In general a neural net does not have any way of knowing "why" it is doing what it is doing. This completely applies to humans too. Metacognition means we can make some decent guesses, and sometimes the "reasons" are at a metacognitive level (e.g., "having examined my three options it is only rational to select B" is a reasonable "reason") but that is the exception, not the rule.

You can get something of an intuitive sense of what I mean if I ask you to pick a neuron in your brain and tell me when it fires. You can't even pick a neuron in your brain. You can't even tell whether a broad section of your brain is firing. It is only through scientific examination that we have any idea what parts of the brain are doing what; we certainly have no direct access to that information. There are entire cultures who thought the seat of cognition was the heart or the gut. That's how bad our access to our own neural processes is.

So "why" explanations always need to be taken with a grain of salt when a neural net (again, yes, fully including humans) tries to "explain" what it is doing.

Contrast this with a symbolic reasoner, which has nothing but "why" some claim is true (if it yields the full logic train as its answer and not just "yes"/"no"), no pathway for any other form of information to emerge.