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.
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.
