Obviously, it’s easy to imagine a big increase in spam. But can you imagine if the content became reliably very good? What if every new thing you read was more interesting than any other thing you’ve ever read.
GPT-3 style language models assemble nonsense with similar statistical properties to the (hopefully) meaningful text in their training corpus, and that's it. At best, they are engines for contextually regurgitating chunks of real information, but in practice it's more like reaching for a volume from a lightly curated shelf of Borges' Total Library; self-cast shadows of information that roil and collapse into meaninglessness. The technique is fundamentally untrustworthy for any application with real stakes.
GPT-3, I think, is most dangerous when it comes to reducing the amount of propaganda a human has to write in order to be 'taken seriously.' Long essays and long articles in major publications are taken seriously, but how many people read to the end? With GPT-3 a human propagandist can get away with writing a headline and initial paragraph. The filler text - that's required to make the article 'weighty' enough to be taken seriously can be GPT-3. That's one of the initial applications I see in terms of manufacturing consent and propaganda.
It's one of hundreds of skills it has.
I think you overestimate the difficulty of exploiting our sense of novelty.