- Humans will bring their implicit biases to any reporting they do; I feel like it's better for the reader to make implicit biases explicit, and call out where the writer feels uncomfortable.
- If you try to cut humans out of the loop and replace them with algorithms, you're creating two problems: algorithms will have implicit biases from their creators, and there will be attempts to game and dupe the algorithms.
The problem in the US is that news outlets are expected to be biased and so they take full advantage of that to make their news more entertaining.
These news channels are driven by add revenue. And divisive, incendiary reporting is the best way to get people to keep watching.
Apart from that, you are perhaps asking for data devoid of biased analysis. You can keep up with current events like this on your own. There is plenty of public data on anything that you can analyze yourself and draw your own conclusions. Instead of reading business news, read SEC filings. Instead of reading about coronavirus, graph the raw data and make your own models. Skip the sensationalist science and health articles, and go right for the peer reviewed article. Open that layer on GIS yourself. Ignore medium blogs and read the actual documentation. Become your own data scientist.
This all takes a lot of mental effort and time, which few people have, so most people actually prefer to read summary articles from biased sources that reinforce their existing world view.