I hadn’t really put much effort into crisping the entry when I first created it, so I’m not surprised there. I do still think that, in the context of a wiki filled with a variety of tags already (including “Fabianism,” which has been used for zero posts), it would make sense to add a new tag for this subject—which I agree is related to messaging, cost-effectiveness calculations, local priorities research, cause neutrality, and a few other things but is not entirely subsumed by any one of those tags. However, it seems that I am alone (and outclassed) on this point, so feel free to do/delete as you see fit.
Harrison D
Karma: 516
I may not be fully/properly understanding your objection(s), but it sounds like you are interpreting the tag as more about philosophical issues (e.g., the demandingness of morality), whereas my intent for the category (as well as that of the first post I tagged with this) was more about questions regarding the outreach/branding/community-building strategy of EA as a movement: for example, to what extent should EA try to persuade people to change their cause areas altogether (which tends to be a more difficult sell) vs. encouraging/helping people to find more-effective charities within their own preferred cause areas (even if such charities are less impactful than ones in other areas)? Is it better to support or provide research about something (hypothetically low/medium-impact) like “most effective (1st-world) disaster relief funds” as opposed to supporting or providing research about something typically higher-impact like “most effective 3rd-world health and development charities,” once you take into consideration less-direct effects like movement image/growth, moral circle expansion, etc.
I would be interested to see an 80K Hours profile on this field (among many others) if there isn’t one already, but regarding the points you mentioned:
“this engineering sector (and even the military itself) seem to have great impact. Hence, it should be a good candidate to somehow be an “effective” sector to work in.”
On some level, I agree that defense engineering and the broader defense industry can be impactful, but even if something is impactful overall it may not be a good candidate for cause prioritization. For example, it may not be neglected in the important areas (e.g., many thoughtful and/or skilled people are already working in the field), so having an extra person (or a more ethical and/or skilled person than whoever they are replacing) may not be as valuable as one might expect. Additionally, it may not be a very tractable field for someone who wants to have an impact by being more ethical, since institutional momentum/precedent and corporate incentive may be very strong, and such individuals will often just be a small part in a large bureaucracy/organization. This latter point is especially significant given that improvements in the industry are not so unambiguously good—in fact, in some instances they might be bad if, for example, a new technology leads to destabilizing dynamics. (80K actually does briefly touch on this idea in point 6 of this article) Additionally, my understanding is that there are already some non-EA efforts to promote better norms regarding weapons research (such as the anti-nuke campaigns like ICAN and the anti lethal autonomous weapons (LAWs) campaign, although I know both groups/movements have met with mixed reactions from EAs)
Ultimately, I would still like to hear others’ opinions or see any research people may have found, but on the surface I don’t see it as clearly neglected by the EA community relative to its potential value. Furthermore, I feel that even if someone does see this field as very valuable, they should probably see defense/security policy (e.g., in executive branches of government, as policy researchers in think tanks) as even more promising, since that work seems less saturated and less constrained.
This ^ I immediately went to the comments to make the same point when I read that (and re-read it twice to make sure it wasn’t just satire).
In their current form these question are rather broad which makes them a bit hard to effectively/insightfully answer. That being said, my thinking is:
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Depending on how broad your definition of “defense industry” is, most likely there are some positions in the field that make sense to pursue if someone already has relevant connections and/or experience, especially some things related to AI safety or biosafety/biosecurity (while my cursory impression is that things related to nuclear weapons or missile defense are less promising due to effort saturation (less neglectedness), inflexibility of long-standing systems, the fact that asymmetric improvements in such weapons/defenses could be destabilizing, etc.). However, aside from those areas nothing else immediately comes to mind, and overall I suspect that the defense industry is probably not the best career path for most people—even for someone interested in international security there are other options like focusing on security policy. (If your parents are arms magnates, I’d say it might be a good idea, but otherwise I’m fairly skeptical)
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I can’t really provide a good answer to this, in part because I’m not even sure what issues to address/focus on, but also in part because I haven’t seen it as a impactful question to answer: we can’t just wish away a (bad?) industry by snapping our fingers, much like we can’t just wish away all nuclear weapons in the world. Should America have a defense industry? Absolutely. Does America spend too much on its defense industry? Most likely in some areas yes, but overall I don’t know. One plain justification is “without an American defense industry, other countries (e.g., China, Russia) will gain relative military advantage and bully/invade surrounding countries, prop up brutal dictators, etc. Additionally, subnational groups will still acquire weapons and commit similar acts of violence against populations…”
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The purpose of the TUILS framework is to break down advantages and disadvantages into smaller but still collectively exhaustive pieces/questions (e.g., are the supposed benefits counterfactual, how likely will does the desired state materialize).
I’m not sure if you have a very particular definition for “Cost Effectiveness Analysis,” but if you just mean calculating costs and benefits then yes: the whole point of the framework is to guide your reasoning through the major components of an advantage or disadvantage. There is a spectrum of formality in applying the TUILS framework, but the informal version basically treats the relationship between the factors as roughly multiplicative (e.g., anything times zero is zero, if you only solve half the problem you may only get half the originally claimed benefit—assuming there is a linear relationship). I haven’t fully sketched out a truly formal/rigorous version since I’m not a mathematician and I don’t see that as the main value of the framework (which tends to more about assumption checking, intuition pumping, concept grouping/harmonizing, and a few other things). However, if you’re actually interested in the more-formal application, I could write out some of my rough thoughts thus far. (It’s basically “imagine an n-dimensional graph, with one of the dimensions representing utility and everything else representing input variables/measure…”)
In terms of example applications, I gave some simplified example applications in the post (see the subsection “ Examples of the TUILS framework being applied”), but I haven’t done any written, deep, formal analyses yet since I haven’t seen that as a valuable use of time since organic interest/attention didn’t seem very high even in the simpler version. That being said, I’ve also used a less refined/generalized version of the framework many times orally in competitive policy debate (where it’s referred to as the stock issues)—in fact, probably more than 90% of policy debate rounds I watched/participated in make reference to it. (All of this just to say that a version of it is pretty widely used in the policy debate community)
It’s just that it related to a project/concept idea I have been mulling over for a while and seeking feedback on
(Perhaps you could take a first step by responding to my DM 😉)
I’m not very programming-oriented so I can’t really engage with the technical side of things, but I am curious whether/to what extent you think that a quantitatively oriented tool like Pedant would be complemented by a conceptually-oriented framework like the [TUILS framework] (https://forum.effectivealtruism.org/posts/SyWCmqtPsi4PsxnW8/the-tuils-framework-for-improving-pro-con-analysis-1) ? The latter is not so (inherently) focused on specific calculations or parameter harmonization, but it does try to highlight bigger picture conceptual steps/assumptions (e.g. counterfactual effects, the normative value of a given change).
