the Renaissance were universal. Through the centuries however, the amount of knowledge grew so that in the nineteenth century, the all-embracing men disappeared, and were gradually replaced by naturalists, physicists, mathematicians, astronomers, chemists, philologists, historians, philosophers, etc. At the end of nineteenth century, only a handful of great minds were still able to master more than one of these branches of knowledge. Since the advent of Big Science ( ~ 1945), this tendency has been considerably accelerated: in the fifties, historians were for example specialized in the Roman Empire or the Middle Ages (mediaevalists); philologists were replaced by germanists or latinists, mathematicians by probabilists or algebrists; physicists became specialized in nuclear physics or semi-conductors. More recently, no germanist could still be competent in German literature, but only in German-Swiss literature of XVIII^th century or Goethe's work, no algebrist could still master algebra, but only finite groups, etc.

This general tendency is not due to anything like a degeneracy of knowledge or moral principles. It is merely due to the fact that the amount of human knowledge is growing exponentially, whereas the human faculties remain constant. On the other hand, however, another complementary tendency appeared: the need for technical and professional versatility. This countertendency is due to the evolution of economy; it is an aspect of the need for flexibility. Concerning Science, this countertendency results in the fact that no laboratory, no scientist can afford to establish its (or his) future in only one of these tiny areas that now constitute the specialities. This new situation is especially of interest to science managers, for they have to handle many activities at the same time. However, this also concerns every research worker, even the most unpretentious one, because he might have to find another job, or change his present activity according to the market fluctuations. At first sight, it could seem that both tendencies are conflicting, if not irreconcilable, and that there is no way for humans to adapt themselves to such a contradictory situation. But human beings have been selected by a long struggle for life process, which enabled them to face the most hostile situations. And today's scientists are human beings: they succeeded in finding a way of adapting. This way is keyword thinking.

2. The natural mechanism that produced keyword thinking.

The principle of keyword thinking consists in a mental symbolic scheme that covers the entire knowledge, and replaces the knowledge itself. In the traditional thinking mode (that of Newton, Gauss, Poincaré, or Einstein for example), the progress of knowledge consisted in understanding deeper and deeper: concepts such as time, space, energy, field, consciousness, life, etc. were analysed in their deepest aspects and meanings, far from people's everyday experience. But it was precisely this depth of investigation that hindered the possibility of mastering a wide scope; because of the intrinsic limitations of human brain, a deeper insight on a subject was - within a life - only possible by restricting the scope. Conversely, a wider scope is only possible by restricting the profoundness. We can understand this property of knowledge through the following image: knowledge has some horizontal dimensions, in which its different branches will extend, and a vertical dimension, which corresponds to the profoundness of knowledge. The capacity of the human brain limits the volume of knowledge. Now, Science covers a given surface that is fixed (except possibly when new areas are created), and its progress goes along its vertical direction. This image clarifies the aforementioned state of today's Science: progress is made by research workers who are boring wells of evanescent diameter. Keyword thinking is the adapted response to the dilemma: it suppresses the vertical dimension. More and more scientists are divided into two categories: research miners, generally the junior scientists; and research managers, generally the senior scientists. The miners are boring at the bottom of their wells and are not supposed to be competent in the superficial structure of the extracting field; on the other hand, the managers only have knowledge about the superficial structure and ignore what precisely happens in the different wells; they must ignore it, otherwise there will be no more room left in their brains for their part of competence. Hence keyword thinking is the way of thinking managers have to use, whilst miners develop specialized jargons that are only understood in their own wells.

No scientist can work as a miner during his whole careeer. Generally, he works in a well at the beginning, and rapidly becomes too old for this kind of activity. So he will have to become a manager sooner or later, and then he will work on the surface. He will no longer have to understand the precise technical meaning of the jargonistic terms used at the bottom of the wells.

