I like this idea. Here is some brainstorming output. Apologies for it being unedited/not sorted by categories:
Age of the universe
Age of the Earth
Age of homo sapiens
Timing of major transitions in evolution
Timing of invention of writing, agriculture, and the Industrial Revolution
Gross world product
Time for which Earth remains habitable absent big intervention
Number of working days in a year
Number of working hours in a year
Net present value of expected lifetime earnings of some reference class such as “graduate from roughly such-and-such uni and discipline”
Good Ventures’s total assets
Net present value of expected total EA-aligned capital by cause area/worldview
Number of parameters, training wall clock time, compute requirements, etc. for GPT-3 and some other landmark AI models
World population, population of China, population of India, population of Europe/the US, etc. - and predictions for these
Some key numbers about the human brain, e.g. number of synapses, energy requirements, …
Expected number of lives saved by smallpox eradication
Volume of yearly Open Phil grants by cause area
Volume of donations moved by/to GiveWell and ACE top charities
Number of people working on certain cause areas such as AI safety, GCBR reduction, nuclear security, …
The ‘Kaldor facts’
The ‘Great Decoupling’ of labor productivity from jobs + wages in the US
Some key stats about the distribution of world income and how it has changed, e.g., Milanovic’s “elephant graph” and follow-ups
Some key stats about, e.g., South Korean economic growth since 1950
Something about speed of improvement in various technologies, e.g., Moore’s Law, how quickly the price of solar panels or various chemicals has fallen, etc. - weighted toward things that seem more ‘relevant’, e.g., falling price of various biotech services
Number of wild animals (by appropriate groups, e.g., mammals, birds, invertebrates)
Number of bacteria
Number of atoms in the observable universe
USG budget
Chinese govt budget
Big tech market capitalization
Total budget of some key international institutions, e.g., UN, WHO, BWC, OPCW
World energy use
Certain physics-based limits to growth, and when we’d reach them on a business-as-usual trajectory
How much total compute there is, and how it’s distributed (e.g. supercomputers vs. gaming consoles vs. personal computers vs. …)
How much EAs should discount future financial resources
Size of the EA community
Number of impact-weighted career plan changes caused by 80k every year
Some key stats about impact distributions where we have them, e.g., on how heavy-tailed the DCP2 global health cost-effectiveness numbers are
How much does it cost to cause the equivalent of one life saved by donating to the top-rated GiveWell charity?
What ‘trade ratio’ between doubling someone’s consumption and averting the death of a <5 year old do you need to have such that GiveDirectly becomes as cost-effective as AMF according to GiveWell’s cost-effectiveness model?
How many years of, e.g., chicken suffering do you avert with marginal donations to, e.g., ACE top charities?
How many years of, e.g., chicken suffering do you avert by going vegan?
How many people, and what share of the world or regional population were killed in certain historical catastrophes such as the Black Death, the Mongol conquests, the Great Leap Forward, or the transatlantic slave trade?
This is amazing. I’d be happy to create an Anki deck for these and any other numbers suggested in this thread.
EDIT: Judging from the upvotes, there seems to be considerable interest in this. I will wait a few days until people stop posting answers and will then begin creating the deck. I’ll probably use the CrowdAnki extension to allow for collaboration and updating; see the ultimate-geography GitHub repository for an example.
I would also definitely use it, just one suggestion: It would be cool if you include a field with the source link for the number so it is easy to go back and take a look. I know it will be quite some work so thanks a ton!
I’d love to use this Anki deck too! Would it make sense to add a google form or some other way to let people express an interest in this, for when you’ve made it? (and/or to express interest in contributing)
I think that’d be great. I suspect you or somebody else ought to have a strong editorial line, because otherwise we’d have too many flashcards + it’d look too much like design by committee.
I’m afraid I don’t know of great sources for the numbers you list. They may also only exist for the distribution of compute. Perhaps the numbers on the EA community are too uncertain and dynamic to be a good fit for Anki anyway. On the other hand, it may be mainly the order of magnitude that is interesting, and it should be possible to get this right using crude proxies.
One proxy for the size of the EA community could be the number of EA survey respondents (or perhaps one above a certain engagement level).
