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You seem to be imagining very impressive machine learning. I agree that's the right thing in the very long run. I don't understand why you say the simple versi

You seem to be imagining very impressive machine learning. I agree that's the right thing in the very long run. I don't understand why you say the simple version is "unworkable" though. Currently many forums just use a heuristic based on date and "total number of upvotes" to decide what to display. Would you describe that as unworkable?

ohyeshedid 10y ago
> Currently many forums just use a heuristic based on date and "total number of upvotes" to decide what to display. That's why these systems often fall victim to brigading by organized trolls.
- samplatt 10y ago
  I'd change "often" to "always", given enough viewers/exposure/popularity.
- paulchristiano 10y ago
  The proposed mechanism makes brigading harder (e.g. a voter is only weighted highly if they are adding useful information, such that increasing their weight improves predictive accuracy), but doesn't make it impossible. In any case, it seems extreme to call existing systems "unworkable."
  - lightedman 10y ago
    "a voter is only weighted highly if they are adding useful information" Just how do you propose one determines if the information is useful? Again, back to my original point, you'd need a system trained in EVERY FIELD. In other words, such systems are pretty much unworkable unless you're giving it full access to the entire ACCURATE knowledge of mankind. You happen to have a nice accurate database of everything man's ever accomplished and discovered for such a machine to use? Even Watson isn't even close to that level.
    - paulchristiano 10y ago
      By "useful" I mean "improves our ability to predict what the moderator would say." The mechanism for determination is just the usual approach in machine learning, set the weights to minimize prediction error. (Plus some regularization, which may incorporate a prior against new users offering useful feedback.)
lightedman 10y ago
"You seem to be imagining very impressive machine learning" It doesn't even need machine learning. I've got an image aggregator that can recommend images to me based upon what I like, why I like it, and IT LEARNS. Only a couple of times of telling it I don't like this subject matter in the picture, and it won't show me pictures with that subject matter in it. It's nothing more than a game of association and having a reliably fast database with proper tagging. "Currently many forums just use a heuristic based on date and "total number of upvotes" to decide what to display." That's not a heuristic. That's a simple if post count upvotes > x number, display here, if < this number, don't show. That's simple child's play TI-BASIC level programming.

ohyeshedid 10y ago

> Currently many forums just use a heuristic based on date and "total number of upvotes" to decide what to display. That's why these systems often fall victim to brigading by organized trolls.

samplatt 10y ago
I'd change "often" to "always", given enough viewers/exposure/popularity.
paulchristiano 10y ago
The proposed mechanism makes brigading harder (e.g. a voter is only weighted highly if they are adding useful information, such that increasing their weight improves predictive accuracy), but doesn't make it impossible. In any case, it seems extreme to call existing systems "unworkable."
- lightedman 10y ago
  "a voter is only weighted highly if they are adding useful information" Just how do you propose one determines if the information is useful? Again, back to my original point, you'd need a system trained in EVERY FIELD. In other words, such systems are pretty much unworkable unless you're giving it full access to the entire ACCURATE knowledge of mankind. You happen to have a nice accurate database of everything man's ever accomplished and discovered for such a machine to use? Even Watson isn't even close to that level.
  - paulchristiano 10y ago
    By "useful" I mean "improves our ability to predict what the moderator would say." The mechanism for determination is just the usual approach in machine learning, set the weights to minimize prediction error. (Plus some regularization, which may incorporate a prior against new users offering useful feedback.)

lightedman 10y ago

"You seem to be imagining very impressive machine learning" It doesn't even need machine learning. I've got an image aggregator that can recommend images to me based upon what I like, why I like it, and IT LEARNS. Only a couple of times of telling it I don't like this subject matter in the picture, and it won't show me pictures with that subject matter in it. It's nothing more than a game of association and having a reliably fast database with proper tagging. "Currently many forums just use a heuristic based on date and "total number of upvotes" to decide what to display." That's not a heuristic. That's a simple if post count upvotes > x number, display here, if < this number, don't show. That's simple child's play TI-BASIC level programming.