I am a doctoral student of Public Policy and Political Economy at UTDallas and looking for opportunities in the social sector, especially in think tanks. I’ve previously interned at the Center for Global Development and worked as a Data Analyst at a boutique consulting firm for ~2.7 years. My undergraduate degree was in Physics.
If you are considering reading something I have written on this forum, please see: Interpreting the Systemistas-Randomistas debate on development strategy
Really liked this one -brief and to the point! Here is my attempt to condense it further presuming I understood the author properly and also understood the ITN framework properly (correct me if I’m wrong about either!) :
Say I subscribed to the ITN (Importance, Tractability, Neglectedness) framework before I started my work on cause area X and wrote down my scores for I, T and N. When I look at an example of someone failing and giving up (like the one OP mentions in the post), my first instinct would be to do 2 things:
Increase the N score I had given earlier for X, since I now see one less person/entity working on X.
Reduce the T score I had given earlier, since there is failure.
If I understood it correctly, this post argues that 2 should be modified: Modified 2. Maintain the T score I had given earlier, since the devil is in the details and the details of my solve are different from the failed solve I am looking at.
So, I still update my neglectedness (a small update) but maintain my tractability score (no update). Overall, not an “over-update”.
Ah! That makes sense.
I agree that the EA thing to do would be to work on and explore cause areas by oneself instead of just blindly relying on 80k hours cause areas or something like that.
If someone said “I am not going to wear masks because I am not going to defer to expert opinions on epidemiology of COVID19” how would someone taking the advice of this article respond to that?
Overall, being a noob, I found the language in this article difficult to read. So, I am giving you a specific scenario that many people can relate to and then trying to learn what you are saying from that.
I am pretty sure this is not worthy of a full cross post, but I think a shortform could be tolerable.
I wrote a piece about Economic Complexity. I have seen a few posts on the forum (Like 1 and 2) about Complexity Science and I appreciate the healthy skepticism people have of it. If you are also such an appreciator, you might like my piece.
I attended EAGx Berkeley event on Dec 2, 2022. Previously I had engaged with EA by participating & later facilitating in Intro to EA Virtual programs, writing on this forum and attending the US Policy careers speaker series. All these previous engagements were virtual. This was the first time I was in a room full of EAs! I want to thank the organizers for giving me a travel grant for this event. It would have been impossible for me to attend this event without it.
It was a net positive experience for me. I had 4 goals in mind. 3 of them went much better than expected and 1 of them didn’t go as well. I explain my goals and how they went below. They are listed in priority:
Find an internship (especially in DC)
When I applied to the event, this goal was Find an internship (anywhere) and it was 2nd priority. But I was getting closer to the final rounds of a fellowship program which was conditional on getting a DC internship. So, I increased priority before the conference.
This goal didn’t go as well as I thought it would. Many orgs I spoke to didn’t have applications open. They just asked me to fill some sort of ‘general interest form’ on their website and told me when positions might open. I guess December is not really hiring season (at least for the orgs I was interested in)
Get advice on if I should stop at my Masters or go all the way to a PhD
When I applied to the event, this goal was originally What after Masters and it was 3rd priority. But one of my profs at uni spoke with me to consider a PhD a week before the conference. So, it changed and got higher priority before the conference.
I got some of the best advice on this. The 1-on-1 and office hours really helped me. Also, on day 1 of the conference Alex Lawsen spoke about An easy win for hard decisions.. So I ended up writing up a Google doc on this decision and sending it to many of the people I did 1-on-1s with. In addition, I attended a session on ‘Theory of Change’ by Michael Aird and it is going to play a huge role in how I finally make this decision.
Get advice on starting a student group
This was actually priority 1 when I applied. But my cofounder also ended up getting selected for the event and since he could also talk about it with folks it made sense to push this down, given there were other goals that had to be prioritized as well.
I got good suggestions for this. My cofounder spoke with Jessica Mccurdy. I spoke with another student group organizer who got me into the ‘EA Groups’ Slack channel.
