Beyond the Information Age discusses a new way of thinking about computers, knowledge and understanding. See the editorial for more information....

Both Knowledge and Understanding

So far the book has discussed data, knowledge, and understanding. The next step is to assemble these components into what we call an issue. An issue is a combination of both knowledge and understanding arranged in a specific way that helps us solve problems.

As humans we deal with hundreds of issues everyday and hardly even notice them. Issues come and go, as we have problems and then resolve them. Our environment presents us with these problem issues and we either resolve them or ignore them.

Let's look at the simple issue of a coin you notice lying on the ground. You notice the coin because it reflected type SE data into your eyes where you detected it and converted it to knowledge of the existence of the coin. Next your brain analyzed this knowledge in more detail to determine what kind of coin it was. Depending on its value you may decide to pick it up or ignore it. In either case the issue is resolved in moments.

The previous paragraph describes a simple issue that can be resolved in a couple of different ways. What seems so simple is actually a very complex operation that only a human or maybe a very well trained monkey could perform. Our brains are designed to resolve issues like this in a matter of seconds and then go on to resolving other issues. This chapter will introduce how knowledge is structured in an issue, and the process of resolving issues.

As you walked toward the coin you were operating your seeing and walking affectors. You're seeing affector is programmed to pick out unusual shapes in your field of vision and call them to your attention. From a child you were programmed to recognize the value of a coin, so knowledge of the coin caught your attention and became an issue for you to resolve. For this issue you are the understanding engine that understands the knowledge that comes from the data in your environment.

To resolve the issue of the coin on the ground your brain needs to access knowledge about the configuration of the coin and also the value of the coin before deciding whether you should go to the trouble of picking it up or not. Configuration and Value are two different knowledge contexts that are important to examine before making the decision. A knowledge context defines a scope or grouping of knowledge concepts. Back in the second chapter the four elements of our universe of MEST was described which included 16 data types. Each of these data types is essentially a data context that can contain an infinite number of different possible coding schemes. In the domain of knowledge there are at least ten different contexts that living systems use to organize and manage knowledge. Configuration and Value are just two of the ten knowledge contexts.

If you look down at the coin you recognize its value as only a penny, your decision may be not to pick it up. But if it were a dollar coin then its value would encourage you to pick it up. On the other hand if its configuration is that it is stuck in some tar or cement, your decision would be not to pick it up even though its value was considerable. From this example issue you can see how your brain analyzes knowledge from different contexts in order to adjust its procedures for resolving the issue. You should also note how the knowledge in one context can overrule knowledge in another when making a decision.

Last Update: 2006-Dec-23