When I started working on Zeitgaist [1] I immediately recognized that biased information is the main problem. I'm currently thinking about attaching additional information to the sources I present like ground [2] is doing with political spectrums. I really like your idea for the news algorithm. If you or someone elsw wants to build something like that on top of Zeitgaist with me, don't hesitate to contact me.

[1] https://zeitgaist.ai [2] https://ground.news/

Your "etc" includes some very powerful ethnic groups. Are you planning on "identifying" them?

I didn't think so.

I don't see why you can't. Throw religion in while you're at it. Even interest groups around other classes: disability, socioeconomic, etc.

You can absolutely say a newspaper (or individual columnist or editor) is pro-LGBT, pro-Israel, pro-Palestine, pro-Mormon, pro-Amish, pro-Atheist, etc. That shouldn't be controversial. Wikipedia can and does do this in a relatively neutral way.

If your classification is meant to disparage a group, then I'd see the trouble. Don't do that.

I want an up to date, well rounded view of how everyone sees the world. A system capable of getting me to see geopolitical events in other perspectives is useful, even if I ultimately choose to uphold my existing beliefs.

FWIW, I subscribe to all sorts of diverse political view subreddits and Twitter handles. Unfortunately, it's still hardly comprehensive is a lot of work to analyze and distill.

What we're really talking about here is boting any deviation from a tabula rasa appraisal of reality, then clustering that into an affiliation/quality, right?

I.e. Christians (as an averaged whole) can look at the same situation as a blank slate and have a statistically significant and consistently different perspective

As can scientists. As can maybe microbiologists and industrial chemists.

The point of the clustering isn't that the tags are pejorative, but that they're predictive metadata on any source's bias.

And often times that's currently unexposed. I see a post by echelon, but only by the content of that single post (and maybe some prior HN contact) can I reconstruct his typical perspectives.

It would probably include some institutions masquerading as representatives of ethnic groups but that isnt quite the same thing.

1. Will your cluster identification be unbiased? How do you avoid providing more fine-grained taxonomy for clusters that hit close to home for you (or this tool’s operator) and shoving the rest into as few buckets as possible (because you don’t care)? 2. What about biases shared by all news organizations, regardless of cluster?