BLUF:
* To determine whether AI is ‘improving exponentially’, ‘hitting the wall’, or any other claim which involves a quantity or magnitude (e.g. ‘This model was a big leap/small increment’). We need a good y-axis: an interval scale of AI capability which means +1 unit always represents the same degree of ‘how much better’, in the same way +1 degree Celsius is always the same amount of ‘how much hotter’.
* Yet there is no good y-axis for AI capability. All our...
Summary
* The animal welfare movement has already seen an influx in funding and should prepare for the possibility of more.
* The EA Animal Welfare Fund is encouraging those working in animal advocacy to actively set aside time and resources now to concretely plan for scaling sustainably, and we’ll support you in doing that.
* We’re requesting advocates set concrete ambitious goals and submit plans t...
Public service announcement
1. Applications are now open for our first ever round of the Charity Entrepreneurship Incubation Program dedicated exclusively to animal welfare. Learn more about what’s different this round here and apply...
Second-best theories & Nash equilibria
A general frame I often find comes in handy while analysing systems is to look for look for equilibria, figure out the key variables sustaining it (e.g., strategic complements, balancing selection, latency or asymmetrical information in commons-tragedies), and well, that's it. Those are the leverage points to the system. If you understand them, you're in a much better position to evaluate whether some suggested changes might work, is guaranteed to fail, or suffers from a lack of imagination.
Suggestions that fail to consider the relevant system variables are often what I call "second-best theories". Though they might be locally correct, they're also blind to the broader implications or underappreciative of the full space of possibilities.
Examples