Knowledge is limited.
Knowledge deficits are unlimited.
Knowing something–all of the things you don’t know collectively is a form of knowledge.
There are many forms of knowledge–let’s think of knowledge in terms of physical weights, for now. Vague awareness is a ‘light’ form of knowledge: low weight and intensity and duration and urgency. Then specific awareness, maybe. Notions and observations, for example.
Somewhere just beyond awareness (which is vague) might be knowing (which is more concrete). Beyond ‘knowing’ might be understanding and beyond understanding using and beyond that are many of the more complex cognitive behaviors enabled by knowing and understanding: combining, revising, analyzing, evaluating, transferring, creating, and so on.
As you move left to right on this hypothetical spectrum, the ‘knowing’ becomes ‘heavier’–and is relabeled as discrete functions of increased complexity.
It’s also worth clarifying that each of these can be both causes and effects of knowledge and are traditionally thought of as cognitively independent (i.e., different) from ‘knowing.’ ‘Analyzing’ is a thinking act that can lead to or improve knowledge but we don’t consider analysis as a form of knowledge in the same way we don’t consider jogging as a form of ‘health.’ And for now, that’s fine. We can allow these distinctions.
There are many taxonomies that attempt to provide a kind of hierarchy here but I’m only interested in seeing it as a spectrum populated by different forms. What those forms are and which is ‘highest’ is less important than the fact that there are those forms and some are credibly thought of as ‘more complex’ than others. (I created the TeachThought/Heick Learning Taxonomy as a non-hierarchical taxonomy of thinking and understanding.)
What we don’t know has always been more important than what we do.
That’s subjective, of course. Or semantics–or even pedantic. But to use what we know, it’s useful to know what we don’t know. Not ‘know’ it is in the sense of possessing the knowledge because–well, if we knew it, then we’d know it and wouldn’t need to be aware that we didn’t.
Let me start over.
Knowledge is about deficits. We need to be aware of what we know and how we know that we know it. By ‘aware’ I think I mean ‘know something in form but not essence or content.’ To vaguely know.
By etching out a kind of boundary for both what you know (e.g., a quantity) and how well you know it (e.g., a quality), you not only making a knowledge acquisition to-do list for the future, but you’re also learning to better use what you already know in the present.
Put another way, you can become more familiar (but perhaps still not ‘know’) the limits of our own knowledge, and that’s a wonderful platform to begin to use what we know. Or use well.
But it also can help us to understand (know?) the limits of not just our own knowledge, but knowledge in general. We can begin by asking, ‘What is knowable?” and ‘Is there any thing that’s unknowable?” And that can prompt us to ask, ‘What do we (collectively, as a species) know now and how did we come to know it? When did we not know it and what was it like to not know it? What were the effects of not knowing and what have been the effects of our having come to know?
For an analogy, consider an automobile engine disassembled into hundreds of parts. Each of those parts is a bit of knowledge: a fact, a data point, an idea. It may even be in the form of a tiny machine of its own in the way a math formula or an ethical system are types of knowledge but also functional–useful as its own system and even more useful when combined with other knowledge bits and exponentially more useful when combined with other knowledge systems.
I’ll get back to the engine metaphor in a moment. But if we can make observations to collect knowledge bits, then form theories that are testable, then create laws based on those testable theories, we are not only creating knowledge but we are doing so by whittling away what we don’t know. Or maybe that’s a bad metaphor. We are coming to know things by not only eliminating previously unknown bits but in the process of their illumination, are then creating countless new bits and systems and potential for theories and testing and laws and so on.
When we at least become aware of what we don’t know, those gaps embed themselves in a system of knowledge. But this embedding and contextualizing and qualifying can’t occur until you’re at least aware of that system–which means understanding that relative to users of knowledge (i.e., you and I), knowledge itself is characterized by both what is known and unknown–and that the unknown is always more powerful than what is.
For now, just allow that any system of knowledge is composed of both known and unknown ‘things’–both knowledge and knowledge deficits.