On the other points:
For the Great Decoupling you could use “total growth of US labor productivity since 1980” together with “total growth of median household income since 1980″ (or both up to some recent year for which data is available). And the same for labor productivity vs. number of jobs since 2000. See, for instance, the graph here. You could also use the graph itself as an answer.
For changes in the distribution of world income, you could just use the two graphs in this article as answers (the ‘elephant graph’ is the one for 1988-2008, and there is also a newer one for 2008-2013/14). You could also extract some key numbers from these graphs, or some other statistics. E.g., the article provides the change of the Gini coefficient of the world income distribution, but this may have the downside that it’s hard to interpret:
As measured by the Gini coefficient, which ranges from zero (a hypothetical situation in which every person has the same income) to one (a hypothetical situation in which one person receives all income), global inequality fell from 0.70 in 1988 to 0.67 in 2008 and then further to 0.62 in 2013. There has probably never been an individual country with a Gini coefficient as high as 0.70, while a Gini coefficient of around 0.62 is akin to the inequality levels that are found today in Honduras, Namibia, and South Africa. (Loosely speaking, South Africa represents the best proxy for the inequality of the entire world.)
For the heavy-tailedness of various distributions I’d use the share of, e.g., the top 10% and 1% in the total.
Thanks! It hadn’t occurred to me to use the graph as the figure, but that’s a good idea. On reflection, we could perhaps use “image occlusion” for this or other questions.
I like this idea. Here is some brainstorming output. Apologies for it being unedited/not sorted by categories:
Age of the universe
Age of the Earth
Age of homo sapiens
Timing of major transitions in evolution
Timing of invention of writing, agriculture, and the Industrial Revolution
Gross world product
Time for which Earth remains habitable absent big intervention
Number of working days in a year
Number of working hours in a year
Net present value of expected lifetime earnings of some reference class such as “graduate from roughly such-and-such uni and discipline”
Good Ventures’s total assets
Net present value of expected total EA-aligned capital by cause area/worldview
Number of parameters, training wall clock time, compute requirements, etc. for GPT-3 and some other landmark AI models
World population, population of China, population of India, population of Europe/the US, etc. - and predictions for these
Some key numbers about the human brain, e.g. number of synapses, energy requirements, …
Expected number of lives saved by smallpox eradication
Volume of yearly Open Phil grants by cause area
Volume of donations moved by/to GiveWell and ACE top charities
Number of people working on certain cause areas such as AI safety, GCBR reduction, nuclear security, …
The ‘Kaldor facts’
The ‘Great Decoupling’ of labor productivity from jobs + wages in the US
Some key stats about the distribution of world income and how it has changed, e.g., Milanovic’s “elephant graph” and follow-ups
Some key stats about, e.g., South Korean economic growth since 1950
Something about speed of improvement in various technologies, e.g., Moore’s Law, how quickly the price of solar panels or various chemicals has fallen, etc. - weighted toward things that seem more ‘relevant’, e.g., falling price of various biotech services
Number of wild animals (by appropriate groups, e.g., mammals, birds, invertebrates)
Number of bacteria
Number of atoms in the observable universe
USG budget
Chinese govt budget
Big tech market capitalization
Total budget of some key international institutions, e.g., UN, WHO, BWC, OPCW
World energy use
Certain physics-based limits to growth, and when we’d reach them on a business-as-usual trajectory
How much total compute there is, and how it’s distributed (e.g. supercomputers vs. gaming consoles vs. personal computers vs. …)
How much EAs should discount future financial resources
Size of the EA community
Number of impact-weighted career plan changes caused by 80k every year
Some key stats about impact distributions where we have them, e.g., on how heavy-tailed the DCP2 global health cost-effectiveness numbers are
How much does it cost to cause the equivalent of one life saved by donating to the top-rated GiveWell charity?
What ‘trade ratio’ between doubling someone’s consumption and averting the death of a <5 year old do you need to have such that GiveDirectly becomes as cost-effective as AMF according to GiveWell’s cost-effectiveness model?
How many years of, e.g., chicken suffering do you avert with marginal donations to, e.g., ACE top charities?
How many years of, e.g., chicken suffering do you avert by going vegan?