Learn if there is any intersection between AI safety and policy
I made up this goal on day 2 of the conference given the number of AI safety events that happened. That is why it is bottom priority.
I learnt that the jargon here is “AI Governance”. I saw that many AI safety orgs didn’t really hire folks to do this (with notable exceptions). I hope to spend a few hours this winter break looking into this given that a few people told me that this is a fairly neglected area. If I find it really interesting, I might end up writing up something on the forum about this.
Other thoughts:
Given that the FTX scandal happened recently, I was kind of worried the event would be all about that. I had read enough about it on social media and on the forum, felt bad for the people who got cheated, recognized what I can learn from it and by the time the conference rolled on I was over it. I didn’t want it to be stirred up all over again. So, I was glad to not be forced into any conversations about it. There were some events on the agenda on that topic but I was able to avoid them. So, discussions on this very important disaster did happen but it was out of the way for those who had worked through it which I really appreciated.
I was generally encouraged and felt optimistic seeing a bunch of people who (are atleast trying to) care about the world. Some of them were eccentric, some of them were too gloomy (IMO) about x-risks but all were kind people.
I personally felt that I was generally being too risk averse. Seeing people daring to try out of the ordinary stuff has helped me update a little bit more towards risk taking (of course keeping in mind to internalize risks to the max)
Thanks a lot for making this! I just started research on something Econ growth adjacent and this reading list could come in handy. So I really appreciate it.
I do not think its about discount rates. I was recently corrected on this point here. It looks like conservatives and moderates thinking closer to the present have other better reasons like population axiologies or tractability concerns or something along those lines.
There is ambiguity in the terminology here. So here is how I visualize it with my own terminology. Its not a Venn diagram but this is how I see it.
I thoroughly enjoyed this! The tone of the writing matched perfectly with the idea that is being conveyed.
If I may add a category:
Desi EA—Someone not from a developed country kinda feeling out of place and totally inadequate to do anything about most mainstream EA cause areas. Mostly English-speaking educated elite from developing countries who possibly watch a lot more Hollywood than their local genres. (Also has some inability to parse slang. I honestly didn’t understand what the moniker “IDW” and “A-aesthetic” meant although I think I understood the explanation)
Recently Less wrong has created this feature. C’mon EA Forum!
Please let me search within my bookmarks.
In general, I read something and bookmark it if I liked it. Then that thing that I read comes up in conversation. I go into my bookmarks to find it so that I can share it with the other person mid-convo quickly but then I can’t retrieve it from the bookmarks list as fast as I thought I could! This happens to me in almost every session as a facilitator of the EA Virtual programs!
On the topic of saving posts—I personally use the bookmarks feature quite a bit. Just wanted to mention it in case someone wasn’t aware. The one issue I have is that I can’t search within my bookmarks.
One can bookmark posts by clicking on the 3 dots just below the title of the post and then clicking on Bookmark. Then the Bookmarks can be accessed from the dropdown menu that appears underneath the username.
So EA isn’t “just longtermism,” but maybe it’s “a lot of longtermism”? And maybe it’s moving towards becoming “just longtermism”?
EA has definitely been moving towards “a lot of longtermism”.
The OP has already provided some evidence of this with funding data. Another thing that signals to me that this is happening is the way 80k hours has been changing their career guide. Their earlier career guide started by talking about Seligmann’s factors/Positive Psychology and made the very simple claim that if you want a satisfying career, positive psychology says your life must involve an aspect of helping others in a meaningful way. Then one fine day they made the key ideas page and somehow now longtermism has become the “foundation” of their advice. When the EA org that is most people’s first contact with EA makes longtermism as the “foundation” of their recommendations, it should defintiely mean that EA now wants to move towards “a lot of longtermism”.
What if EA was just longtermism? Would that be bad? Should EA just be longtermism?
Yes, it would be bad if EA was just longtermism.
