The quest of meaning coincides with the search for answering the four essential questions raised by Immanuel Kant (1724-1804) in course of the European enlightenment:
On the previous pages of this page sequence, we addressed already aspects of the first three questions briefly, or sometimes with a certain level of depth. For a comprehensive coverage of our current subject, let us summarise and integrate the main findings at first. We start with a discussion of the first question and the specific human intellectual capabilities. The next two questions are associated with the intelligibility of reality in general.
The main focus of the content below lies in the ethical implications of the fourth question. It is not the attention here to raise universal ethical principles. Preferably, the ethics of systems engineering must be discussed in the particular application specific context. The way humans identify their needs, how needs turn into motivation, and how motivation leads to action are as well common enablers as common constraints for ethical behaviours. Thus, we will concentrate on the cognitive capabilities controlling human action.
Humans share the principle organic architecture of their nervous system at least with all other vertebrates. As evolution follows the mutual principles form follows function and function follows form, the similarities of organic structures support similarities of resulting functions. What is proven for simpler organic functions in many instances most likely applies to complex brain functions as well. It is further reasonable that with increasing brain complexity new complex functions emerge. On this basis, it is possible to investigate the evolution of nervous systems regarding their functional impact although we are far from understanding complex brains in detail.
Brains operate basically by perceiving concrete scenarios, analysing its meaning and concluding appropriate actions, or in other words: Brains perform systems thinking. By their actions, individuals shape their living environments, many times accidentally, but sometimes also intentionally, e.g. they perform systems engineering. This includes the production of tools enabling otherwise impossible goal achievements. New inventions spread by imitation, occasionally including continuous improvement of tools and operation techniques by other individuals.
Humans surpass other species due to the capability of using argumentative language. It is the current view of leading anthropologists including Michael Tomasello that argumentative language may be the sole but is at least the main feature constituting today’s human dominance in the biosphere. Argumentative language allows time-logical explanations for understanding scenarios in the sense David Hume (1711-1776) has defined causality. In addition to imitation, the dissemination of inventions is supported by argumentative language for motivation and explanation. Overall, argumentative language improves social interactions and enables a high variability of social behaviours and social relationships beyond other genetic dispositions determining hierarchical dominance.
Argumentative language allows the generation of theories about phenomena beyond the capabilities of human senses. These theories provide forward and backward translations assisting in inventing and applying new technologies. Kant’s question two – What can I know? – and three – What may I hope? – together cover two concerns: First, is the whole real world intelligible by human invented theories? Second, is there a single universal theory integrating all other theories and capturing all phenomena of the real world at once?
There is significant evidence that both claims are deniable with some evidence provided already by previous considerations of this page sequence. It is worth to illustrate the reasoning in condensed form. First, we will turn to two examples from physics. We will continue with summarising the limitations of strict logical formal languages. Finally, we extend our considerations to natural languages with their nearly unbounded semantical complexity.
Is time continuous or quantised? This question is undecidable. All measurements of physical phenomena rely themselves on physical phenomena with quantum leaps as the lowest resolution known. According to basic physical theory, quantum leaps taking place in infinitesimal time would require unlimited power what would support a claim for continuous time, respectively the possibility of higher time resolutions than measurable. On the other hand, we do not even know, if the concept of time could be reasonable without a physical world at all. Paradoxes like this point us to the limits of acquirable knowledge and let raise doubts regarding the universality of theories and pure reductionistic world views.
The detection of quants revived Gottfried Wilhelm Leibniz’ (1646-1716) hypothesis of monades in the sense that all worldly phenomena are caused by quants, their states, and their state changes. Logically, this hypothesis is easily validated: If quants are the unique smallest building blocks of reality, then the whole physical and imaginable world is made of quants. Just one unmentioned contextual detail is debatable: the role of the human observer.
We have little reason to doubt the existence of a unique and universal reality. All alternatives result in flavours of solipsism assuming reality as a mere construct of an individual intellect or a kind of super-intellect. Solipsism does not lead to any epistemological progress. For the human observer, the universality claim is dependent on the most advanced human cognitive capabilities, e.g. the availability of argumentative language. Is argumentative language fully suited to provide unambiguous translations between theories in all directions without information losses, and what would be the character of unambiguous translations? The latter question may be simply answered claiming unambiguous translations must be reasonable. In our discussion, we set reasonability equal to the causality criteria according to David Hume’s definition.
