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...
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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...
Not sure if this is the best forum for feedback, so please direct me elsewhere and happy to delete my comment if not.
A few suggestions on the explanation of EV. While the examples are clear, I found the definition of expected value confusing.
It is written as "expected value = likelihood of option x value of option", and "The expected value is the probability multiplied by the value of each outcome".
I read this as: E[X]=xP(x), which doesn't capture the need to sum across outcomes.
Pitched at the same level of technicality, I think a clearer definition is: "The expected value of an uncertain decision is the sum across all outcomes of the value of each outcome multiplied by its probability."
Or some other wording that captures that this is a weighted average. This properly implies the necessary summation across outcomes: E[X]=∑xP(x).
It might also be worth:
Hi John, your revised version of definition helps me greatly.