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Kondratieff cycles and algorithms

Geschreven door Ben van Lier - 28 augustus 2014

Ben van Lier
Research into the origins and progress of the process of industrial development over a longer period clearly reveals, according to Schumpeter [1], that it always occurs in a long wave movement extending over a period of around 45 to 60 years.

He names this long-term cycle after the Russian statistician Kondratieff. According to the writer, such a cycle always comprises multiple factors about which no doubt at all exists. Although we cannot know with certainty at what stage in such a long-term cycle we are situated at present, algorithms could be one of the primary and characteristic factors of this cycle.

Kondratieff cycles

The first of the three Kondratieff cycles that Schumpeter investigated and named is the First Industrial Revolution (1780-1842) [2]. He also includes in this the long-lasting process of social absorption of the consequences of this revolution. He calls the second cycle the Age of Steam and Steel (1842-1897). The third and last cycle in characterised by the application and use of electricity, chemistry and engines (1898-?). The book written by Schumpeter about these three cycles dates from 1939 and we may therefore assume that the last cycle ended at some time during the Second World War.

The end of each long-term cycle is associated with a tipping point starting a new long-term cycle. The new cycle that begins at the end of the Second World War could be characterised by the subsequent Cold War, the developing mass production, and particularly the application of automation. In 1943, in a series of lectures, quantum physicist Erwin Schrödinger already laid the foundation for what we now consider bio-informatics (genetics, DNA and molecular research, etc).


In 1948, the American mathematician Nobert Wiener developed and described the feedback mechanism as a central element of what he called the theory of Cybernetics. This theory was developed further with the help of others, including the Englishman Ross Ashby. In the subsequent years, this theory became more and more the theoretical basis for the automation and control of autonomous processes for mutually-interconnected (parts of) machines.

Telecommunication networks

In 1943, the American mathematician and cryptographer Claude Shannon developed and published the mathematical theory of communication that formed the basis for the rapid worldwide development of telecommunications networks in the following decades. The basis for all these developments lies in the world war that preceded them. We are still confronted daily with the different manifestations that arose from this last long-term cycle, these taking the form of cars, holidays by air, computers, the internet, mobile phones, etc, which have come to define our daily life and work in the past decades.

Do algorithms displace human decision-making?

Now, more than sixty years later, we are possibly again at a tipping point on the way to a new long term cycle that is currently developing. We will only know for certain after a few decades what exactly the defining factors of this period were. One of these factors would already seem to be obvious, namely algorithms. Chris Steiner [3] describes an algorithm thus: ‘At its core, an algorithm is a set of instructions to be carried out perfunctorily to achieve an ideal result. Information goes into a given algorithm, answers come out.’

Algorithms are becoming ever more intelligent in their development, can observe and are increasingly able to adapt themselves to their environment or the changing circumstances in which they have to conduct their activities. They do all this free from their human inventors and developers. The essence of the value of algorithms is particularly in the speed with which, i.e. in a period of milliseconds, they can analyse very complex tasks, make decisions, and based on these decisions can carry out new activities. Algorithms are thus becoming a revolutionary development. Steiner also states: ‘As our world shifts from one where humans have made all of the important decisions to one in which we share that role with algorithms, the value of superior intellect has increased at a corresponding rate.’ (2013:215). Algorithms are thus, slowly but surely, becoming the new knowledge logic for man, organisation and society.

Need for an ethical framework

Algorithms are certainly not value-free in the sense that choices that are made by algorithms only consist of rational assessments that can be summarised in a 0 or a 1. The choices that are made by algorithms are partly based on considerations that have been included in them by the programmer, and it is therefore important that more attention is paid to these value-linked choices that are included in these algorithms.

Moral algorithms

The use and the application of ever more algorithms that carry out their tasks autonomously causes the need for a new and ethical framework for their development and management. By placing more emphasis on ethical aspects in the use and application of algorithms these can also learn to involve moral aspects in their analyses and decisions. To make moral algorithms possible, an ethical framework must be developed for the development and management of algorithms. Such an ethical framework could help in the development and maintenance of a form of morality for physical and software related bots or robots that are becoming more and more autonomous.

The need for the development and management of such an ethical framework for algorithms has become topical due to matters such as High-Frequency Trading in the financial sector and Network-Centric Warfare and the resultant use of, for example, ‘unmanned aerial vehicles’, also referred to as drones.

This discussion is also of importance in the development of, for example, Advanced Manufacturing or Industries 4.0. In this, it is assumed, for instance, that in the future: ‘Businesses will establish global networks that incorporate their machinery, warehousing systems and production facilities in the shape of Cyber-Physical Systems (CPS). In the manufacturing environment, these Cyber-Physical Systems comprise smart machines, storage systems and production facilities capable of autonomously exchanging information, triggering actions and controlling each other independently.’ [4] The questions that ought to arise concerning this industrial development are in what relationship, in what role and in what proportion man can still be independently active in an algorithm interconnected entirety of worldwide manufacturing processes that are dominated by robots and other smart and autonomous technologies.

Ben van Lier works at Centric as an account director and, in that function, is involved in research and analysis of developments in the areas of overlap between organisation and technology within the various market segments.

[1] Schumpeter, J.A. (1935) The analysis of economic change. The Review of Economics and Statistics, vol. 17 , no. 4, (May 1935) pp. 2-10
[2] Schumpeter J.A. (1939) Business Cycles. A Theoretical, Historical and Statistical Analysis of the Capitalist Process. ISBN 9781578985562
[3] Chr. Steiner (2013) Automate this. How algorithms took over our markets, our jobs, and the world. ISBN 9781591846529
[4] Securing the future of German manufacturing industry. Recommendations for implementing the strategic  initiative INDUSTRIE 4.0 (2013) Final report of the Industrie 4.0 Working Group

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