Makes me wonder if an ELO-based system would work to mitigate these issues. People who merged PR successfully onto a project, that had real issues acknowledged, the quality of their responses measured by other users reactions or something, etc, multiplied possibly by the degree of importance of the project where their activity has been made. Won't be about human vs AI, but actual helpful effective being vs low effort/spammy contributions. Issues and PRs could be sorted and filtered by their ELO score. I'm saying ELO as analogy to "score based given the context", not really a 1:1 translation of the ELO system.
Negative score would be reports from other users because of spammy content or not acknowledged issues, with a middle ground of neutral score (+-0) or little positive score to issues or whatever with clear good intention, but couldn't reach a proper merged PR or were not issues (e.g. issue existed but wasn't the correct repo to be addressed, PR was good but needed other stuff to be implemented prior to it, maybe in the long run, etc)
For those wondering what Elo means, it is a person's last name, not an acronym (not all caps). More info here:
This would just hurt new users similar to how you are unable to comment on 90% of subreddits on Reddit as a new user, because you don't have enough karma points, or how on Stackoverflow your permissions are severely limited until you do certain jobs. The incentives aren't very good in systems like this. Bots can be made to easily game the system while regular users are discouraged from even participating.
I have built something like this and in process of collecting the data.
Frontier users: 527,865 Light indexed: 527,865 Ready to queue: 9,083 Fast scores ready: 0 Activity events 24h: 30,266 Fast scores completed 24h: 19,123 Deep jobs completed 24h: 3,043 Fast-score ETA: n/a Deep-hydrate ETA: 69h Stale running jobs: 0 GitHub backpressure jobs: 19,113 High automation signals: 4,608 Medium automation signals: 1,327 Completed jobs: 74,714
Biggest challenge is Github's rate limits. At this pace it will take two more months to have 98% coverage. But after that the maintenance should be quite straight forward.
Sounds a bit like Mitchell Hashimoto’s Vouch: https://github.com/mitchellh/vouch
Some kind of vouching or scoring might make sense to help qualify contributions and many people have suggested similar recently. If by "ELO-based system" you meant "some kind of scoring system (not based on Elo)".
The Elo rating system doesn't make sense in this context; it's designed around collecting zero sum game results for a given community of players and building a model around it.
I think you need trust circles, not ELO.
The problem is you want the ELO score based on work on other community projects - you can't assume good faith here.
ELO is shockingly easy to manipulate. For example there was a literal jail with a decent chess player in it. He created a pool of players who got great ELOs by beating him, then used them to boost his rating higher. Wash, rinse, and repeat.
Given any manipulatable scheme, AI will figure out how to manipulate it. For the OP, what happens if a single AI manages to get through to contributor? Then it starts elevating other AIs to contributor, and we're off again. There doesn't have to be a purpose to this. Trolls will troll, and trolls armed with AI bots can devote endless energy to doing so. The more you work to keep them out, the more fun it becomes for them.
I wish I had an answer for that problem. But I don't.