All of elifland's Comments + Replies

elifland's Shortform

Appreciate the compliment. I am interested in making it a Forum post, but might want to do some more editing/cleanup or writing over next few weeks/months (it got more interest than I was expecting so seems more likely to be worth it now). Might also post as is, will think about it more soon.

elifland's Shortform

Hi Lizka, thanks for your feedback and think it touched on some of the sections that I'm most unsure about / could most use some revision which is great!

  1. [Bottlenecks] You suggest "Organizations and individuals (stakeholders) making important decisions are willing to use crowd forecasting to help inform decision making" as a crucial step in the "story" of crowd forecasting’s success (the "pathway to impact"?) --- this seems very true to me. But then you write "I doubt this is the main bottleneck right now but it may be in the future" (and don't really
... (read more)
3MichaelA3moFwiw, I expect to very often see forecasts as an input into important decisions, but also usually seem them as a somewhat/very crappy input. I just also think that, for many questions that are key to my decisions or to the decisions of stakeholders I seek to influence, most or all of the available inputs are (by themselves) somewhat/very crappy, and so often the best I can do is: 1. try to gather up a bunch of disparate crappy inputs with different weaknesses 2. try to figure out how much weight to give each 3. see how much that converges on a single coherent picture and if so what picture (See also consilience [].) (I really appreciated your draft outline and left a bunch of comments there. Just jumping in here with one small point.)
elifland's Shortform

I wrote a draft outline on bottlenecks to more impactful crowd forecasting that I decided to share in its current form rather than clean up into a post.



  1. I have some intuition that crowd forecasting could be a useful tool for important decisions like cause prioritization but feel uncertain
  2. I’m not aware of many example success stories of crowd forecasts impacting important decisions, so I define a simple framework for how crowd forecasts could be impactful:
    1. Organizations and individuals (stakeholders) making important decisions are willing to use c
... (read more)
2Aaron Gertler3moI liked this document quite a bit, and I think it would be a reasonable Forum post even without further cleanup — you could basically copy over this Shortform, minus the bit about not cleaning it up. This lets the post be tagged, be visible to more people, etc. (Though I understand if you'd rather leave it in a less-trafficked area.)

I really enjoyed your outline, thank you! I have a few questions/notes: 

  1. [Bottlenecks] You suggest "Organizations and individuals (stakeholders) making important decisions are willing to use crowd forecasting to help inform decision making" as a crucial step in the "story" of crowd forecasting’s success (the "pathway to impact"?) --- this seems very true to me. But then you write "I doubt this is the main bottleneck right now but it may be in the future" (and don't really return to this). 
    1.  Could you explain your reasoning here? My intuit
... (read more)
Towards a Weaker Longtermism

A third perspective roughly justifies the current position; we should discount the future at the rate current humans think is appropriate, but also separately place significant value on having a positive long term future.


I feel that EA shouldn't spend all or nearly all of its resources on the far future, but I'm uncomfortable with incorporating a moral discount rate for future humans as part of "regular longtermism" since it's very intuitive to me that future lives should matter the same amount as present ones.

I prefer objections from the epistemic c... (read more)

3evelynciara4moYeah. I have this idea that the EA movement should start with short-term interventions and work our way to interventions that operate over longer and longer timescales, as we get more comfortable understanding their long-term effects.
Incentivizing forecasting via social media

Overall I like this idea, appreciate the expansiveness of the considerations discussed in the post, and would excited to hear takes from people working at social media companies.

Thoughts on the post directly

Broadly, we envision i) automatically suggesting questions of likely interest to the user—e.g., questions related to the user’s current post or trending topics—and ii) rewarding users with higher than average forecasting accuracy with increased visibility

I think some version of some type of boosting visibility based on forecasting accuracy seems promisi... (read more)

2David_Althaus1yThanks, great points! Yeah, me too. For what it's worth, Forecast mentions our post here []. Yeah, as we discuss in this section [] , forecasting accuracy is surely not the most important thing. If it were up to me, I'd focus on spreading (sophisticated) content on, say, effective altruism, AI safety, and so on. Of course, most people would never agree with this. In contrast, forecasting is perhaps something almost everyone can get behind and is also objectively measurable. I agree that the concerns you list under (b) need to be addressed.
Incentivizing forecasting via social media

The forecasting accuracy of Forecast’s users was also fairly good: “Forecast's midpoint brier score [...] across all closed Forecasts over the past few months is 0.204, compared to Good Judgement's published result of 0.227 for prediction markets.”

For what it's worth , as noted in Nuño's comment this comparison holds little weight when the questions aren't the same or on the same time scales; I'd take it as fairly weak evidence from my prior that real-money prediction markets are much more accurate.

Elicit Prediction (
... (read more)
2David_Althaus1yRight, definitely, I forgot to add this. I wasn't trying to say that Forecast is more accurate than real-money prediction markets (or other forecasting platforms for that matter) but rather that Forecasts' forecasting accuracy is at least clearly above the this-is-silly level.
Delegate a forecast

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 t... (read more)

Delegate a forecast

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. Du... (read more)

I'm Linch Zhang, an amateur COVID-19 forecaster and generalist EA. AMA

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?
3Linch1yI’m not very good at strategy games, so hopefully not much! The less quippy answer is that strategy games are probably good training grounds for deliberate practice and quick optimization loops, so that likely counts for something (see my answer to Nuno about games [] ). There are also more prosaic channels, like general cognitive ability and willingness to spend time in front of a computer. I’m guessing that knowing how to do deliberate practice and getting good at a specific type of optimization is somewhat generalizable, and it's good to do that in something you like (though getting good at things you dislike is also plausibly quite useful). I think specific training usually trumps general training, so I very much doubt playing strategy games is the most efficient way to get better at forecasting, unless maybe you’re trying to forecast results of strategy games [].
Problem areas beyond 80,000 Hours' current priorities

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%

7Stefan_Schubert1yYes, though it's possible that some or all of the ideas and values of effective altruism could live on under other names or in other forms even if the name "effective altruism" ceased to be used much.
elifland's Shortform

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 ... (read more)

2Khorton1yChallenge trials face resistance for very valid historical reasons - this podcast has a good summary. []
How should longtermists think about eating meat?

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 n... (read more)

Why not give 90%?
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 s... (read more)

3HaydenW2yYep, I agree that that's probably more likely. I focused on giving up completely to keep things simple. But if it's even somewhat likely (say, 1% p.a.), that may make a far bigger dent in your expected lifelong donations than do risks of giving up partially. That certainly sounds sensible to me!