I think it might be interesting and valuable to create a "list of numbers every EA should know", in a similar vein to Latency Numbers Every Programmer Should Know and Key Numbers for Cell Biologists.
I was originally thinking of either a) making the whole list myself, or b) convincing someone else (eg, an RP intern) to do it, but on AaronGertler's advice I decided to turn to the Forum to help with crowdsourcing this problem.
We can use upvotes/downvotes and comments to debate which numbers should be worth including/excluding.
So what are some key numbers that (almost) every EA should know?
Feel free to answer with either important numbers that you think are cause-specific (eg, numbers of chickens currently alive in factory farms, Toby Ord's x-risk estimates, extreme poverty rates in 1950 vs 2018) or relatively cause agnostic (eg, $billions that Open Phil has, expected lifespan of social movements, number of atoms in the observable universe).
My favorite exponential growth numbers:
1.01^20,000 = 10^86
1.03^7000 = 10^89
1.05^4000 = 10^84
If the economy were to grow by 1% annually for a mere 20,000 years (which is a blink of an eye on a geologic timescale), then the economy would grow by a factor of 10^86, which is more than the number of atoms in the observable universe.
Of course this won't happen, but when talking with people outside of EA about the question of how soon we might create AGI or how soon we might reach technological maturity or how soon we might create a civilization with more value in it each year than the value of all life that has ever lived on Earth so far, I sometimes find that peoples' intuition is that the answer to each question is a very long time, e.g. millions of years.
However, when I give these exponential growth numbers in this context it often acts as an intuition pump, such that whoever I'm talking to immediately sees that "millions of years" is too long, "thousands of years" is a lot more reasonable seeming than moments before, and "a few centuries or less" suddenly seems plausible.