“Where is the wisdom that we have lost in knowledge?
Where is the knowledge that we have lost in information?”
Because they invite error we should be wary of interchangeable terms and there are few that invite more than the terms data, information, knowledge and wisdom. The first two are easily muddled while the last two seem either elusive or too loaded to discuss.
However in an era of Big Data and information overload it’s important to consider what it is we talk about when we talk about data or information or when we say we ‘know’ something.
Though its origins are debatable, since around the 1980’s the DIKW hierarchy has been used as a model to help disentangle the terms Data, Information, Knowledge and Wisdom. Not very catchy acronym aside, its purpose is to define the relationships between the terms and provide a little insight into how we process information (though it’s not what we could call cognitive science).
Often represented as a pyramid, like Maslow’s Hierarchy of Needs, it places wisdom at the pinnacle and data at the base:
Let’s begin with data.
When we talk about data we are talking ‘discrete, objective facts’. How objective are they? Well they exist independently of us as records of reality although they are part of a system of symbols (such as numerals or language), however unless we want to fall down a semiotic rabbit hole it might be best to leave data as simply records of observation.
Data exists independently of the context we place it in but how honestly that data reflects reality is another question.
According to statistician Nate Silver, who knows a thing or two about the perils of poor data:
“Numbers have no way of speaking for themselves. We speak for them.
We can imbue them with meaning…(and) may construe them in self-serving ways that are detached from their objective reality”.
Which brings us to information…
When we take data and interpret it purposefully we get information so we can consider information as data with added meaning. Though coloured by culture and other factors, meaning is largely subjective – what has meaning for you may have little, none or be something entirely different for me.
At this point we’ve moved from objective artefacts of fact (data) to something at the mercy of the subjective – whether it’s what we seek to learn from the data or the unintended biases we bring to interpreting that data, information is not without influence.
Information comes and goes and of course not all of it translates into knowledge. For this to happen it must have a context, whether using it as the basis of a decision or as source material for an essay. This knowledge then becomes the application of information.
For centuries philosophers have tied themselves in knots debating knowledge; in fact the entire branch of philosophy called Epistemology is dedicated to just that so it’s not surprising then that knowledge and its more slippery cousin, wisdom, can prove difficult to pin down.
In our case we can think of knowledge as an understanding of information that can be applied practically. No wonder then that it’s sometimes equated with ‘know-how’.
If we take information and, after placing it in the context of our existing skills, experience and other information acquired, we can then make decisions and carry out actions based on this we can call that knowledge.
Arriving to us laden with images of elderly, bearded gentlemen, wisdom is possibly the most difficult element to define and many who have discussed the model have simply sidestepped it. In this context it’s not an absolute nor a hallowed end in itself so it’s best to dispense with our preconceptions.
Wisdom can be defined as taking the acquired knowledge – remember knowledge is the application of internalised information – and forming associations with other pieces of knowledge. When we can apply knowledge to domains other than the one that we originally acquired it then we have wisdom. So taking a knowledge of software development and seeing how some aspects could then be applied to education would be a form of wisdom.
It’s no mistake then that wisdom sits atop the hierarchy since – once we’ve shaped data with meaning and produced information that, when placed in the context of other information we have acquired, allows us to do apply it in the form of knowledge. Wisdom, then, can be viewed as the application of knowledge to other knowledge both within and beyond a particular field.