I believe that striving to make the simplest and honest case for a cause area is not a choice but an intellectual obligation. It is irresponsible to put forth unnecessarily complicated ideas and chase away people who might have otherwise contributed to that cause. I think Longtermism is currently an unnecessarily complicated way for us to make the case to convince people to contribute to most of the important EA cause areas. My thoughts come from this excellent post.
I am willing to concede my stance on this 2nd question if you can argue convincingly that:
striving to make the simplest and honest case for a cause area is not an intellectual obligation we need to hold.
there are some cause areas where longtermism is actually the simplest argument one can make to convince people to work on them. Of course, that would mean EA can then only work on those cause areas where this is true, but that might not be so bad if it is still highly impactful.
Some hedging:
I still believe Longtermism is an important idea. If you are a philosopher I would highly encourage you to work on it. But I just don’t think it is as important for EA as EA orgs are currently making it seem like. This is especially true of Strong Longterism.
I also think that this could all be a case of nomenclature being confusing. Here is a post talking about this confusion. Maybe those who do Global health & development are also on the longtermism spectrum but are just not as ‘gaga’ about it as Strong longtermists seem to be. After all it’s not as though Expectation value bets on the future (maybe not far future) can’t be made in a Global health & development intervention! If we clarify the nomenclature here then it could be possible that “Longtermism” (or whatever else the clarified nomenclature would call it) could become a clearer & simpler explanation to convince people to contribute to a cause area. Then I would still be fine with EA becoming “Longtermism” (in the clarified nomenclature).
I am really happy to see someone doing something about the replication crisis. Sorry that you didn’t get funded. I know very little about FTX or grantmaking in general and so I can’t comment on the nature of your proposal or how to make it better. But now that I see someone doing something about the replication crisis I have done an update on the Tractability of this cause area and I am excited to learn more!
This excitement lead to some small actions from my end:
I visited the Institute for Replication website and found it to be very helpful. I really appreciate the effort that went into making the Teaching tab on the website. I will try to make time in the near future (within a month or so) to go through the resources carefully.
I subscribed to the BITSS YouTube Channel and skimmed through a couple of chapters of the open source textbook, Reproducible Data Science.
I looked for material on the replication crisis elsewhere on this forum. I found this panel discussion from EA Global 2016 and… thats about it! Since, IMO, not enough EA material is there on this cause area, I put down a comment in the What posts do you want someone to write? in the hopes that someone wading through it for ideas will decide to write more about it.
One thing still unclear to me—are there career opportunities here or just volunteer opportunities? In the proposal, you mentioned “reproducibility analysts at selected journals”—I had no idea that was a thing that people did! But it sounds like a very interesting role to me considering the Scale of the problem. How many people do it and is there a high demand for it? What sort of degree does someone need to do it?
All the best with the project! I sincerely hope someone else will fund it and it will be successful.
Write about the replication crisis in the 80k hours Problem profile style. Basically, write about the problem, apply the SNT framework to it, mention orgs currently working on it, mention potential career options for someone who wants to address this problem etc..
This suggestion came after reading this post.
From reading this and other comments, I think we should rename longtermists to be “Temporal radicalists”. The rest of the community can be “Temporal moderates” or even be “Temporal conservatives” (aka “neratermists”) if they are so inclined. I attempt to explain why below.
It looks like there is some agreement that long-termism is a fairly radical idea.
Many (but not all) of the so-called “neartermists” are simply not that radical and that is the reason why they perceive their monicker to be problematic. One side is radical and many in the other side are just not that radical while still believing in the fundamental idea
By “radical”, I mean believing in one of the extreme ends of the argument. The rest of the community is not on the other extreme end which is what “neartermism” seems to imply. It looks like many of those not identifying as “longermists” are simply on neither of the extreme ends but somewhere in the spectrum between “longtermists” and “neartermists”. I understand now that many who are currently termed “Neartermists” would be willing to make expectation value bets on the future even with fairly low discount rates. From the link to the Berger episode that JackM provided (thanks for that BTW!):
“It’s tied to a sense of not wanting to go all in on everything. So maybe being very happy making expected value bets in the same way that longtermists are very happy making expected value bets, but somehow wanting to pull back from that bet a little bit sooner than I think that the typical longtermist might.”
