Doing stuff @ Effective Altruism Israel

Working (6-15 years of experience)

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Hey! I'm Edo, married + 2 cats, I live in Tel-Aviv, Israel, and I feel weird writing about myself so I *go meta*.

I'm a mathematician, I love solving problems and helping people. My LinkedIn profile has some more stuff.

I'm a forum moderator, which mostly means that I care about this forum and about you! So let me know if there's anything I can do to help.

I'm currently working full-time at EA Israel, doing independent research and project management. Currently mostly working on evaluating the impact of for-profit tech companies, but I have many projects and this changes rapidly.

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OMG!!!

What do you think of ACE's recent recommendations?

It brings to mind birds colliding with windows (wiki). It's estimated that more than 100 million birds die each year from colliding into a window in the US alone and there are some legislative work to address it (say, by "painting" them with patterns visible in the UV spectrum).

It might be cost-effective to promote such legislation. I haven't looked into the details at all, except for the wiki page.

(also the inner-doc links inside footnote 46 point to the doc)

Mind expending on this?

Thanks for the write up :) Quick question, when would the charities prefer getting money through you rather than directly?

Thank you! 💖

Moderator comments behave weirdly in dark mode

Plotting the estimates, we get:

This looks logarithmic. Plotting the probability over Log(Year - 2022) does look linear (although clearly it is't, as it is bounded to [0,1], so a better fit would probably be something "arctan"y):

Also, it makes sense to me that uncertainty over "time until E" would behave more like a log-normal distribution (when the probability is fixed). That is, I'd expect that a forecaster's estimate for years-until-AGI in particular probability p would itself be a lognormal distribution over the years (as I imagine the forecaster would be equally likely to be wrong by twice as many years or half as many years).

This justifies taking the geometric mean over the years (as it corresponds to an average over the log of the years), but not when looking at the probabilities.

Fitting the curve with a linear function (excluding the N/As), we get P(AGI at year y)=log(y−2022)/2−0.15

For y=2030, we'd get p=0.3

For y=2050, we'd get p=0.57

For y=2100, we'd get p=0.79

Or, for a probability p, we'd get the year y=102(p+0.15)+2022.

For p=0.1, we'd get y=2025

For p=0.5, we'd get y=2042

For p=0.9, we'd get y=2148

Overall, I got rather similar numbers 😊