They are so commonly called fellowships that calling them something else in this post would complicate the message.
I haven't changed my mind, and probably somebody should write a post about why we shouldn't call them that so we can discuss this further. This unfortunately is not currently high on my priority list, but I may do it at some point.
I've always thought the name "fellowship" was misleading. But that seems like an argument to change the name, not really to pay people.
You do lay out some plausible arguments for how paying fellows could be good. As Michael mentions in another thread, Penn EA paid their fellows last term. I think the most useful evidence for or against this idea would be a writeup from them about how well it worked and what kind of people it attracted.
Also, this is definitely the kind of thing that you should preclear with funders prior to trying; it is not included in CEA's list of common expenses.
I appreciate this point a lot! I think the counterfactual value of taking history classes is pretty hard to generalize across university students because everyone has different tradeoffs. Some students might have more value from taking other kinds of classes, even other kinds of "padding" classes. Good candidates might be CS, economics, philosophy, math, and maybe a writing class. My general sense is that the value of those classes are more well known in EA (e.g. I see many people majoring in the first four) and probably don't need an explanation. I think history might need more of an explanation, which is why I offered one here. In general, I do agree that people should be thinking about this counterfactually, but I think the outcome would be very dependent on the individual student.
Classes are often not the most efficient way to learn things. History is certainly no different, and I think the idea of history modules sounds very interesting. That being said, I wrote this post mainly for undergrads who have to operate within the boundaries of classes to some extent.
I definitely don't mean to say that classes shouldn't have secondary sources; they should and these sources are important (I am less excited about tertiary sources). I think a key to primary sources is something like the ability to read current sources as primary sources. If you develop the skills to be able to understand primary sources in the context of history, it helps enable you to be able to evaluate primary sources of today. I see history as a good way to learn how to evaluate the world at present, and the world at present has more primary than secondary sources about it.
This is great! Do you have a breakdown of the total number of FTEs for each focus university (rather than just those that were approved recently)? I think this would be useful for people to understand how much the groups are staffed.
It doesn't seem (unlike some other places) that Redwood is directly trying to create AGI, so value will have to come from the techniques being used by other labs. Assuming Redwood finds some promising techniques, how does Redwood plan to influence the biggest research labs that are working towards AGI? Do you hope for your techniques to be useful enough to AGI research that labs adopt them anyway? Do you want to heavily evangelize your techniques in publications/the press/etc.? Or do you expect the work of persuading the biggest players to be better done by somebody else?
Hi Mauricio! More details are in the post linked at the top: https://forum.effectivealtruism.org/posts/N6cXCLDPKzoGiuDET/yale-ea-virtual-fellowship-retrospective-summer-2020#Selectiveness
I agree, I do not think I would say that "we have evidence that there is not a strong relation". But I do feel comfortable saying that we do not have evidence that there is any relation at all.
The 95% confidence intervals are extremely wide, given our small sample sizes:
Spring 2019: -0.75 to 0.5 (95th) and -0.55 to 0.16 (75th)
Fall 2019: -0.37 to 0.69 and -0.19 to 0.43
Spring 2020: -0.67 to 0.66 and -0.37 to 0.37
Summer 2020: -0.60 to 0.51 and -0.38 to 0.26
The upper ends are very high, and there is certainly a possibility that our interview scoring process is actually good. But, of the observed effects, two are negative, and two are positive. The highest positive observed correlation is only 0.10.
To somebody who has never been to San Francisco in the summer, it seems reasonable to expect it to rain. It's cloudy, it's dark, and it's humid. You might even bring an umbrella! But, after four days, you've noticed that it hasn't rained on any of them, despite continuing to be gloomy. You also notice that almost nobody else is carrying an umbrella; many of those who are are only doing so because you told them you were! In this situation, it seems unlikely that you would need to see historical weather charts to conclude that the cloudy weather probably doesn't imply what you thought it did.
This is analogous to our situation. We thought our interview scores would be helpful. But it's been several years, and we haven't seen any evidence that they have been. It's costly to use this process, and we would like to see some benefit if we are going to use it. We have not seen that benefit in any of our four cohorts. So, it makes sense to leave the umbrella at home, for now.
Broadly, I agree with your points. You're right that we don't care about the relationship in the subpopulation, but rather about the relationship in the broader population. However, there are a couple of things I think are important to note here:
In general, we believe that in order to use a selection method based on subjective interview rankings -- which are very time-consuming and open us up to the possibility of implicit bias -- we need to have some degree of evidence that our selection method actually works. After two years, we have found none using the best available data.
That being said -- this fall, we ended up admitting everyone who we interviewed. Once we know more about how engaged these fellows end up being, we can follow up with an analysis that is truly of the entire population.