3. How keyword thinking works.

The technical sense of jargon lies in some specific know-how; the mathematical language, for example, is the most sophisticated of such technical jargons; if a mathematician writes (h²/8p²m)Dy+ K²(x²+y²+z²)y = 0, another mathematician understands not only that it is a partial differential equation, but also that there are some functions y that satisfy it, and he knows the methods to find them, or to compute them numerically. If a physicist says ``the Schrödinger equation for a harmonic oscillator'', another physicist will understand this phrase as representing (h<sup>2</sup>/8p<sup>2</sup>m)Dy+ K<sup>2</sup>(x<sup>2</sup>+y<sup>2</sup>+z<sup>2</sup>)y = 0, and know how to handle it. In keyword thinking, however, it suffices to know the phrase: neither its mathematical (symbolic) expression, nor the methods to solve the equations, nor its physical meaning are requested. By way of compensation, keyword thinking is rich in associations: the keyword thinker who hears from ``the Schrödinger equation for a harmonic oscillator'' will instantaneously be aware of the connections with quantum mechanics, eigenvalues, quantum field, creation and annihilation operators, etc, without understanding at all the technical sense of these related concepts. Another example, the Fast Fourier Transform (F.F.T.) first had a technical meaning in numerical computing: it was a powerful algorithm for rapidly computing Fourier transforms, and the miners who worked in the wells of image processing were able to program this algorithm. In keyword thinking, it is not useful to know the algorithm; it is not even necessary to know that it uses some guileful decomposition of matrices; only the associations are of interest, for example the associations with signal filtering (low- or high-pass filters), deconvolution, contour extraction, phase reconstruction, texture recognition, etc. That these associations can come to the mind without any technical understanding of low- or high-pass filters or deconvolution is the root principle of keyword thinking. Moreover, for a manager in engineering, it is not useful to know that Fast Fourier Transform has anything to do with Joseph Fourier (a French mathematician of the early nineteenth century), the heat equation, or something called Fourier series: on the contrary, this would encumber the manager's mind and be prejudicial to his rapidity of decision and efficiency. Keyword thinking is based on associations, but uses only the pertinent ones. Within a small area corresponding to one speciality, the associations appear spontaneously and do not need any training. The brains of workers who are using some specialized jargon will automatically generate associations between the technical words of this jargon. This is merely due to the neuronal structure of brain. So if in the course of the professional training of a science worker or engineer we consider the part of time that is devoted to create such spontaneous associations, in relation to the total time of training, we see that it is infinitesimal. This ratio r explains the efficiency of keyword thinking: if ten years are needed to train a miner for one given well, then it is theoretically possible in the same period to train a pure keyword thinker to cover 1/r wells.

4. A reformed schooling for science managers?

In the ideal organization of modern science, keyword thinking will be the thinking mode of managers, whereas specialized thinking (jargon) will be the thinking mode of the miners, the obscure workers. At the present time managers always begin their careers as miners (on the way to Ph. D.). In § 2 above I said that ``no scientist can work as a miner during his whole careeer. Generally, he works in a well at the beginning, and rapidly becomes too old for this kind of activity. So he will have to become a manager sooner or later''. This is the way things are today, but it is not proved at all whether this career scheme is optimal. I observed that many managers, though experienced in pure management, are unable to attain full objective judgments in writing research reports or conceiving research policies, because they began as miners. To have worked in some particular well during the early career may brand the mind for life, so that the manager will then give too much importance to his earlier activity. Therefore it could be necessary to change the training of future science managers by creating special schools in which they will not study the methods of mathematics, physics, or biology, but only their keywords and the managerial sense of these keywords (instead of the technical sense). I frequently observe that today's managers are amateurs: as they were students they were trained for research and not for management; in other words they were educated for working in wells, as miners. Everywhere in the world, the universities or research institutes are providing graduate courses of science, in which the purpose of the teachers is clearly to make the students able to understand the laws of nature, the deep sense of natural philosophy, and to continue the work initiated by Galileo, Kepler, and Newton. This kind of teaching made sense in previous centuries, but cannot be maintained in the future. Nowadays the Big Science needs: a) obscure workers who are trained to work at the bottom of extremely narrow and deep wells; b) managers who are trained to optimize the sites of the wells and to organize the work of the miners. The fact that people work as miners as long as they are young, and later become managers, is strongly prejudicial to the efficiency of the whole system: imagine that in industry, the managers were all former workers! For this reason, it will be necessary for preserving efficiency, to fire the miners when they become too old and then to use them as teachers for the next generation of miners rather than as managers. The efficiency of modern industry is based on the division of labour: on the one hand, there are workers who do not understand the sense of their work; on the other hand managers who have no idea of the technical aspects of the work. Since the middle of the twentieth century, science has undergone a complete metamorphosis like the industrial revolution: from the artisanal structure of ancient great minds, Science has been transformed, by the mere force of progress, into Big Science, the industrial structure of obscure workers and managers. Now the problem lies in the fact that, unlike industry, Big Science is not yet rid of the relicts of the old artisanal science. The stupid illusion of scientists who continue to believe that they are the successors of the ancient great minds, that their work is a matter of inventiveness rather than mere labour organization, must be eradicated.

Thank you for your help, Sarah.