As an example for translations between theories, we take again Ludwig Boltzmann’s (1844-1906) theorem linking classical mechanics and statistical mechanics, e.g. how the energy state of individual molecules in a gas volume are related to pressure and temperature of the whole gas volume. For the translation from classical mechanics to statistical mechanics, the translation works under two conditions: either we assume that all molecules share the same energy state, or we identify the energy state of all molecules. The first condition is unrealistic as the occurrence probability of the condition lies in the magnitude of a once-in-a-universe event. Practically, we cannot conclude the features of the whole from the energy state of a single molecule. With respect to the second condition, the identification of the energy state of every molecule is unfeasible. Due to physical interferences, measurements of the energy state of every molecule would result in massive, incalculable distortions of the temperature and pressure of the complete gas volume. Nevertheless, in theory an unambiguous translation works without information loss. This does not hold for the opposite direction. Only statistical statements on the energy state of a particular molecule may be derived without considering the actual trajectory and past collisions with other molecules of the particular molecule. In general, the example illustrates the limitations of reductionistic world views. The emergent properties of the whole – in our example temperature and pressure – may be determined from the parts if the existence of those features is known upfront. Potentially, further emergent features of the whole may come as a surprise. In the opposite direction, the features of the parts cannot be deduced from the whole without information losses. These findings set limits to claims for the unique and universal intelligibility of reality.
Now the reader may be a bit puzzled about associating a physical law expressed in mathematical formula with argumentative language. The reason and the validity of this move may become clear below. We go even a step further by interpreting arithmetic as a strict logical formal language for investigating the limits of logic and causality. In their Principia Mathematica, Alfred North Whitehead (1861-1947) and Bertrand Russell (1872-1970) define arithmetic based on pure logical axioms. The first surprise is provided by the existence of prime numbers. No mathematical formula determining the sequence for the occurrence of prime numbers exists. Their occurrence is arbitrary. We must conclude that even strictest logical rules may lead to disorder. Kurt Gödel used prime numbers to express basic arithmetic symbols, e.g. definitions and operators. Then, the prime factorisation of other numbers may be used to express arithmetic theorems in arithmetic itself. For some hypothetical theorems, their validity may be proven within arithmetic, for others that they are invalid. In addition, hypothetical theorems are proposed arithmetic can neither prove that they are true or false. Kurt Gödel’s undecidable theorems may be generalised as follows: In any strict logical formal language issues and questions may be raised that cannot be solved within the scope of the particular language.
For natural languages, Juri Lotman (1922-1993) has coined the term semiosphere. In analogy to the term biosphere as the world of biology, the semiosphere denotes the world of language. He uses the term recursively like we use the term system. A semiosphere may contain other semiospheres like the family of Indo-European languages, dialects, discipline specific languages and so forth. Principally, research on the semiosphere has concluded the same results as the scientific theorists Thomas Kuhn (1922-1996) and Imre Lakatos (1922-1974) have concluded on the sociology of science. Thomas Kuhn talks about scientific paradigms and Imre Lakatos about research programmes. Briefly summarised, all talk about the life cycles of languages. Languages are initially formed to serve particular purposes, evolve extending their grammar and semantics, and reach out for generalisation. They become fuzzy and challenged at the periphery. Their owners and supporters start fighting against the periphery for defending the paradigm. Paradigm changes happen usually when someone close to the centre of the semiosphere adopts the concerns of the periphery. This narrative allows manifold interpretations and applications. For our subject, we can learn how we overcome the limitations of strict logical formal languages: We just invent new language! Without going into details here, this happens always when we engineer innovative complex systems.
Our actions depend on our perceptions. Behaviourism assumed behaviour is to be explained by the perceptions of the external world exclusively. Consequently, all living creatures including humans would operate as some sort of deterministic automata. Henry Maslow (1908-1970) opposed such radicalism emphasising human individuality: Humans act according to their needs. He also claimed a pyramid of needs. A particular need drives human action when needs on lower levels become satisfied.
In the context of the human capability for using argumentative language and the corresponding richness and variability of social behaviours, his findings support a view that body state needs have precedence over social needs – a statement compatible with the evolutionary fact that argumentative language resides cognitively on top of all other cognitive capabilities inherited from the brain architecture of other vertebrates in the course of evolution. Consequently, precarious living conditions leaving basic body state needs unsatisfied limit the unfolding of material growth and societal progress.
