A question - Machine Learning

We learn commonsense. We arent born with all of it. What does commonsense tell us or makes us want to know about, when we are told about any economic activity - anything involving economics? It is the AMOUNT OF MONEY INVOLVED. How do we learn this? After being exposed to tonnes to examples of economic activities - buying ice-cream from pocket money, learning that someone signed a deal, reading that Microsoft bought Yahoo, hearing that tax rates or interest rates lowered, knowing that uncle bought a house, listening to "we paid some amount to them" etc. The key points or at least the first points of commonsensical relevance/interest here are - how much did the ice-cream cost? how much was the deal for? Microsoft bought yahoo for how much, rates lowered by how much? ....etc. So we LEARN, from repeated experience and exposure, that the most or the first relevant/important/interesting thing in anything that has to do with economics is 'HOW MUCH money is involved?' It becomes a part of our second nature to ask that upon hearing any such thing.

The question is this - can a Machine Learning model, exposed to millions of pieces of economic activities' data, learn this piece of commonsense, from them?