Researchers introduce ML model where learnability cannot be proved Packt Hub

In a study published in Nature Machine Intelligence, researchers discovered that in some cases of machine learning it cannot be proved whether the system actually'learned' something or solved the problem. They explore machine learning learnability. We already know that machine learning systems, and AI systems in general are black boxes. You feed the system some data, you get some output or a trained system that performs some tasks but you don't know how the system arrived at a particular solution. Now we have a published study from Ben-Davis et al that shows learnability in machine learning is undecidable.