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A Simple Definition of Knowledge

Attempting to define knowledge is always a source of great joy. I've tried to walk wide circles around the subject by focusing instead on describing (as compared with defining) knowledge. But descriptions can only go so far...and at a certain point, the question of "what is knowledge" becomes important to many people - particularly managers, philosophers, and people who generally have too much time available or possess a generally contentious spirit.

Laying aside common definition approaches - often mired in epistemology and ideological and even political wrangling - I define knowledge more as a function of its structure than it's inherent nature. To that end, this image reflects how I currently see knowledge:

At its simplest, information is a node which can be connected. When connected, it becomes knowledge (i.e. it possesses some type of context and is situated in relation to other elements). The combined nature of many such connections results in understanding...i.e. understanding is an emergent property of the network (I think "property" is a more accurate term than "entity" as listed in the diagram...hmm, need to change that). By way of a simple example, if I'm involved in educational psychology, possessing the names of key theorists is an example of information...see how different theorists relate to others, how they contrast, and what they each contribute, is an example of knowledge...the aggregate and depth (including strength) of these connections presents a degree of understanding of the field and related factors or concepts. At this point, we bring in our existing knowledge networks - i.e. how do educational theorists relate to other experts in different disciplines? What's the history of Russian culture and how did it influence Vygotsky? How do the ideas of Piaget relate to Darwin? Or how do Darwin's ideas relate to Ancient Greek Philosophy? Each one of these nodes (information) contributes to a connection (knowledge), of which the aggregate produces our understanding.

Seeing knowledge as connections and understanding as aggregation of connections is particularly relevant in the current climate of read/write web. The tools which enable the greatest possibility of connection forming provide the greatest possibility of knowledge growth. The tools with provide the greatest possibility of making sense of the resulting connections form the basis for understanding (which is why pattern creating or information visualization tools are valuable as our connections become more diverse and networks become more complex).


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I've put forward a simple definition of knowledge on my Knowing Knowledge blog: "At its simplest, information is a node which can be connected. When connected, it becomes knowledge (i.e. it possesses some type of context and is situated in... [Read More]

Tracked on June 7, 2007 10:39 AM

Comments (5)

Dave Sabol:

George,

What a simple, yet elegant and descriptive definition of a term / phrase / concept that has caused so much debate and confusion over the years. I particularly like the ideas of connectivity and generativity as I believe that information is the fundamental building block upon which knowledge and understanding are built.

Thanks for sharing this.

Posted by Dave Sabol | June 7, 2007 12:37 PM

Stephen Downes:

Um... no.

I don't want to be antagonistic, but this account is not satisfactory.

> information is a node which can be connected

So what, then, a neuron is information? No, that makes no sense - because then we would have the same information, unchanged, day in and day out, in our brains.

At the very least - information has to refer to a neural *state*. A nodal *state*. At its simplest, a neuron can be 'off' or 'on' (actual neurons have more complex states, of course). A given neural state might be a bit of information - a sequence of neural states or a collection of neural states 'information'.

Even then, we may want to rstrict our attention to certain states, and not all states. Taking an information-theoretic approach, for example (cf Dretske) we might want to limit our attention to neural states that are reflective of (caused by, representative of) states of affairs in the world. This is the distinction between 'signal' and 'noise'.

There's a lot more to be said here. because now we night want to say that the information isn't the actual state, but rather, it is the (description of, proposition describing, etc) state of affairs represented by the neural state. Because the actual neuron doesn't matter, does it? If we switched the current neuron out for a different one, it would still be the same infomration, wouldn't it?

> When connected, it becomes knowledge (i.e. it possesses some type of context and is situated in relation to other elements).

The traditional definition of knowledge is 'justified true belief'. There are many problems with that definition, but it does point to the fact that we think of 'knowledge' as being something broadly mental and propositional. Knowledge, in other words, is a macro phenomenon, like an entire set of connections, and not a micro phenomenon, like a single connection.

But there's also more at work here. Is knowledge the actual physical se of connections? Is it the pattern represented by the connections, that could be instantiated physically by any number of systems? Is it tantemount to the state of affairs that caused the set of connections to exist? Is the connective state representational? Referential?

Simply saying 'knowledge is a connection' answers none of these. It offers no account of the relation between the brain and the world, if any. It doesn't account for the relation between, say, 'knowledge' and 'belief'. I am sympathetic to the non-representational picture of knowledge suggested by the definition - but if knowledge is non-representational, then what is it? Saying that it's some physical thing, like a connection, is about as useful as saying that it is a brick.

> understanding is an emergent property of the network

Which means... what?

To put this bluntly: is understanding an epistemological state - that is, it it some kind of super-knowledge, perhaps context-aware knowledge? Kind of like wisdom?

Or is it a perceptual state? Is 'understanding' what it *feels* like to know?

Is *any* emergent property of a network an 'understanding'? We could imagine a digital video camera that records the 'face on Mars'. So we have some emergent property of the networks of sensors. Is this emergent property 'understanding'?

