I look forward to the quasi-spam slurry of infiniscroll feed crap once growth hackers start trying to game the algorithm to get more traction for their project. I don’t think you can introduce a recommendation algorithm without it having a negative effect on the content it’s supposed to aid discovery of. Pre-recsys, the content is made for human consumption, but once you add the recsys, the AI itself becomes part of…
What exactly does "optimizing for Github recommendations" mean? I'm not writing and debugging 10,000 lines of C just to farm Github stars. It seems crazy to think anyone would change how they work for that. Whereas, people on Youtube/Twitter/Facebook/etc. really do change their videos or writing to spread better.
And neither would anybody else. That's the problem. (i.e. they'll do something else besides write and debug code to farm stars)
Let's say I determine (or at least believe) that the GitHub algorithm prefers projects with a README with lots of images and emoji, MIT-licensed, and lots of forks.
Obviously, there are already some really great projects out there that have exactly that! The problem is that now I'm incentivized to do those things as well, even if it doesn't always make sense. Sure, I might not create actual spam, but I might choose a license based on partly on that. Or I might inflate my README with an unreadable number of images. After all, my project is pretty important -- if only I could get a few more people interacting with it.
And of course, there's outright abuse. Maybe I'm desperate and build a bot that creates a bunch of forks.
The point is that it doesn't always require the latter scenario when there's also the former. Sure, it's not as bad, but I expect there to be more cases of it, and those cases are harder to determine and retroactively fix.