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Covid 2/11: As Expected

The scoring system incentivizes predicting your true credence, (gory details here).

I think Metaculus rewarding participation is one of the reasons it has participation. Metaculus can discriminate good predictors from bad predictors because it has their track record (I agree this is not the same as discriminating good/bad predictions). This info is incorporated in the Metaculus prediction, which is hidden by default, but you can unlock with on-site fake currency.

Covid 2/11: As Expected

You could also check their track record. It has a calibration curve and much more.

Why it feels like everything is a trade-off

This feels related to Policy Debates Should Not Appear One-Sided: anything that's obvious does not even enter into consideration, so you only have difficult choices to make.

Intellectual Dark Matter

Don't you mean that it will damage the institutions built on intellectual dark matter? Did I miss something?

Complexity Penalties in Statistical Learning

This was interesting. I think I missed an assumption somewhere, because for , it seems that the penalty is , which seems very low for a -degree polynomial fitted on points.

Less Competition, More Meritocracy?

I almost gave up halfway through, for much the same reasons, but this somehow felt important, the way some sequences/codex posts felt important at the time, so I powered through. I definitely will need a second pass on some of the large inferential steps, but overall this felt long-term valuable.

Playing Politics

I find this kind of post very valuable, thank you for writing it so well.

I see someone who seems to see part of the world the same way I do, and I go “can we talk? can we be buds? can we be twinsies? are we on the same team?” and then I realize “oh, no, outside of this tiny little area, they…really don’t agree with me at all. Dammit.”

That rang very close to home, choked me up a little bit. But the good sad, where you put clean socks on and go make the world less terrible.

Explore/Exploit for Conversations

I'd never thought about it clearly, so thanks for this model.

A behavior I've observed (and participated in) that you don't mention: the group can temporarily splinter. Picture 6 people. Someone explores topic A. Two other people like the new topic. The other 3 listen politely for 1-2 minutes. One of the three bored people explores topic B, addressing a bored neighbor (identified by their silence). The third bored person latches on to them. Then both conversations evolve until one dies down or a leader forcibly merges the two.

(By forcibly merge, I mean: while participating in conversation A, listen to conversation B, wait for a simultaneous pause in both, then respond conspicuously to conversation B, dragging most conversation A participants with you. I have observed myself doing this.) (Single participants can also switch freely.) (I have observed this to work with close friends and relative strangers, but obviously strangers need leaders/confident people to start new conversations, because they have to be in explore mode.)

I think this lowers the exploration barrier, compared to your model.

Decision Theory

Content feedback : the inferential distance between Löb's theorem and spurious counterfactuals seems larger than that of the other points. Maybe that's because I haven't internalised the theorem, not being a logician and all.

Unnecessary nitpick: the gears in the robot's brain would turn just fine as drawn: since the outer gears are both turning anticlockwise, the inner gear would just turn clockwise. (I think my inner engineer is showing)

Kalman Filter for Bayesians

Very neat tool, thanks for the conciseness of the explanation. Though I hope I won't have to measure 70° temperatures by hand any time soon. (I know, I know, it's in Fahrenheit, but it still sounds... dissonant ? to my european ears)

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