The data model question is - at best - a very poor choice of words. Implicitly assuming a data model is a bad idea as the data model is one of the major choices every program has to contend with. So implicitly assuming it isn't really a desirable goal. It is like types where explicitly having information on types in key places in a program is always desirable and the only question is how pervasive it should be.
I also liked "They will instead ask questions about data in a natural language". Humans can't answer questions about data in natural language - when data questions come up they have to be couched in formal terms and statistics. I look forward to the day an AI can answer "what is the best decision we can make with this data?" but it runs into a problem we already have in spades. If the asker of the question isn't thinking in formal terms I question whether they are going to be able to consistently pose meaningful questions and interpret the answers. Applied Math is not easy to implement in industry because a company's ability to perform is limited by its management's understanding.
It is easy to nitpick. I'm also glad we have people thinking about the big picture of how data gets handled.
I also liked "They will instead ask questions about data in a natural language". Humans can't answer questions about data in natural language - when data questions come up they have to be couched in formal terms and statistics. I look forward to the day an AI can answer "what is the best decision we can make with this data?" but it runs into a problem we already have in spades. If the asker of the question isn't thinking in formal terms I question whether they are going to be able to consistently pose meaningful questions and interpret the answers. Applied Math is not easy to implement in industry because a company's ability to perform is limited by its management's understanding.
It is easy to nitpick. I'm also glad we have people thinking about the big picture of how data gets handled.