LessWrong 2.0 Reader

Agreed -- conditional on the EMH holding, I think the most likely explanation is that you're taking on risk you're not aware of. If this is indeed the case, I'd expect a traditional financial advisor to be able to pick up on it very quickly, and so I'm curious what such a person has to say.

If that's not the case, my guess is that the quants on wall street are bogged down in some kind of inflexible process that prevents them from targeting the opportunities you're going for. That feels like a stretch, though. Or maybe it's some kind of knowledge that's illegible to a trading bot?

Personally, this is still an update in the direction of "I should be browsing obscure financial subreddits"

I think you're interpreting me correctly.  

Most internet forums are pretty pure democracies. If you can get an account, you can upvote/downvote as much as anyone else and each post you make is graded in a vacuum. I'm proposing an alternative that does not treat all participants equally.

Accurate predictions give you more karma and that karma means your posts/comments/upvotes/downvotes rank higher and have more influence than people who have not built up "accuracy karma"

I actually didn't realize that is how karma works here.  Thanks.  I think the critique would be that, as I understand it, we would be rewarding popularity rather than accuracy with this model.

I agree with all that.

My question is why isn't it already being done?  

Why don't the media make pundits and politicians go on record and challenge or ignore them when they get things wrong? One theory might be they aren't interested in informing as much as getting ratings and accuracy isn't a big part of that. Another more conspiracy minded theory might be that they are interesting in driving a certain narrative.

It's even more interesting to think about why companies don't use prediction markets. Seems like a company would be more profitable if they had the best predictors....so why aren't they doing more to attract them?  Robin Hanson has, what I think, are some great thoughts on this.

Again, agree with everything you've said in this post, but I don't feel we have a great theory on why people don't take forecasting more seriously and until we do are unlikely to increase their use.

I would worry in a lot of these cases that there's some risk that your model isn't taking account of, so you could be "picking up pennies in front of a steamroller". Not in all cases though - 70-200% isn't pennies.

But things like supposedly equivalent assets that used to be closely priced now diverging seems highly suspicious.

It seems to me this is getting into Social Safety Net territory. Elliott is cautious because he really has fewer resources. Would the group benefit if he's given more so he isn't running so close to the edge?

Maybe provide an example of a prisoner's dilemma with Clippy, and a stag hunt with Clippy, to distinguish those cases from 'games with other humans whose values aren't awful by my lights'? This could also better clarify for the reader what the actual content of the games is.

See The True Prisoner's Dilemma [LW · GW]. Suppose I'm negotiating with Hitler, and my possible payoffs look like:

• I cooperate, Hitler cooperates: 5 million people die.
• I cooperate, Hitler defects: 50 million people die.
• I defect, Hitler cooperates: 0 people die.
• I defect, Hitler defects: 8 million people die.

Obviously in this case the defect-defect equilibrium isn't optimal; if there's a way to get a better outcome, go for it. But equally obviously, cooperating isn't prosocial; the cooperate-cooperate equilibrium is far from ideal, and hitting 'cooperate' unconditionally is the worst of all possible strategies.

This confirms my experience so far. I tried to read Naive Set Theory, but after like 3 chapters I realized that the author already expects me to know how proofs work. I used the book How to prove it by Daniel J. Velleman to learn how to write proofs. I cannot say whether this is the best book out there, but it is definitely useful for self-study. It has a lot of exercise problems after every section and solutions for 30-50% of them. I went through roughly half of the book. I am currently taking linear algebra and real analysis in university and I feel more comfortable about the class so far because I learned how to write proofs first.

We do have something very loosely like this here. Unlike on Reddit, getting more karma on LW gives your own posts more starting karma, and also ups the amount of Karma you're able to add/remove from posts. Being able to write well-received posts gives you more of an ability to highlight or bury other people's posts.

It would be neat if there was a forecasting equivalent to Facebook. One unified identity associated with various prediction markets. Perhaps with lots of tools to create specialized forecasts. You could imagine that there was an official "City of New York" forecasting page, in which the government could post questions that citizens could make forecast about the effect of bills, conditional on them passing or not passing.

Other websites could tie into... let's call it "Castbook"... and gauge the amount of influence that accounts received on their site based on their track record on Castbook. Castbook could be a professional-esque website like LinkedIn, so that employers would consider who to hire based on their track record.

At its highest growth potential, I imagine that this would be sort of like a "light side" version of China's reputation tracking system. It would be voluntary, and be about making forecasts rather than judging people. But it would allow this tremendous resource of people considering outcomes to be distilled, preserved, and used not only to make decisions, but also as a complement or alternative to our present credentialing system.