Our species emerged from earlier hominids more than 200 000 years ago. We do not know to what extent our evolutionary ancestors had developed argumentative language already. Our species possessed argumentative language and the corresponding social capabilities up from the beginning. There is no reason that cognitive dispositions have changed since then. What has changed over time was the climate on Earth. Around 200 000 years ago the world became significantly colder hampering the opportunities for extending human settlements. Since then, two major interglacial periods are identifiable, the first one about 130 000 years ago. The second began less than 20 000 years ago. Sea levels rose approximately linearly by 120 meters within less than 10 000 years.
As commonly known, humans emerged in Africa. Coincidently, Africa consists mainly of lot of the oldest land masses. So-called cratons have not altered much by the geological forces vulcanism and subduction. Dominant is the third geological force shaping the Earth’ surface: erosion. Rich deposits of minerals and metal ores are located deep under the surface. This is one potential reason why humans in Africa had not developed metallurgy earlier. The fertility of human habitats allowed a reasonable living and thanks to the social capabilities of humans they not only survived but were able to increase human population and to settle into regions with harsher living conditions. This all changed with the end of the ice age. Former habitats became arid land. People migrated into remaining niches, for example to the Nile valley and coastal regions in the northwest of Africa when we talk about former human populations of the Sahara region, or migrated to latitudes further north where living conditions were improving due to climatic change. There they found soil fertilised by abrasions from glacier movements providing agricultural conditions much better as known from their earlier habitats, and metal ores close to the surface. The better fertility of the soil enabled permanent settlements. Humans entered an accelerated path of growth, and invented civilisation. The invention and sustenance of irrigation systems led to societal structures with an unprecedented level of workshare, specialisation, and standardisation far beyond the former social practices.
Please, don’t read the story of the last paragraph as a strong causal explanation of human prehistory and history. There are myriads of other traits and interdependencies in addition. All attempts to reduce the complexity of human prehistory and history in one paragraph cannot satisfy scientific standards at all. The paragraph just collects some evidence for three hypotheses: First, the neolithic revolution was no revolution in the sense we use this term in other historic instances. Agriculture developed most likely over time periods exceeding the duration of historic times by far. Second, human cognitive and social capabilities have not changed with the emergence of civilisations. Considering the comparably short duration of historic times, we may talk about progress in the sense of a cultural evolution but not about progress in the sense of a biological evolution. Third, our cognitive and social capabilities may be not fully adopted to cope with the complexity of the societal architectures we create. Advanced societies may develop societal architectures hardly to be transformed in cases of massive internal and external threats. Specialisation inherits a risk for reductionistic views and may have contra productive impacts when more holistic views are required to identify strategies and solutions to cope with those threats. Sound processes, methods, and tools for multidisciplinary cooperation are an important prerequisite for successful societal transformations.
For this section’s subject – motivation and action –, the considerations above provide some hints on a reasonable scope of our investigations. We start with what human needs are and how needs drive action. Then we turn to the relations between individual needs and the behaviour of social groups analysing major social motivation systems. We continue with discussing the characteristics of social motivation systems in a societal context. We close with a survey on the dynamics of motivation cycles within individuals and social groups.
Humans have many needs at once. Some are concerned with maintaining existential living conditions for survival or a more comfortable state of well-being, others with desires and hopes regarding an anticipated future state of well-being. The grade of need satisfaction may be partitioned in four categories: unsatisfied, precariously satisfied, comfortably satisfied, and over-satisfied.
Needs are unsatisfied when there is a desire for a change from the present state to something better. They have the potential to become action-driving when other high-priority needs are satisfied and opportunities for their fulfilment arise. Precariously satisfied needs are satisfied but remain action-driving due to fears to fall back into an unsatisfied state again. The priority to invest in precariously satisfied needs may even exceed the priority allocated to unsatisfied needs. When needs are comfortably satisfied, the investment for need satisfaction falls to a maintenance level, or below in case that the need is felt as something given by default. Over-satisfied needs may become a major concern when they remain action-driving without reducing the priority to a maintenance level. Then, continuing high investments in their satisfaction do not improve the well-being further. Over-satisfied needs come along with greedy and addictive behaviours.
