I'm not sure that quite addresses the problem here.

After all there is no clear definition of 'what dogs look like' (in the sense of a collection of logical rules), but deep learning models excel at detecting them, when provided with enough positive examples.

If it's possible for humans to agree on whether a given article is clickbait or not, we should be able to put together an adequate dataset for training a system to classify them too. From the linked article I am unable to discern how the training dataset was labelled.

In other words, the fact that 'clickbait' is a nebulous concept shouldn't preclude machine learning from being able to detect it.