Good points. Understanding what and how it really works will be valueble. Explaining the AI needs the knowledge of what can be done. For example, you cannot sa

Good points. Understanding what and how it really works will be valueble. Explaining the AI needs the knowledge of what can be done. For example, you cannot say AI "build systems that process the data". You need to explain AI what "kind of processing should be done". That by itself requires knowledge of what kind of processing exist and when to use which. Also, explaining to AI what should be done takes time and effort which should not be underestimated. Sometimes when I am exlaining someone which way data should be cleaned in many cases I think that it maybe faster to do it by myself and explainig to AI will most likly be a harder than to AI. So, the question about is it easier to implement by myself than explain what I need to AI is a valid and important question. Also, with data important part even without AI is to verify how well system works. Does it correctly handles differents types of data and different use cases? Just having a system that processes data but you are not sure what output can be is in most cases useleless data system. So, in any serious data systems understanding of what they can be done and how code and data systems are working are important and I think will become even more important than now. Also, someone needs to creat AI and systems around them.