How many people, and what share of the world or regional population were killed in certain historical catastrophes such as the Black Death, the Mongol conquests, the Great Leap Forward, or the transatlantic slave trade?
FINAL UPDATE: The deck is now published.
This is amazing. I’d be happy to create an Anki deck for these and any other numbers suggested in this thread.
EDIT: Judging from the upvotes, there seems to be considerable interest in this. I will wait a few days until people stop posting answers and will then begin creating the deck. I’ll probably use the CrowdAnki extension to allow for collaboration and updating; see the ultimate-geography GitHub repository for an example.
You can embed flashcard decks into LW and EA Forum posts:
https://www.lesswrong.com/posts/yK8mKmMQ73TuzgCv6/you-can-now-embed-flashcard-quizzes-in-your-lesswrong-posts
So you could consider creating one of those.
Wow, I didn’t know about this feature.
I will absolutely study that deck.
I’d love to use such an Anki deck!
I would also definitely use it, just one suggestion: It would be cool if you include a field with the source link for the number so it is easy to go back and take a look. I know it will be quite some work so thanks a ton!
Hi, yes, we will have a ‘source’ field.
I say ‘we’ because I’m doing this in collaboration with a user who kindly volunteered to help. I think we should be done by the end of the week.
I’d also use such a deck. Thanks for the offer! :)
Thanks so much! I’d also use that deck.
I’d also love this – it’s been on my todo list for about 5 years 😅
I’d love to use this Anki deck too! Would it make sense to add a google form or some other way to let people express an interest in this, for when you’ve made it? (and/or to express interest in contributing)
I was thinking of announcing it in a separate post, given how much interest this has attracted.
I think that’d be great. I suspect you or somebody else ought to have a strong editorial line, because otherwise we’d have too many flashcards + it’d look too much like design by committee.
Made a save all based on the Anki deck, thank you! Probably janky/includes errors but had to start somewhere.
We’ve now turned most of these into Anki cards, but I’d appreciate pointers to reliable sources or estimates for the following:
Net present value of expected total EA-aligned capital by cause area/worldview
Number of people working on certain cause areas such as AI safety, GCBR reduction, nuclear security, …
How much total compute there is, and how it’s distributed (e.g. supercomputers vs. gaming consoles vs. personal computers vs. …)
How much EAs should discount future financial resources
Size of the EA community
For others, I have the relevant information (or know where to find it), but am not sure what numbers should be used to express it:
The ‘Great Decoupling’ of labor productivity from jobs + wages in the US
Some key stats about the distribution of world income and how it has changed, e.g., Milanovic’s “elephant graph” and follow-ups
Some key stats about impact distributions where we have them, e.g., on how heavy-tailed the DCP2 global health cost-effectiveness numbers are
(This is addressed to anyone in a position to help, not just to Max. Thanks.)
I’m afraid I don’t know of great sources for the numbers you list. They may also only exist for the distribution of compute. Perhaps the numbers on the EA community are too uncertain and dynamic to be a good fit for Anki anyway. On the other hand, it may be mainly the order of magnitude that is interesting, and it should be possible to get this right using crude proxies.
One proxy for the size of the EA community could be the number of EA survey respondents (or perhaps one above a certain engagement level).
On the other points:
For the Great Decoupling you could use “total growth of US labor productivity since 1980” together with “total growth of median household income since 1980″ (or both up to some recent year for which data is available). And the same for labor productivity vs. number of jobs since 2000. See, for instance, the graph here. You could also use the graph itself as an answer.
For changes in the distribution of world income, you could just use the two graphs in this article as answers (the ‘elephant graph’ is the one for 1988-2008, and there is also a newer one for 2008-2013/14). You could also extract some key numbers from these graphs, or some other statistics. E.g., the article provides the change of the Gini coefficient of the world income distribution, but this may have the downside that it’s hard to interpret:
For the heavy-tailedness of various distributions I’d use the share of, e.g., the top 10% and 1% in the total.
Thanks! It hadn’t occurred to me to use the graph as the figure, but that’s a good idea. On reflection, we could perhaps use “image occlusion” for this or other questions.
Amazing, thank you so much!