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RE: Modeling information in an information rating system

in #hivemind3 years ago

I'll never just judge content based on its rating.

I'll argue that you do this all the time. For most people, they value the diagnosis they get from a doctor more than the diagnosis they get from their hypochondriac aunt. And this generally holds true even if you "don't like what was said". Imagine the doctor tells you that the chest pain you have is a sign of a serious heart condition and not just heartburn. You might not want to believe it, but you'll likely take it seriously, because you have some reason to respect the reputation of the information source.

The only way this can be useful is if a whole community uses the same algorithm, and the ratings appear the same for every user in the community.

In my opinion, that's the opposite of useful. For example, a system that doesn't at least allow for an initial diversity of opinion wouldn't allow for a proper exploration of the solution space needed when tackling scientific questions.

On the other hand, allowing for diversity of opinion doesn't mean that consensus can't emerge on the truth of many issues. I'm simply proposing ways we can use computers to improve the process we already use, and we've seen historically that most of humanity has over time been able to reach consensus on many topics.

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I'll argue that you do this all the time.

Theoretically, yes. Your example was a good counter argument, however I don't think a simple rating from an algorithm would have the same effect as talking to a human doctor.

I have a hard time trusting a computer generated number. Maybe that could change once I start using the trust system. It definitely has potential to be revolutionary.

The ratings from a trust network don't really come from a computer, in some sense. It's just doing "provably correct" probability math on your ratings of other people and their ratings of information. So the computer can still generate wrong probabilities, if you feed it the wrong input probabilities, but to the extent that the input probabilities are correct, the output probabilities will be correct. It's similar to the situation where you use a calculator: if you feed it the right inputs, it will generate the right results, but that can be a "big if".

I have a hard time trusting a computer generated number.

Yes, and rightly so to some extent. For a system like this to be trusted, there'll need to be a lot of transparency surrounding the calculations it does. But I see those capabilities as very necessary anyways, since one of the important capabilities of a system like this will be the ability to identify when you're getting bad inputs that are skewing your results and ways to tweak your inputs to adjust its performance.