Jeremy Rifkin, The Zero Marginal Cost Society, Palgrave MacMillan, 2014

French version

I ended up getting The Zero Marginal Cost Society, despite the disappointment felt after reading the previous book of Rifkin, The Third Industrial Revolution.

This book is built on a gross fallacy. Here's where it is expressed:

"Economists have long understood that the most efficient economy is one in which consumers pay only for the marginal cost of the goods they purchase. But if consumers pay only for the marginal cost and those costs continue to race toward zero, businesses would not be able to ensure a return on their investment and sufficient profit. That being the case, market leaders would attempt to gain market dominance to ensure a monopoly hold so they could impose prices higher than the marginal cost, thus preventing the invisible hand from hurrying the market along to the most efficient economy. This is the inherent contradiction that underlies capitalist theory and practice".

Rifkin believes, therefore, that marginal cost pricing is efficient even when this cost is zero!

But this pricing is only efficient if the market obeys the regime of perfect competition, which implies that the marginal cost is not zero (see Eléments de théorie « iconomique »): hence Rifkin's reasoning combines two assumptions that are mutually exclusive.

When the marginal cost is zero, the firm must of course cover the fixed cost of production and thus, contrary to what Rifkin says, offer an average price that is at least equal to the average cost (for example sell at first a new product at a high price, and then gradually lower the price). This is what happens when the market obeys the regime of monopolistic competition, that apparently Rifkin ignores.

The logical fallacy of his reasoning ruin his conclusion at the "end of capitalism". That capitalism disappears would be strange in an economy where the cost of production condenses into a fixed cost that is pure capital.

Rifkin had announced the "end of work" in 1997. In 2011 he located in new energy (wind turbines, solar panels, etc.) the "third industrial revolution". He continues to publish fallacies with this new book and many readers enjoy it greatly.

The media success of Rifkin is a painful sight for those who have, despite everything, some respect for the human nature.

Travel in the country of Programming

(In French : Voyage au pays des programmeurs)

I have a bad habit: when I do something, half of my attention is spend in watching the action in progress. This earned me a bad ranking on these tests which evaluates the intellect as the timeliness of responses.

Enjoying a little free time in August, I went back to programming and it allowed me to do a few observations on myself. It is good to remember the episodes where one encounters obstacles (see mon apprentissage de LaTeX): it helps to avoid making the same mistake repeatedly.

Experienced readers will find me ridiculous because I'm neither a professional programmer nor even a good programmer, but I don't mind. Those who believe that programming is an ancillary activity will stop reading me if they never read me, but I don't mind.

*     *

I confess: I love programming. I am a clumsy, inexperienced freshman, but this experience gives me the joy of exploration. When it works, I am delighted to have been able to bend the computer to do what I wanted him to do - it's much more satisfying than using a program written by someone else.

So I decided to program the methods of data analysis that I taught at ENSAE during the 70s. At the time I did not know programming, so I used the programs written by others and it annoyed me. I had to take revenge on this ignorance.

I know that there are excellent software for data analysis and that what I would do would bring nothing new, but my goal was not to launch a new product on the market.

Here, highly condensed, the story of this adventure.

The supidity of intelligence

French version : "L'imbécillité de l'intelligence"

Le Monde has published an enlightening article on the Snowden case (Aymeric Janier, " target=”_blank”>Keith Alexander, le « pacha » de la NSA", Le Monde, July 15, 2013).

37,000 employees, a budget of about $ 10 billion, ultra-powerful computers, the ambition of "intercept everything about everything, everywhere" ... We guess in Alexander's behavior a bureaucratic delirium : who could refuse him budget and computation power after September 11 2001, which has spread this obsessive fear that is the victory of the terrorists ?

Checklist of the information system

French version : Check-list du système d'information

To troubleshoot an engine one must seek first the most frequent failures, then move gradually towards the rarest (first ignition, then the air filter and fuel supply, then the carburetor, etc.). This allows on average to troubleshoot faster.

The "checklist of the information system" allows us to assess the quality of an existing system and prescribe the measures that will "help out". It begins by examining what happens on the workstation of the users, then it jumps to the other end of the information system to review the decision support system. Having taken the SI in a pincer, it moves on its architecture (organization of responsibilities, semantics). Finally, it considers the control of the information system from the point of view of the functional evolution, the technical platform and the economy.

1) Workstation

Operational information system

Have agents often to do manual re-keying? should they, in the same operation, connect and disconnect for various applications?

Are clearances clearly defined? Are the access rights of each agent automatically assigned when he identifies and authenticates its identification? must the agent identify several times in a day?

Is impression management effective? Are the mails sent by the company of good quality?

Are the agents adequately supported by the information system in the performance of their duties?

Does the company perform a periodic survey on the satisfaction of the users of the information system? Are decisions taken following the results of this survey?

An essay on industrial classifications

(Article by Bernard Guibert, Jean Laganier and Michel Volle in Économie et statistique No 20, February 1971)

French version: Essai sur les nomenclatures industrielles.

