The knowledge pyramid can be used to explain why AI is different from IT. Here is how.
The fundamental difference is that AI works with knowledge, not data, and the significant differences between knowledge and data are essential. It is much more than just words.
The figure called the knowledge pyramid can help us gain perspective. Overall, we can say that AI is a knowledge-driven technology, and IT is a data-driven technology.
For example, knowledge-driven technology could be the technology behind self-driving cars. The software that controls the self-driving cars is based on advanced AI algorithms.
That AI can drive cars illustrates the potential that knowledge-based technologies has.
A way to understand the difference between AI and IT is to look at how they work with information as a Hiraki. The concept can be illustrated as a pyramid, also known as the knowledge pyramid. The pyramid shows different levels of enriched knowledge.
It shaped like a pyramid because the upper layers are based on the lower ones. Meaning, for each step you go up, more knowledge is added, and it is assumed that you master the lower layers before an upper layer can be realized.
Thus, the lowest level of the pyramid of knowledge is data, and the highest is wisdom. The definitions of the four levels are:
• Data: A collection of facts in raw or in unorganized form.
• Information: Organized and structured data that has been cleared of errors. It can, therefore, be measured, analyzed and visualized.
• Knowledge: Learning is the central component of the knowledgeable part. Here you learn on the basis of insights and understanding of data and information.
• Wisdom: The last level is wisdom. Here, Reflection is the central component, as well as being an action-oriented stage.
The key to knowledge is that you use it as a starting point for making decisions. But there is a massive difference in a decision-making process based on data or wisdom. And this makes a significant difference when you look at AI and IT as two different technologies.
If you have to make decisions based on data, then your basis is facts in unstructured form. You cannot make that decision on data as it is. You will partly need to process the data (and thus turn data into information). So you also need to have an experience base that lets you know that if you see in the data and how you can turn this into knowledge.
Take web analytics as an example. Web analysis tools provided us with data and perhaps information about users’ behaviour, but the tools do not tell us what the cause of the users’ actions was.
To know this, you need to be able to “read the data” and turn it into actionable insights. A skilled web analytics expert can do this because she knows what the information from the analyzes meant. She would know that because of her experience or education.
So data and information require experience and insights before any decisions can be made. And the findings are pointing backwards because they will always be based on historical data. Meaning that the data shows something someone did some time ago.
The top two layers of the pyramid are fundamentally different, for they relate to knowledge and wisdom. So, there is a learning of what data and information mean that is now built into the layer.
So our web analytics expert from the example can be placed in the wisdom layer. And that means that the actions at this level are pointing forward.
Wisdom is the top layer and here is a reflection element built into it. Here you deal with the problem and maybe consider alternatives.
In short, you can say that data and information describe the world as it was, so knowledge and wisdom are moving forward and orienting ourselves to what we can do now and in the future.
Therefore, one can also say is that the higher up the pyramid one gets, the more value there is.
What is important to understand with AI is that for the first time, you have a technology that is not on the data or the information level. AI is a knowledge technology.