[Saad_M]

I very much disagree. There are use case such as weather reporting, electronic medical report summarisation, etc. That make more sense as a textual representation than bundles of graphs and tables. In fact textual summarisation has been shown to lead to better decision making[1].

Good data-to-text NLG applications not only summarise data but they also can provides insight into causal relations of why events occurred by leveraging domain knowledge.

[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2656014/

[is_true]

I agree with you Saad. I worded that comment poorly. There are some use cases that are gonna be used to keep people reading a lot of algorithmical gibberish for no reason other than increasing revenue, for example sports articles.

I think NLG is really interesting, the problem is that there are incentives to create long form content that doesn't add any value to readers.