21 January 2021

Converting information into knowledge


Converting information into knowledge


Topic by Mariona

Essay by Lawrence


This is a very specific issue which could easily be deceptive, and maybe even lead us into the rabbit hole of philosophical debate of what is knowledge and information. There is no doubt that sooner or later we need to have some sort of definition of what knowledge is.


So the question for us is not “what is the difference between information and knowledge”, but rather what must happen to information to become knowledge. And are we justified to assume that information can be converted into knowledge? We can also understand “convert” as a causal action conversion. For example: converting flour, yeast, water, heat, time, and salt into bread. But the problem with this example is that we don’t have a single ingredient but an amalgam of identifiable ingredients coming together which at the end of the process we call bread.


On the website, Key Differences (1), information is defined as filtered data and knowledge as being able to filter information relevant to the subject. Alternatively information is the building blocks and knowledge the building. In our bread example, the causal conversion test is our ability to know what the ingredients for making bread are and then mixing those ingredients (building blocks) to convert them into bread.


But in my bread making example the “information” I gave is far from being the building blocks that are really required for bread making. This example is a language exercise to represent at a certain vague level of “understanding” the bread making process. This highlights a necessary condition in our debate, that the natural language we use to convert our information into knowledge must be precise information. Precision calls for accuracy which means that “information” (ingredients, building blocks) must be measured and measurable, thus introducing the need for a system to do the job of measuring; mathematics can take us a long way to help us convert information into knowledge.


Before we can convert information into knowledge we also have to breach the natural language barrier in the spirit of Ludwig Wittgenstein idea of family resemblance (check Wikipedia:family resemblance). Wittgenstein attributes our errors when using natural languages to failing to be critical about our use of language. This is important for us because information is usually presented to us in natural language format: Gran Via, 2 litres, flour, heat, 300 people, sample population, and so on.  So when we use such terms as flour, yeast and so on such terms refer to different things in different places. And there are many local reasons why they are different but what is certain is that many times recipes do not always turn out well in different countries. This fits very well with the idea of family resemblance issue and I speak from experience.


We can certainly argue that data is raw and in a sense objective; in the meantime let us not get involved that the data might be wrong. But our idea of knowledge is that when we speak of knowledge we are speaking of something that can be crowned as universal, and a feature of something universal is that it is repeatable. When we say something like “I know that Calle Fuencarral is corner with Gran Via” we are using “I know” to suggest that you are wrong if you suggest otherwise and not to confirm that I have a justifiable true belief.


The problem is not that knowledge may or may not be universalisable, but rather the content of the information has no family resemblance to the content when we still use the same language label for example flour. No matter how much we try to specify the label (word/name) at our macroscopic level there are subtle differences which will make flour bought in Munich different from the one bought in Madrid. Of course, the reason why I cannot make bread in Madrid might have nothing to do with the flour but maybe my oven which is not sufficiently hot for bread making! This leaves us with an element of uncertainty and bringing into doubt the universal element of knowledge.


Now compare the difference between my information about bread making (recipe) which was successful in London but not Madrid, and the periodic table of elements. The elements are more precise and supposedly more reliable than say generic language labels. But would we still be able make bread if we used the language of the elements rather than the traditional language of flour, yeast, and water? The romantics and traditionalists amongst us would be justified in wanting to know “how can we make traditional bread by using measurements of chemical elements?”


So far I have been discussing the ideas of knowledge and information in a material empirical context: Gran Via, flour, water etc. But are there other forms of information and knowledge that are not empirical but still require a causal effect to convert information into knowledge? Morality and jurisprudence come to mind, but I also want to suggest that even natural languages are subject to this conversion debate.


The Wittgenstein family resemblance debate requires that such languages have some common factors for them to avoid errors. The problem as I have tried to argue is that local conditions determine the meaning of local concept words in the local natural language. This can have devastating effects with translations and interpretation between languages. In a translation process the original text is the information and the target language text is the resulting knowledge. The problem is not with basic instruction texts, e.g. how to use a new oven, but conceptual texts, for example philosophical or literature texts. How serious is this problem for us?


We can add another example on how we can create errors in our knowledge due to deficiencies on natural languages. Let’s take the example: Do you speak English? (It could be any language) We might even ask what’s you level of English? These two questions can easily be translated into other languages, but these two questions do not give us any real knowledge about the language skills of the person. If we were to ask someone in the street whether they spoke English and they said “yes”, we would be justified to ask them where the 44 bus stop is in Gran Via. But is a “yes” enough to assume we can discuss such things as the importance of language in philosophy.


Probably we’re not justified to assume they can discuss philosophy. This is because to discuss philosophy we require a different kind of “yes.  Specifically: can you discuss philosophy in English? My point is that if knowledge is dependent on being presented in a natural language by definition we need a relational and relevant context to perform this task. Traditional language teaching and maybe mathematics for example can be learnt in an abstract context but this is unnatural for speakers of a natural language.


Physical systems or dynamic systems do change and mathematicians have studied these changes in catastrophe theory (but not exclusively). I am not interested in the mathematics of the theory but in the idea that small changes in a system can lead to drastic changes (catastrophe) that may convert the system to something else. What is important for us is that we have the conceptual means to measure these small changes and thus the change from one system to another. And then when these changes happen we tend to create a language reference or label to describe the new system. The classical example is a slice of bread converted into a toast. At what point does the slice of bread become toast?


In our discussion, is there a series of small changes that will eventually convert our information into knowledge? We can argue that the change from information to knowledge happens when we add more relevant information and use pre knowledge we might have acquired previously to bring about the outcome we desire. In effect not only is information converted into knowledge but also knowledge itself gives rise to new natural language concepts. For example a slice of bread and a toast: these two concepts are not the same, when we order a toast we don’t expect a soft slice of bread.


What is evident is that although we can move along the causal chain from data to information to knowledge, this chain will break when either the data or information change. And as a consequence knowledge will lose its aura of universalizability. I have not discussed wisdom because this is a slave to a stable knowledge base.


Best Lawrence


(1) Difference Between Information and Knowledge




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