Eric Neyman

I'm a theoretical CS grad student at Columbia specializing in mechanism design. I write a blog called Unexpected Values which you can find here: My academic website can be found here:

Topic Contributions


Why Helping the Flynn Campaign is especially useful right now

Does anyone have an estimate of how many dollars donated to the campaign are about equal in value to one hour spent phonebanking? Thanks!

My bargain with the EA machine

I guess I have two reactions. First, which of the categories are you putting me in? My guess is you want to label me as a mop, but "contribute as little as they reasonably can in exchange" seems an inaccurate description of someone who's strongly considering devoting their career to an EA cause; also I really enjoy talking about the weird "new things" that come up (like idk actually trade between universes during the long reflection).

My second thought is that while your story about social gradients is a plausible one, I have a more straightforward story about who EA should accept which I like more. My story is: EA should accept/reward people in proportion to (or rather, in a monotone increasing fashion of) how much good they do.* For a group that tries to do the most good, this pretty straightforwardly incentivizes doing good! Sure, there are secondary cultural effects to consider-- but I do think they should be thought of as secondary to doing good.

*You can also reward trying to do good to the best of each's ability. I think there's a lot of merit to this approach, but might create some not-great incentives of the form "always looking like you're trying" (regardless of whether you really are trying effectively).

My bargain with the EA machine

I may have misinterpreted what exactly the concept-shaped hole was. I still think I'm right about them having been surprised, though.

My bargain with the EA machine

If it helps clarify, the community builders are talking about are some of the Berkeley(-adjacent) longtermist ones. As some sort of signal that I'm not overstating my case here, one messaged me to say that my post helped them plug a "concept-shaped hole", a la

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My bargain with the EA machine

Great comment, I think that's right.

I know that "give your other values an extremely high weight compared with impact" is an accurate description of how I behave in practice. I'm kind of tempted to bite that same bullet when it comes to my extrapolated volition -- but again, this would definitely be biting a bullet that doesn't taste very good (do I really endorse caring about the log of my impact?). I should think more about this, thanks!

My bargain with the EA machine

Yup -- that would be the limiting case of an ellipse tilted the other way!

The idea for the ellipse is that what EA values is correlated (but not perfectly) with my utility function, so (under certain modeling assumptions) the space of most likely career outcomes is an ellipse, see e.g. here.

My bargain with the EA machine

Note that the y-axis is extrapolated volition, i.e. what I endorse/strive for. Extrapolated volition can definitely change -- but I think by definition we prefer ours not to?

Best Countries during Nuclear War

Note that covid travel restrictions may be a consideration. For example, New Zealand's borders are currently closed to essentially all non-New Zealanders and are scheduled to remain closed to much of the world until July:

The best $5,800 I’ve ever donated (to pandemic prevention).

Historically, there have been ~24 Republicans vs ~19 Democrats as senators (and  1 independent) from Oregon, so partisan affiliation doesn't seem that important.

A better way of looking at this is the partisan lean of his particular district. The answer is D+7, meaning that in a neutral environment (i.e. an equal number of Democratic and Republican votes nationally), a Democrat would be expected to win this district by 7 percentage points.

This year is likely to be a Republican "wave" year, i.e. Republicans are likely to outperform Democrats (the party out of power almost always overperforms in midterm elections); however, D+7 is a substantial lean that's hard to overcome. I'd give Carrick a 75% chance of winning the general election conditional on winning the primary. His biggest challenge is winning the primary election.

Principled extremizing of aggregated forecasts

Hi! I'm an author of this paper and am happy to answer questions. Thanks to Jsevillamol for the summary!

A quick note regarding the context in which the extremization factor we suggest is "optimal": rather than taking a Bayesian view of forecast aggregation, we take a robust/"worst case" view. In brief, we consider the following setup:

(1) you choose an aggregation method.

(2) an adversary chooses an information structure (i.e. joint probability distribution over the true answer and what partial information each expert knows) to make your aggregation method do as poorly as possible in expectation (subject to the information structure satisfying the projective substitutes condition).

In this setup, the 1.73 extremization constant is optimal, i.e. maximizes worst-case performance.

That said, I think it's probably possible to do even better by using a non-linear extremization technique. Concretely, I strongly suspect that the less variance there is in experts' forecasts, the less it makes sense to extremize (because the experts have more overlap in the information they know). I would be curious to see how low a loss it's possible to get by taking into account not just the average log odds, but also the variance in the experts' log odds. Hopefully we will have formal results to this effect (together with a concrete suggestion for taking variance into account) sometime soon :)

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