K for Knowledge

Readers of the sociology and/or the philosophy of science or knowledge have a hard time. Each discipline is evolving at such a high speed that is terribly hard for humans to follow more than 1 or 2 fields. Perhaps the choice of Karma instead of knowledge would have made it easier here. Alternatively, in German it is easy to find many nouns starting with a capital K. Kapital, Krieg, Kritik or Käsekuchen would have been popular, I guess. Soon I shall open the comments for suggestions for additional nouns, as part of the empirical “swarm knowledge strategy” rather than the theory-driven deductive method applied in knowledge generation on my side so far.
But wait, we are already in the middle of the unsatiable quest for knowledge. On a meta-level we would deal with the multiple ways to acquire knowledge and create new knowledge. Artifical intelligence is certainly one of the hypes at the moment. New data and new combinations of data drive us forward in the expanding universe and knowledge space. We have witnessed the disappearance of the thick printed encyclopedia in most households, replaced by specilised digital dictionaries or the network society’s shared knowledge base of “wikipedia“. Knowledge is linked to the history of ideas and Peter Burke is a prominent figure to rely on as a reference in this field. 20 years after “A social history of knowledge: From Gutenberg to Diderot” he published the much acclaimed: “The Polymath. A cultural history from Leonardo da Vinci to Susan Sontag” in 2020. To synthesise across the many “monsters of knowledge” over centuries is a daunting task. I like quotes like the one from Leibniz (p.77) “the horrible heap of books that is constantly increasing” and then his own continuation: “Printing, once viewed as a solution to the problem, had become a problem itself”. The whole section is devoted to information overload. Fragmentation of knowledge into disciplines and, much worse, the manufacturing of false knowledge create new challenges to knowledge. Maybe transforming the term to “knowledges” rather than knowledge is likely to capture better the differences between artificial knowledge, created by artificial intelligence and specialised algorithms, and human based knowledge. In knowledge storage we have lost the race with computers, but in deciding what are promising combinations between different fields of knowledge, we are still a wee bit ahead of the machines. Klara tell me, where is the exit, or your synthesis of the whole lot. Meanwhile I continue to read – what? books and the like.

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