There can be no economic analysis without a classification. Only a classification can give precise enough meaning to the terms that crop up so often in economic reports - "textile industry", "furniture", "steel industry" and the rest. Classifications play an absolutely crucial role, but they tend to be dismissed as tedious. They consist of tiresome lists with only the occasional intriguing oddity to break the boredom. A classification specialist is seen as a real technology geek, and has to be exactly that to answer the seemingly hair-splitting questions (s)he is faced with every day: should the manufacture of plastic footwear come under footwear manufacture or under manufacture of plastic products? What is the distinction between shipbuilding and the building of pleasure boats? Should joinery be classed as manufacture of wood and wood products or as building construction?

The limit of statistics

In French : La limite de la statistique.

We know that statistics is not appropriate to describe a small population. We can certainly count the individuals who compose it, but it will be virtually impossible to go from description to explanation.

In fact, explanation requires that we find in the statistical observation clues that guide us to causal hypothèses, between which we will choose based on the accumulation of past interpretations provided by the theory.

We find these clues in comparing the distribution of a character between different populations (eg, comparing the structure of age between two countries or between two times in the same country) and in looking at the correlation between characters within the same population.

One can always extract a representative sample in a large population, that is to say that distributions and correlations observed in this sample are not substantially different from those that could be observed on the entire population because the clues they provide lead to the same hypotheses.

Here is the test that will tell if the size of a population is sufficient to interpret its statistical description: that population must be able to be considered a representative sample drawn from a virtual population of infinite size whose structure is explained by the same causes that the population considered.

*     *

Some populations are therefore not "statistisable" (please forgive this neologism). For sure we can count their individuals and calculate totals, averages, dispersions and correlations, then publish it all in tables and graphs: but this morass will be impossible to interpret, we cannot move from this description to an explanation.

This is the case, for example, for much of business statistics: it often happens that the production of a branch or sector is concentrated in a few large companies whose number is too low for this population being “statistisable".

There is a remedy: if it is impossible to interpret a statistical description, we will use the monograph. The search for causal relationships at work in the population will no longer consider distributions and correlations, but consider each individual case in its particular history.

Of course history never provides more than assumptions, because the past is essentially enigmatic, but after all statistics also provides in the best case only assumptions... but they are not of the same nature, and the monograph requires a depth of investigation which statistics does not require.

The world of nature is ultra fractal

In French : Le monde de la nature est ultra fractal

Whatever the scale at which they are considered, fractals have the same degree of complexity. This is for example the case of the coast of Brittany: whatever the scale of the map, it is shredded. Magnify the detail of a fractal reveals a pattern similar to that of the entire drawing.

Examination of a natural object - whether the whole universe or a speck of dust - let appears, when the scale is changed, a series of views of the same complexity - but unlike Fractals they are not similar.

Consider the universe. Its geometry is non-Euclidean (space is curved). At the level of everyday experience the geometry is Euclidean. We find clusters of molecules in the grain dust examined by electron microscopy. Later we will encounter atoms, then the probability waves of quantum mechanics. Farther particles appear. We could go on, we could also select other scales ...

In the thinnest detail of nature lies, as in a fractal, a complexity which is equivalent to that of the whole. However each of the scales follows a peculiar geometry. This adds another kind of complexity to the complexity of the fractal. Nature, being essentially complex, is "ultra-fractal."

*     *

The examination of any physical object - your hand, a pencil, a speck of dust - can never achieve a detailed and complete description. This despairs those whose only absolute knowledge can satisfy the thirst for knowledge, but "absolute knowledge" is a mirage consisting of words that should not be juxtaposed.

The destiny of every human being is the both comic and tragic theater of the dialectic between the ultra-fractal world of physical, human and social nature and the world of values that animate his intentions. . This dialectic is the action.

To act he doesn't need an absolute knowledge: he needs only a relevant knowledge, that is to say a knowledge that is adequate to the action he intends to achieve. This knowledge, being expressed in a finite number of concepts, will always be simple compared to the complexity of nature.

The concepts that are necessary to driving - identifying obstacles and signals, anticipating the behavior of other drivers - select for example, in the complexity of the visual spectacle, a finite number of events. It is the same for all our actions: explicit thought is always simple and it is best to reserve to nature the qualifier "complex" ("complex thought", expression dear to Edgar Morin, is an oxymoron) even if a thought can be complicated in the sense that its acquisition requires a long apprenticeship. By cons the process of elaboration of thought is complex because the brain belongs to the world of nature.

*     *

The contrast between the simplicity of thought and the complexity of nature invites to postulate that this complexity is unlimited (that is to say not only infinite as a right line, but without limit). This hypothesis is an axiom because we can neither prove it nor demonstrate the opposite.

This axiom has the consequence that any mathematical theory, that is to say any logical structure based on a non-contradictory battery of axioms, is the model of a phenomenon belonging to the world of nature: thus the non-Euclidean geometries, created as an exercise in pure logic, provided subsequently a model for the geometry of the cosmos). If this was not the case, this theory would be a limit to the complexity of nature.

A mathematical theory can wait a long time or even never encounter the phenomenon it models because, being not revealed by experiment has revealed, this phenomenon remains is buried in the complexity of nature: but we are sure it exists. This confers to the math a radical realism, with an obvious caveat: if any mathematical theory models a phenomenon, it does not model all phenomena. It follows that the ambition of a "Theory of Everything" in physics is a mirage.