Tim Bray writes about the inevitability of "algorithms" and what we can do about it: rather than lamenting over anything but reverse-chronological ordering we could/should/shall give users the tools necessary to build their own priorities in a feed presentation.
… the chant over there is “No algorithms on Mastodon!” This chant is wrong, and the discussion around it teaches us that we need clarity on what algorithms are, what moral weight they can carry, and whether they can be avoided.
Tim calls for software that allows users to build their own algorithms.
With the advent of the Fediverse generally and Mastodon specifically, for the first time we have a large-scale opportunity to experiment with algorithms who are written for people by people just because they’re cool, or because they produce feeds that the programmer likes for herself, or that her Dad likes, or that she notices causes her kids to be less obsessive about screen time.
So let’s stop saying “No algorithms!” because that’s just wrong, and figure out how to get nice algorithms built, ones that primarily are there to serve humanity’s best interests.
This has me thinking once again about the most effective algorithmic system I have used, Gnus's Adaptive Scoring system. When reading my mail and feeds I add only one bit of information: "was this message worth reading" and my system extracts sender and subject keywords and stores a big blob of scores for each of those, and applies them to every folder I open. After years of training my inbox and my feed reader is better than Twitter's social-focused algorithms or anything a "smart" feed reader could deliver to me, even NewsBlur's training system pales.
I refreshed my document musing about this, and I'm wondering once again how to go about reasonably doing this on a backend: