I used AI to fix transcription errors, rerrarange the ideas, and suggest tweaks to the title and some sentences.
Three of the most exciting projects to come out of EA in recent years are, in a vague sense, CEA spinouts:
* Kairos is directly a spinout of CEA and now handles most support for university AI safety groups. Basically everyone I've found who knows them is really excited about what they do
* NEST is an opinionated ideas-fi...
This post presents the executive summary from Giving What We Can’s impact evaluation for 2025. At the end of this post we share links to more information, including the full report and...
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.