An Example Of Something We Didn’t Know
Let’s make this a little more concrete. If we learn about tectonic plates, that can help us use math to predict earthquakes or design machines to predict them, for example. By theorizing and testing concepts of continental drift, we got a little bit closer to plate tectonics but we didn’t ‘know’ that. We may, as a society and species, know that the traditional sequence is that learning one thing leads us to learn other things and so might suspect that continental drift might lead to other discoveries, but while plate tectonics already ‘existed,’ we hadn’t identified these processes so to us, they didn’t ‘exist’ when in fact they had all along.
Knowledge is odd that way. Until we give a word to something–a series of characters we used to identify and communicate and document an idea–we think of it as not existing. In the 18th century, when Scottish farmer James Hutton began to make clearly reasoned scientific arguments about the earth’s terrain and the processes that form and change it, he help solidify modern geography as we know it. If you do know that the earth is billions of years old and believe it’s only 6000 years old, you won’t ‘look for’ or form theories about processes that take millions of years to occur.
So belief matters and so does language. And theories and argumentation and evidence and curiosity and sustained inquiry matter. But so does humility. Starting by asking what you don’t know reshapes ignorance into a kind of knowledge. By accounting for your own knowledge deficits and limits, you are marking them–either as unknowable, not currently knowable, or something to be learned. They stop muddying and obscuring and become a kind of self-actualizing–and clarifying–process of coming to know.
Learning leads to knowledge and knowledge leads to theories just like theories lead to knowledge. It’s all circular in such an obvious way because what we don’t know has always mattered more than what we do. Scientific knowledge is powerful: we can split the atom and make species-smothering bombs or provide energy to feed ourselves. But ethics is a kind of knowledge. Science asks, ‘What can we do?’ while humanities might ask, ‘What should we do?’
The Fluid Utility Of Knowledge
Back to the automotive engine in hundreds of parts metaphor. All of those knowledge bits (the parts) are useful but they become exponentially more useful when combined in a certain order (only one of trillions) to become a functioning engine. In that context, all of the parts are relatively useless until a system of knowledge (e.g., the combustion engine) is identified or ‘created’ and actuated and then all are critical and the combustion process as a form of knowledge is trivial.
(For now, I’m going to skip the concept of entropy but I really probably shouldn’t because that might explain everything.)
See? Knowledge is about deficits. Take that same unassembled collection of engine parts that are simply parts and not yet an engine. If one of the key parts is missing, it is not possible to create an engine. That’s fine if you know–have the knowledge–that that part is missing. But if you think you already know what you need to know, you won’t be looking for a missing part and wouldn’t even be aware a functioning engine is possible. And that, in part, is why what you don’t know is always more important than what you do.
Every thing we learn is like ticking a box: we are reducing our collective uncertainty in the smallest of degrees. There is one fewer thing unknown. One fewer unticked box.
But even that’s an illusion because all of the boxes can never be ticked, really. We tick one box and 74 take its place so this can’t be about quantity, only quality. Creating some knowledge creates exponentially more knowledge.
But clarifying knowledge deficits qualifies existing knowledge sets. To know that is to be humble and to be humble is to know what you do and don’t know and what we have in the past known and not known and what we have done with all of the things we have learned. It is to know that when we create labor-saving devices, we’re rarely saving labor but rather shifting it elsewhere.
It is to know there are few ‘big solutions’ to ‘big problems’ because those problems themselves are the result of too many intellectual, ethical, and behavioral failures to count. Reconsider the ‘discovery’ of ‘clean’ nuclear energy, for example, in light of Chernobyl, and the seeming limitless toxicity it has added to our environment. What if we replaced the spectacle of knowledge with the spectacle of doing and both short and long-term effects of that knowledge?
Learning something generally leads us to ask, ‘What do I know?’ and sometimes, ‘How do I know I know? Is there better evidence for or against what I believe I know?” And so on.
But what we often fail to ask when we learn something new is, ‘What else am I missing?’ What might we learn in four or ten years and how can that kind of anticipation change what I believe I know now? We can ask, ‘Now I that I know, what now?”
Or rather, if knowledge is a kind of light, how can I use that light while also using a vague sense of what lies just beyond the edge of that light–areas yet to be illuminated with knowing? How can I work outside in, beginning with all the things I don’t know, then moving inward toward the now clear and more humble sense of what I do?
A closely examined knowledge deficit is a staggering kind of knowledge.