It is said that GPT-3's parameter space is enough to encode/memorize nearly 1/3rd of it's training corpus[0] as pointed out by 'GIFtheory in another GPT-3 thread here on HN. It seems you're finding the effects of that.
Additionally I'm curious about the recursive effect of this over-fitting after more and more output from GPT-n is published on the internet and inevitably gets included in the training corpus for GPT-(n+m) as pointed out by 'jobigoud[1]. Especially as people start using GPT-like models to spam the internet. We may lack a ground-truth corpus in the future to label "human".
It would be a bit like how carbon dating or production of low background steel changed after 1945 due to nuclear testing.