1.3 Hyperlinked reality
Today, our social as well as technological conditions drastically differ from the time when our still often prevailing epistemological structures were formed. Only a few decades ago every analog medium (newspaper, radio, television, etc.) was organized rather independently. Due to their differing medial properties, there was only limited communication between them so that they functioned complementary. By the notion of digitalization this medial compartmentation is now replaced with a vast, homogeneous, digital infrastructure that tends to combine all symbolical transactions into one single medium. With the help of computers, the whole world gets seamlessly translated into digital signals. And thanks to the internet these bits and bytes are then automatically circulated, processed, and networked back into the system. The resulting extracts of data are often so big that they can’t be analyzed anymore by us humans alone, but only with the aid of computers again. Any media has always been an “extension of man”, extending not only our physiological but also our cognitive features. With the rise of digital media, a new door seems to have opened to formerly unknown depths of reality. Reduction was and still is inescapable. The world simply holds too many wonders for us to even register them, let alone understand. But what is different today is that we have new allies to meet our “wicked” presence. Not only can amounts of data be processed in seconds that would have taken several human lifetimes in the analogue age. But also, through the networking capacities of contemporary technology, silos of thought found a common, communicative infrastructure which used to be separated into disparate social and epistemic disciplines. As a result, a multiplicity of new connections is made bridging the demarcations and creating new fields of joint research. Slowly, a new understanding of knowledge emerges that works transdisciplinary and pays close attention to those intricate entanglements. Tree-knowledge is not able to represent these kinds of non-linear constellations because of its very limited organizational capacities. In this way, material reality has already transcended our conceptual and terminological framework. And contrary to the simple principle of linear reduction of the tree-knowledge there is an emerging awareness for complexity. A system can be identified as complex if its causal categories are intertwined in a non-linear manner so that their sum is greater than the single components. This means that the movements and flows in the system aren’t predetermined and can’t be fully predicted. Complex systems resist the idea of a preexisting and stable formal structure. The lateral interaction between the entities leads to modifications of their own qualities and the relations between them. Accordingly, their ontological functioning is based on emergence and self-organization. Tree-knowledge works in a much different way. In its hierarchical structure there are only linear relations possible meaning that every property of an entity must be easily deducible from its superior. In this system therefore the whole corresponds exactly to the sum of its parts. It postulates an ever static and stable framework with which every knowledge entity must coincide because of the assumed essentialist nature of things. Today, there is a discrepancy between our still traditional understanding and organization of knowledge and a completely different technological reality. Therefore, I think that from an epistemological standpoint there is no technological need any more to rely on the reductionist principles of the modern knowledge classification. Back in the day there was no way to work with multidimensionally complicated data the same way we do it now with the help of algorithms that run on our personal computers. Also, something as fundamental as change was so challenging to be taken in into account so that it had to be suppressed to a minimum. Contrary to that, the networked computational power of contemporary digital technologies allows for non-linear modes of organization that have structural instability and change at its very basis. We are now able to extract more and different kinds of data, circulate those huge amounts with highspeed and process all this material with much higher degrees of complexity. Against this backdrop, complexity here means that the enormous leap in terms of greater quantities also comes with altered qualities. We now see ourselves confronted with the multifaceted nature of things that necessarily had to be ignored because they were structurally so difficult to handle for predigital epistemological communities. The non-trivial, the wicked problems, the hybrids and non-binaries have come to the forth. Complexity is not a problem anymore, but a challenge. |