Greed and addiction are a threat to every social community. This sheds a new light on the history of civilisations. The anthropologist David Graeber (1961-2020) and the archaeologist David Wengrow provide comprehensive evidence that human communities of the past constituted themselves by choice. Of course, prehistory was not free of fraud, robbery, and violence but patriarchal government executing authoritarian power may have been the exception among a huge variety of other social leadership arrangements. For executing power projections against the will of people successfully, rich resources are required to force and to sustain authority. More likely, it was widely a free choice of people to cooperate and to found civilisations due to expectations to satisfy individual and commonly shared needs.
Let us now consider the following statement: The agriculture production in Egypt achieved a surplus and then the Egyptians built pyramids. Due to the general characteristics of argumentative language and narratives, we are tempted to interpret the sentence in a way that economic profit from agriculture was achieved for the purpose of building pyramids. More convincingly, the increase of agricultural production by irrigation systems had the sole purpose to feed the population. When societal leaders recognised that agricultural overproduction led to greed and addiction, they feared the detrimental impact on societal stability and invented new transcendental needs to consume the surplus. The solution to move gigantic amounts of soil, clay, or stone to construct monuments seems to have been a standard solution in early civilisations around the world.
It is a common pattern that human cultures do not develop following a great plan but more on a trial-and-error basis. Whenever new unknown threats are identified new societal needs and solutions must be developed for survival. If a civilisation is not able anymore to adopt to challenges, it is doomed to collapse. In other words, civilisations need multidisciplinary systems engineering. Without setting and agreeing on feasible societal goals and breaking them down consecutively in feasible objectives for all parts of society, all institutions of a society may try their best defining objectives on their own. Then, resulting actions are likely biased by defending the institution’s survival. Rampant bureaucracy may lead to collateral damages. The capability to alter societal architectures appropriately is hampered or may be lost totally.
Congratulations for approaching this concluding section after reading the five pages of this website’s initial page sequence. Each page is written to be understandable in isolation from the other pages and provides hopefully beneficial information for someone interested in systems engineering. Nevertheless, the page sequence follows a deliberate line of thoughts from clarifying basic systems engineering terms and concepts first.
Novices to and practitioners of systems engineering may profit directly from the concise recommendations for how to engineer high-integrity technical systems. However, experience has shown that readers may feel uneasy that applying just these four principles consequently for implementing systems engineering will make a difference and may even turn systems engineering projects in crises into successes. After reading systems engineering textbooks and standards you may have got reservations that the complexity of the subject and the intricacies of how systems engineering is presented cannot be reduced to just four practical implementation principles. I fully understand these concerns because I challenge the practicability of systems engineering textbooks and standards due to their illusionary assumptions that are even many times introduced silently instead of being stated explicitly. Compulsorily, omissions, incompleteness, weaknesses, and inconsistencies hamper the practical applicability of the provided instructions and recommendations.
Multidisciplinary systems engineering is an advanced civilisational activity essential for improving and sustaining mature societies and enterprises especially when existing societal or technical system architectures are threatened and demand alterations. Human cognitive and social capabilities need to be exploited up to their limits for leading systems engineering projects to success. For this reason, successful systems engineering as a primarily human endeavour requires a reasonable understanding of epistemological boundaries in addition to knowledge of solution specific technologies. Consequently, the further two pages concentrated on human cognitive and epistemological capabilities.
And now the caveat: The four principles are fairly straight and sound simple but implementing them is a rather complex and challenging undertaking. The good news is that this website provides further information on the Theory of Systemgestaltung. The Theory of Systemgestaltung is a flow-oriented implementation of systems engineering carefully designed not to jeopardise the four principles. Exploiting the narrative of Norbert Wiener’s general feedback theory, systems engineering is presented as a set of four basic systems engineering narrations. Each narration obeys causal principles allowing a direct time-logical implementation without getting tangled in circular dependencies. Together, they provide a comprehensive description of the intricacies of systems engineering enabling the successful evolution of High-Integrity Technical Systems. Please, turn to the Knowledge Category for further valuable information on the Art of Systemgestaltung that introduces the Theory of Systemgestaltung in general without becoming confused by or lost in detailed process requirements, data structures and fine-grained implementation hints.