I have to think more about the status dynamics that Eliezer talked about. There’s probably something to it… But this part stands out as wrong or at least needing nuance/explanation:
Thellim hasn’t gotten tenure at a prestigious university which means they’ll probably reject the paper anyways
I think most academic venues do blind reviews and whoever decides whether or not to accept a paper isn’t supposed to know who wrote it? Which isn’t to say that the info won’t leak out anyway and influence the decision. (For example I once left out the acknowledgements section in a paper submission, thinking that, like the author byline, I was supposed to add it after the paper was accepted, but apparently I was actually supposed to include it and someone got really peeved that I didn’t.)
MIRI suggested I point out that Cheating Death In Damascus had recently been accepted in The Journal of Philosophy, a top philosophy journal, as evidence of (hopefully!) mainstream philosophical engagement.
From talking with people who do work on a lot of grant committees in the NIH and similar funding orgs, it’s really hard to do proper blinding of reviews. Certain labs tend to focus on particular theories and methods, repeating variations of the same idea… So if you are familiar the general approach of a particular lab and it’s primary investigator, you will immediately recognize and have a knee-jerk reaction (positive or negative) to a paper which pattern-matches to the work that that lab / subfield is doing.
Common reactions from grant reviewers:
Positive—“This fits in nicely with my friend Bob’s work. I respect his work, I should argue for funding this grant.”
Neutral—“This seems entirely novel to me, I don’t recognize it as connecting with any of the leading trendy ideas in the field or any of my personal favorite subtopics. Therefore, this seems high risk and I shouldn’t argue too hard for it.”
Slightly negative—“This seems novel to me, and doesn’t sound particularly ‘jargon-y’ or technically sophisticated. Even if the results would be beneficial to humanity, the methods seem boring and uncreative. I will argue slightly against funding this.”
Negative—“This seems to pattern match to a subfield I feel biased against. Even if this isn’t from one of Jill’s students, it fits with Jill’s take on this subtopic. I don’t want views like Jill’s gaining more traction. I will argue against this regardless of the quality of the logic and preliminary data presented in this grant proposal.”
I will self-downvote so this isn’t the top comment. Yud’s stuff is neat, but I haven’t read much on the topic, and passing some along when it comes up has been a good general heuristic.
I have to think more about the status dynamics that Eliezer talked about. There’s probably something to it… But this part stands out as wrong or at least needing nuance/explanation:
I think most academic venues do blind reviews and whoever decides whether or not to accept a paper isn’t supposed to know who wrote it? Which isn’t to say that the info won’t leak out anyway and influence the decision. (For example I once left out the acknowledgements section in a paper submission, thinking that, like the author byline, I was supposed to add it after the paper was accepted, but apparently I was actually supposed to include it and someone got really peeved that I didn’t.)
Also it seems weird that Eliezer wrote this in 2021, after this happened in 2019:
From talking with people who do work on a lot of grant committees in the NIH and similar funding orgs, it’s really hard to do proper blinding of reviews. Certain labs tend to focus on particular theories and methods, repeating variations of the same idea… So if you are familiar the general approach of a particular lab and it’s primary investigator, you will immediately recognize and have a knee-jerk reaction (positive or negative) to a paper which pattern-matches to the work that that lab / subfield is doing.
Common reactions from grant reviewers:
Positive—“This fits in nicely with my friend Bob’s work. I respect his work, I should argue for funding this grant.”
Neutral—“This seems entirely novel to me, I don’t recognize it as connecting with any of the leading trendy ideas in the field or any of my personal favorite subtopics. Therefore, this seems high risk and I shouldn’t argue too hard for it.”
Slightly negative—“This seems novel to me, and doesn’t sound particularly ‘jargon-y’ or technically sophisticated. Even if the results would be beneficial to humanity, the methods seem boring and uncreative. I will argue slightly against funding this.”
Negative—“This seems to pattern match to a subfield I feel biased against. Even if this isn’t from one of Jill’s students, it fits with Jill’s take on this subtopic. I don’t want views like Jill’s gaining more traction. I will argue against this regardless of the quality of the logic and preliminary data presented in this grant proposal.”
Ah, sorry that this wasn’t very helpful.
I will self-downvote so this isn’t the top comment. Yud’s stuff is neat, but I haven’t read much on the topic, and passing some along when it comes up has been a good general heuristic.
No need to be sorry, it’s actually great food for thought and I’m glad you pointed me to it.