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The problem with giving someone a default high score based on what they've done in the past is it devolves into a type of "appeal to authority" fallacy where de
by portLAN 19y ago
The problem with giving someone a default high score based on what they've done in the past is it devolves into a type of "appeal to authority" fallacy where deference is because of who someone is, as opposed to what someone is now saying. Trivial, offhand remarks by an authority figure are given greater weight than insightful, useful posts by an unknown. Even worse, out-and-out mistakes by the highly karmic come with an official stamp of karmic approval -- the whole system is prejudicial by design.
If your goal is to create a system that reflects people's typical judgement, then this works, because people make all sorts of logical errors. If, however, you are aiming for a meritocracy, judging each post on its own worth without regard to who said it (except when identity is actually applicable), the correct approach is to have a swarm of AIs reading everything and assigning points based on content. [1]
[1] Implementing the correct approach is left as an exercise for the reader.
- lkozma 19y agoWhat you say is true for comments, I agree that every contribution should be judged on its own merit. For filtering/ordering submissions though, such as on the reco-page on reddit, a web of trust is quite natural. Since we have limited time, we can't possibly read everything, so we might as well prefer content from people we trust. Same thing in real life, when you read the next book of your favorite author, instead of one by a complete stranger. If the scores are distributed, the authority figures aren't necessarily the same for everyone.
- portLAN 19y agoArticles should also be read and ranked based on content instead of by submitter. With books, you miss out on a lot by sticking with the same author, as there are so many other worthy books you never become aware of; people's usual habits can be improved upon.
- run4yourlives 19y agoYour issue regarding the appeal to authority is present in real life to a large degree, and not limited to websites. What you're suggesting is to remove the human altogether, and I'm not sure how AI would adjust when the average total quality reduces, which is usually the issue when a site scales.
- portLAN 19y ago> Your issue regarding the appeal to authority is present in real life to a large degree, and not limited to websites. Correct, which is why I mentioned the current situation works if you want a model that reflects typical human judgement, including bias and errors. Removing humans is just a labor-saving feature. If you don't mind spending the time, then human editors can do a good job of it, just like with peer-reviewed journals. Make the score independent of the site's userbase size: e.g. from 1 to 10. No -47s or +581s like on reddit. Comments can also be kept in a useful range, instead of something blindingly obvious getting 80 points and something controversial getting 0 (+20,-20). The key is always the editors themselves. Quality reflects the average of the editors, which is why you see a regression toward the general population's mean when everyone is imbued with editorial ability. I would be a very good editor for a few subjects and not good at all for most others; multiply that by a million and the overlap gets you the current situation with various social news sites. Pick editors randomly and you get Slashdot. Pick editors carefully and you get Science or Nature.
- Jd 19y agoVery good comment. I would give it a 9.5 if I could. ;)