elifland's Shortform 2020-06-16T17:19:07.352Z · score: 2 (1 votes)


Comment by elifland on Delegate a forecast · 2020-07-29T19:00:20.959Z · score: 3 (3 votes) · EA · GW

My forecast is pretty heavily based on the GoodJudgment article How to Become a Superforecaster. According to it they identify Superforecasters each autumn and require forecasters to have made 100 forecasts (I assume 100 resolved), so now might actually be the worst time to start forecasting. It looks like if you started predicting now the 100th question wouldn't close until the end of 2020. Therefore it seems very unlikely you'd be able to become a Superforecaster in this autumn's batch.

[Note: alexrjl clarified over PM that I should treat this as "Given that I make a decision in July 2020 to try to become a Superforecaster" and not assume he would persist for the whole 2 years.]

This left most of my probability mass given you becoming a Superforecaster eventually on you making the 2021 batch, which requires you to both stick with it for over a year and perform well enough to become a Superforecaster. If I were to spend more time on this I would refine my estimates of how likely each of those are.

I assumed if you didn't make the 2021 batch you'd probably call it quits before the 2022 batch or not be outperforming the GJO crowd by enough to make it, and even if you didn't you made that batch you might not officially become a Superforecaster before 2023.

Overall I ended up with a 36% chance of you becoming a Superforecaster in the next 2 years. I'm curious to hear if your own estimate would be significantly different.

Comment by elifland on Delegate a forecast · 2020-07-29T18:15:35.621Z · score: 2 (2 votes) · EA · GW

Here's my forecast. The past is the best predictor of the future, so I looked at past monthly data as the base rate.

I first tried to tease out whether there was a correlation in which months had more activity between 2020 and 2019. It seemed there was a weak negative correlation, so I figured my base rate should be just based on the past few months of data.

In addition to the past few months of data, I considered that part of the catalyst for record-setting July activity might be Aaron's "Why you should put on the EA Forum" EAGx talk. Due to this possibility, I gave August a 65% chance of hitting over the base rate of 105 >=10 karma posts.

My numerical analysis is in this sheet.

Comment by elifland on I'm Linch Zhang, an amateur COVID-19 forecaster and generalist EA. AMA · 2020-07-02T00:53:49.926Z · score: 5 (4 votes) · EA · GW

I've recently gotten into forecasting and have also been a strategy game addict enthusiast at several points in my life. I'm curious about your thoughts on the links between the two:

  • How correlated is skill at forecasting and strategy games?
  • Does playing strategy games make you better at forecasting?
Comment by elifland on Problem areas beyond 80,000 Hours' current priorities · 2020-06-27T21:45:13.572Z · score: 14 (7 votes) · EA · GW

Relevant Metaculus question about whether the impact of the Effective Altruism movement will still be picked up by Google Trends in 2030 (specifically, whether it will have at least .2 times the total interest from 2017) has a community prediction of 70%

Comment by elifland on elifland's Shortform · 2020-06-16T17:19:07.594Z · score: 18 (9 votes) · EA · GW

The efforts by to use human challenge trials to speed up vaccine development make me think about the potential of advocacy for "human challenge" type experiments in other domains where consequentialists might conclude there hasn't been enough "ethically questionable" randomized experimentation on humans. 2 examples come to mind:

My impression of the nutrition field is that it's very hard to get causal evidence because people won't change their diet at random for an experiment.

Why We Sleep has been a very influential book, but the sleep science research it draws upon is usually observational and/or relies on short time-spans. Alexey Guzey's critique and self-experiment have both cast doubt on its conclusions to some extent.

Getting 1,000 people to sign up and randomly contracting 500 of them to do X for a year, where X is something like being vegan or sleeping for 6.5 hours per day, could be valuable.

Comment by elifland on How should longtermists think about eating meat? · 2020-05-18T12:26:30.657Z · score: 19 (8 votes) · EA · GW

I think we have good reason to believe veg*ns will underestimate the cost of not-eating-meat for others due to selection effects. People who it's easier for are more likely to both go veg*n and stick with it. Veg*ns generally underestimating the cost and non-veg*ns generally overestimating the cost can both be true.

The cost has been low for me, but the cost varies significantly based on factors such as culture, age, and food preferences. I think that in the vast majority of cases the benefits will still outweigh the costs and most would agree with a non-speciesist lens, but I fear down-playing the costs too much will discourage people who try to go veg*n and do find it costly. Luckily, this is becoming less of an issue as plant-based substitutes are becoming more widely available.

Comment by elifland on Why not give 90%? · 2020-03-23T21:00:20.005Z · score: 4 (3 votes) · EA · GW
If I was donating 90% every year, I think my probability of giving up permanently would be even higher than 50% each year. If I had zero time and money left to enjoy myself, my future self would almost certainly get demotivated and give up on this whole thing. Maybe I’d come back and donate a bit less but, for simplicity, let’s just assume that if Agape gives up, she stays given up.

The assumption that if she gives up, she is most likely to give up on donating completely seems not obvious to me. I would think that it's more likely she scales back to a lower level, which would change the conclusion. It would be helpful to have data to determine which of these intuitions are correct.

Perhaps we should be encouraging a strategy where people increase their percentage donated by a few percentage points per year until they find the highest sustainable level for them. Combined with a community norm of acceptance for reductions in amounts donated, people could determine their highest sustainable donation level while lowering risk of stopping donations entirely.