One would assume that there would be, at a minimum, some requirement of recognition. That is, it doesn't get to be 'understanding' unless it is 'recognized' as being the face of Jesus on Mars. But this means it's not just the emergent property - it's a relation between some emergent property and some perceptual system.

Additionally - there is not really a face of Jesus on Mars. It's just an illusion. Does it count as 'understanding' if it's an illusion, a mirage, or some other misperception? If not, what process distinguishes some recognitions of emergent properties from others?

I don't mean to be antagonistic here. I am sympathetic with the intent of this post. But it is so far from being an adequate account of these terms it was almost a duty, a responsibility, that I post this correction.

I understand that I owe an alternative account of these phenomena. I have attempted a beginning of such an account in my Connective Knowledge paper. But it si clear to me that I need to offer something that is both significantly clearer and significantly more detailed.


Posted by Stephen Downes | June 7, 2007 2:35 PM

George Siemens:

Hi Stephen - thanks for your comment...always appreciate a critical review.

In terms of your first criticism - i.e. relating to the neuronal aspect of information, the connecting of external information/knowledge is different from how they are represented in the brain. In my post, I was describing the external elements of forming connections...you seem more focused on the what happens with neurons…I’m more interested in how the various ideas and concepts we encounter form our understanding. In your discussion, you focus on knowledge as a particular state at a neuronal level.

“So what, then, a neuron is information?”

Don’t think I’m saying anything of this sort. If information is a node…that doesn’t mean that a neuron is information.

In your second line of reasoning, I get a clearer sense of what you are hoping to achieve in terms of a knowledge definition – i.e. the physical mind vs. world connection…as well as categorizing knowledge according to concepts of referential, representational, etc. You are bringing a philosophy orientation to the discussion – I’m bringing an application orientation. Namely, when I look at the tools I use for dialoguing online…how I learn from the connections I’ve made…and the understanding that arises from these networks, I arise at the (as stated) simple definition of knowledge. When I read blogs – Snowden’s, yours, Jay’s, or others, I’m concerned with the structural shape of that relationship. These structures – namely networks – produces my understanding. Each blog post, each idea presented, each citation provided, is a node. Knowledge forms when I connect the unique mixture of nodes that arise from my information intake (blogs, journals, books, videos, podcasts, reports). The depth and breadth of my understanding is a function of the connectedness of my network.

“but if knowledge is non-representational, then what is it? Saying that it's some physical thing, like a connection, is about as useful as saying that it is a brick.”

Again, in my definition here, I’m concerned with how my own understanding grows as I connect sources of information. Your focus appears to be on knowledge at the neuron level. I’m not concerned in this instance with what happens in how knowledge is represented/reflected/related at this level - for several reasons, primary of which is that I’m not a neuroscientist. (Lynne Redder in a recent conference mentioned a soon to be published article about the impact of appealing to neuroscience…when “neuroscience” was introduced during a discussion, the natural critical cognition of students was negatively impacted – the word was intimidating, resulting in self-doubt). So while we can have strong opinions on neural representations, we may very well end up being wrong as new research is put forward on a regular basis. I can speak with much more confidence on how I learn and how I grow in understanding in how I form my own learning networks.

“To put this bluntly: is understanding an epistemological state - that is, it it some kind of super-knowledge, perhaps context-aware knowledge? Kind of like wisdom?
Or is it a perceptual state? Is 'understanding' what it *feels* like to know?
Is *any* emergent property of a network an 'understanding'?”

Great questions. Understanding is a gradient. I can understand a little…or a lot. But whatever I’ve connected (say, with regard to Greek philosophy) is what is emergences from the sources I’ve encountered through out my life…combined with how I’ve connected it – i.e. have I processed it? Did I form a strong connection through practice, writing, debate? If not, I may have very week connections between my information sources…and my overall understanding will be quite weak. But, even on a small scale, it is still understanding.

“I don't mean to be antagonistic here. I am sympathetic with the intent of this post. But it is so far from being an adequate account of these terms it was almost a duty, a responsibility, that I post this correction.”

I don’t take it as antagonistic – it’s an opportunity to dialogue – to form connections between ideas and concepts

Posted by George Siemens | June 8, 2007 2:24 PM

Denee:

Yes, connections are knowledge, but understanding is a lot more than multiple connections.

Understanding is also about having some reality and affinity with something.

Try to say that you understand something with you don't have any affinity !

Posted by Denee | June 18, 2007 10:15 AM

Utopiah:

"connections are knowledge, but understanding is a lot more than multiple connections.

Understanding is also about having some reality and affinity with something.

Try to say that you understand something with you don't have any affinity !"

In the hypothesis of knowledge being a connection, learning could be adding connections to an existing network AFTER checking the compatibility of the new connection against the existing network (our prior knowledge). That would imply that it is much easier and efficient to learn once you understand (fully compatible new network) against brute force remembering (forcing the addition of a potentialy incompatible sub-network).

Posted by Utopiah | December 17, 2007 12:46 PM

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