So to overcome the naming issue, we must have a way to recognize that there are extreme ends in this argument and also a middle ground. With this in mind, I would rename the currently “longtermists” as “Tempoal radicalists” while addressing the diversity of opinions in the rest of the community with two different labels “Temporal moderates” and “Temporal conservatives” (which is the synonym of “neartermism”). You can even call yourself ‘Temporal moderate leaning towards conservatism’ to communicate your position with even more nuance.
PS: Sorry for too many edits. I wanted to write it down before forgetting it and later realized I had not communicated properly.
Is it possible to have a name related to discount rates? Please correct me if I am wrong, but I guess all “neartermists” have a high discount rate right?
For me, the big revelation was that EA was not just about causes that are supported by RCTs/empirical evidence. It has this whole element of hits-based giving. In fact, the first time I realized this, I ended up creating a question on the forum about the misleading definition.
Overall, this seems like a weak criticism worded strongly. It looks like the opposition here is more to the moniker of Complexity Science and its false claims of novelty but not actually to the study of the phenomenon that fall within the Complexity Science umbrella. This is analogous to a critique of Machine Learning that reads “ML is just a rebranding of Statistics”. Although I agree that it is not novel and there is quite a bit of vagueness in the field, I disagree on the point that Complexity Science has not made progress.
I think the biggest utility of Complexity Science comes in breaking disciplinary silos. Rebranding things to Complexity Science, just brings all the ideas on systems from different disciplines together under one roof. If you are a student, you can learn all these phenomena in one course or degree. If you are a professor, you can work on anything that relates to Complex Systems phenomena if you are in a Complexity department. The flip side of it is, you might end up living in a world of hammers without nails—you would just have a bunch of tools without a strong domain knowledge in any of the systems that you are studying.
My take on Complexity Science is that it is a set of tools to be used in the right context. For your specific context, some or none of the tools of Complexity Science can be useful. Where Complexity Science falls apart for me is when it tries to lose all context and generalize to all systems. I think the OP here is trying to stay within context. The post is just saying we can build ABMs to approach some specific EA cause areas. So I am more or less onboard with this post.
On a final note, I am in agreement with your critique on abuse of Power Laws. There are too many people that just make a log-log plot, look at the line and exclaim “Power law!”. The Clauset-Shalizi-Newman paper you linked to is the citation classic here. For those who do network theory, instead of trying to prove your degree distribution is a power law, I would recommend doing Graphlet Analysis.
I am an immigrant (F1) in the US (and I would like to think of myself as ‘high-skilled’ although others may disagree!). So, I am clearly biased.
It all sounds good in theory but it would be hard to assess what counts as AI-related work and what doesn’t. Even just a simple regression can be called “Machine Learning”. Economists have to do regressions basically everyday. In that case, they would have it in their resume and then someone in the VISA office would still reject them because they would have to assume ‘Regression means AI’ and your plan to let the “Oxford-educated economist” into the US would still be foiled. Also skilled economists could just work at tech firms and help them make money which they could then invest in developing AI further.
PS:- I downvoted this post. As I said, I am biased. But I saw very little effort from the author to actually provide references/evidence to substantiate some of the implied causalities. For instance, the author says things like “This policy is unattractive if you think”. IMHO a better post in the “Effective Altrusim” forum (which is based on ‘evidence and reasoning’ and not just what people like to think) would be link to some empirical work that actually shows firms don’t simply just shift if you restrict high-skilled immigration. Here is a study that claims the contrary that indeed immigration restrictions on high-skilled workers simply moves operations offshore: Glennon, B. (2023). How do restrictions on high-skilled immigration affect offshoring? Evidence from the H-1B program. Management Science. https://economics.nd.edu/assets/361162/bglennon_immigration_offshoring.pdf