Systems science is a scientific discipline that aims to regard its objects holistically. This implies to observe systems in their context, in an environment of multiple interactions. While conventional scientific approaches rather aim to free their objects of context and try to investigate them without any impurities, so to speak under clean laboratory conditions, systems science is interested in the externalities that are caused by the influences of context.
An example to illustrate this ambitious approach, provides the so called Kaibab overshoot (Ford 2009), a sudden irruption of deer population that was observed in the 1920ies on the Kaibab Plateau on the north rim of the Grand Canyon, leading to widespread environmental damage in this area caused by rising numbers of deer that fed on every plant they could find. While conventional scientific approaches would focus on the deer population itself in order to find the causes of its sudden growth, a systems scientific approach might suggest to connect the deer irruption to the extinction of its predators, wolves in this case. This approach would assume an ecological system with several rather complex interacting dynamics. The ecologist Aldo Leopold famously coined the phrase “thinking like a mountain” in this respect, alluding to the necessity of having a complete appreciation for the profound interconnectedness of the elements in an ecosystem.
Ford, Andrew (2009). Modeling the Environment. University of Michigan. Island Press.
Systems science hence is concerned with the interaction of dynamics with other dynamics, or of systems with other systems. Since systems in their turn can be regarded as components of higher-order systems, as systems in systems so to speak, this approach concurrently necessitates to consider the interaction within systems. Systems science hence is attentive to the consequences of two kinds of interactions: the interactions of a system with its environment, and the interactions of the system's components. Systems science strives to consider the context of a system and its internal constitution.
The intention to observe objects holistically is ambitious, but somehow contradictory. On the one hand, to consider context and interconnectedness implies to overcome delimitations. Systems would have to be considered as open to all possible influences. Exactly this however, on the other hand, undermines the conception of system itself, as being a distinct and delimited entity in its environment. If systems are to be considered in interaction, they cannot be regarded as delimited at the same time. This problem is recurrent in the philosophy of science. Since pleas against scientific objectivism and for the contextualization of objects have been voiced several times in history, one might as well ask what exactly the novelty is that systems science suggests. What is the value added of this methodology that makes it worthwhile to consider it a productive scientific alternative?
The difference that makes a difference in this case, is the digital computer. Systems science, as it is introduced in this textbook, builds on the calculating capacities of digital machines. It counts on the possibility to enhance our attentiveness and awareness for the consequences of interactions with the addition of computational power. This is not to say, that computers can overcome the mentioned contradiction of objectivism and contextualization in principle. But they seem to be able to expand our analytical possibilities in respect to the dimensions of interactions considered. As we shall see, only with the digital computer, aspects like the emergence of new global properties from local non-linear dynamics could be inferred in a scientifically satisfactory way.