Yes, funding eg “research that also produces forecasts” seems in a completely different category to me than eg prediction markets or platform building. 

I feel the original article perhaps conflates different types of “forecast” funding a bit too much, although I tend to agree with its overall sentiment. 

Yes, exactly. My point is that people are pretty aware and claiming otherwise is a bit of a straw man type fallacy - but I might be wrong, perhaps I interact with different people :D 

I think this is essentially a straw man?
Everyone I know who doesn’t like donating to AI safety basically thinks it’s because p(influencing the outcome positively) is too low. 

Prediction markets seem to be a great business (mostly gambling with all the problems associated with it) so “funding” in the sense of investing in them could be sensible while “funding” in the donation sense not. (And then later donation to AMF or similar). 

In general, I’m hesitant to donate to stuff that’s plausibly just a really good business in its own right. 

Note that in the context of trading/investing, the two terms are often used differently. There, “mean reversion” often means negative autocorrelation of returns, which can either be ~causal or driven by price level noise (which in turn is more like a “regression to the mean” idea). If you invest in a mean reversion strategy you tend to have an actual mechanism in mind though.  

“Regression to the mean” is a less ambiguous  term and generally means what you describe. 

Thanks a lot Joey, this is definitely worth reading for people in the wider EA space, not only larger scale donors or people working in philanthropy directly. 

What I’ve found particularly helpful are the rough quantitative guidelines regarding “charity time consumed per amount donated” and “how to donate as a function of annual amount and time spent per week”. 
 
This is very valuable to better position myself from an earning-to-give perspective. 

I think it might perhaps be interesting to write a short summary of that for the forum, perhaps targeted more at a median e2g EA? (If that doesn’t exist already.)

Separately, it’s great to see that the book really embraces plurality in what areas donors prioritise without too strong a view on what’s preferable in the author’s opinion. 

Yes thanks 

boy did this age in favour of "good judgement" as a factor!

To add a small side note to this, in particular the point around the effectiveness essay: 

I suspect the EA community and in particular 80k hours tend to underestimate how hard it is to do better by being more ambitious (for the typical engaged EA, at least). Eg counterfactually increasing your income from 150k to 600k by "being more ambitious" and working longer hours or negotiating your salary more aggressiely is not a very high probability outcome. Achieving this increase by having better judgement around what area to specialise in is perhaps more likely. Likewise, taking more risk by being an entrepreneur does not 10x your career donations in expectation if you have a decent job.
I would discount the multipliers in 6 & 8 a lot (or at least their component attributable to ambition and risk taking), while I believe they are > 1.

Just to point out the obvious: encouraging some of these professionals to think more about earning to give can also be very valuable.