Given that the choice of which articles to write is incredibly biased to begin with this approach does not seem effective.
What could theoretically work is an “AI news agency” that “summarizes” many different sources to generate unbiased articles.
Selection bias is a given. You always have to keep that in mind. But when you actually want to read a specific article, summarizers are useful. For news and general population content, debullshitifiers could come in handy too.
Point being, the texts are not random. There's some nugget of valuable content in it, but it's usually wrapped by enormous layer of SEO, ad hooks, word count padding, and/or general nonsense. Reducing signal-to-noise ratio here - stripping all those layers of bullshit - is strictly useful.
“Debullshitification” reads as de-biasing which is not what you just itemized.
My point is rather that Fox News+LLM (as an example) is still biased but would appear/may be incorrectly presented as unbiased to a reader not acutely aware of selection bias which is probably not something an average reader is well informed about.
And honestly, I immediately knew what that meant when I read it. My preferred news source, which isn’t horrendously partisan, still has…exactly what I’d call bullshit. If that’s removed, I’ll get more bang for my buck in reading it, and that both provides immense value, and something that I’d call “debullshitification”, whilst working purely from the articles provided.
> verb: bullshit; 3rd person present: bullshits; past tense: bullshitted; past participle: bullshitted; gerund or present participle: bullshitting
> talk nonsense to (someone), typically to be misleading or deceptive.
It’s reasonable to interpret debullshitification as removing bias (i.e. what is misleading or deceptive in the news article) in this context rather than the “fluff” listed.
As I stated in the comment you replied to, GP has a different definition and I agreed removing fluff definitely has value.
NewsMinimalist does this, it’s quite interesting. I’ve been using it since its introduction, and its been a fun way to get lots of summarized, de-sensationalized headlines. Specifically I enjoy setting it to 6.0 and reading the headlines that have impact that didn’t quite reach the 6.5+ threshold.