Thanks for posting this, I have had similar thoughts/questions in the past and briefly talked with a few people about it, but I don’t think I’ve posted much about it on the forum.
I was especially interested in a point/thread you mentioned about people perceiving many charities as having similar effectiveness and that this may be an impediment to people getting interested in effective altruism. I’m not familiar with the research/arguments there, but yeah it sounds like if that is true it might be beneficial/effective to first “meet people where they are” (in terms of cause passions/focuses/neutrality) by showing the differences in effectiveness in that one cause area: I imagine that part of the reason that some people may resistant to believing in high differences in impact is some (perhaps unconscious) motivated reasoning since they don’t want to acknowledge their current passion is not very comparatively impactful.
In other words, if people are resistant to changing their minds in part because of a reinforcing loop of “I don’t want to admit I may be wrong about my passion/cause area,” “many charities have similar impacts,” and “What I am doing is impactful,” one may be able to more effectively change people’s thoughts about the second point by highlighting differences in charity effectiveness within a cause area. Specifically, this could help by sidestepping the “I don’t want to change my cause area” motivated reasoning/resistance. Of course, many people might still be resistant to changing their minds more broadly, and this all depends on the extent to which that claim about people’s perceptions of effectiveness is true, but it seems like it might be helpful for some people.
In some of my conversations with people and through reading some posts/comments on the forum I’ve seen this topic come up multiple times, so I figured it might be good to have a dedicated tag for this. In my quick search (on mobile) I did not see similar existing tags, but it’s quite possible I just missed something. I’ll admit my description was typed up in a hurry so it could be improved, but if this is too niche for a tag I would be surprised. Let me know if you have suggestions for how it should be changed/improved!
^ A link to a mini-model of what I had in mind.
However, I’ll note that as I began making it, I started to see how representing the information could become quite complex or imprecise, so I began to become more skeptical of the value of this (although I think that even an over-simplified list could still be of some value/interest, even if it would have quite a few limitations and thus might just best serve as a quick-reference/encyclopedia). As an example of the limitations, like I mentioned before, consider a situation where someone has a positive reputation among one large group of people, but a negative reputation among another group of people.
I don’t have an answer, but I would also be interested in a spreadsheet of “people who have supported EA” with loose measures on scales of 1–10 for things like “how widely known is this person,” “(roughly) how respected is this person’s opinions by their audience,” and “how much did they support EA?” The second one might be especially tricky since some people might have a very polarized reputation (e.g., Trump, Elon Musk). (Then again, it might also look kind of weird 😅)
Have you seen Taleb’s Black Swan book? (https://en.m.wikipedia.org/wiki/The_Black_Swan:_The_Impact_of_the_Highly_Improbable) I personally haven’t read it, but based on the description it seems related to what you’re describing. Either way, I think it is a good point to consider
[Summary: Most people would probably agree that science benefited greatly from the shift to structured, rigorous empirical analyses over the past century, but some fields still struggle to make progress. I’m curious whether people think that we could/should seek to introduce more structure/sophistication to the way researchers make and engage with theoretical analyses, such as something like “epistemic mapping”]
I just discovered this post, and I was struck by how it echoed some of my independent thoughts and impressions, especially the quote: “But it should temper our enthusiasm about how many insights we can glean by getting some data and doing something sciency to it.”(What follows is shortform-level caveating and overcomplicating, which is to say, less than I normally would provide, and more about conveying the overall idea/impression)
I’ve had some (perhaps hedgehoggy) “big ideas” about the potential value of what I call “epistemic mapping” for advancing scientific study/inquiry/debate in a variety of fields. One of them relates to the quote above: the “empirical-scientific revolution” of the past ~100-200 years (e.g., the shift to measuring medical treatment effectiveness through inpatient/outpatient data rather than professionals’ impressions) seems to have been crucial in the advancement of a variety of fields.
However, there are still many fields where such empirical/data-heavy methods appear insufficient and where it seems like progress languishes: my impression has been that this especially includes many of the social sciences (e.g., conflict studies, political science, sociology). There are no doubt many possible explanations, but over time I’ve increasingly wondered whether a major set of problems is loosely that the overall complexity of the systems (e.g., human decision making process vs. gravitational constants) + the difficulty of collecting sufficient data for empirical analyses + (a few other factors) leads to a situation of high information lossage between researchers/studies and/or people are incentivized to oversimplify things (e.g., following the elsewhere-effective pattern of regression analyses and p<0.05 = paper). I do not know, but if the answer is yes, that leads to a major question:
How could/should we attempt to solve or mitigate this problem? One of the (hedgehoggy?) questions that keeps bugging me: We have made enormous advances in the past few hundred years when it comes to empirical analyses; in comparison, it seems that we have only fractionally improved the way we do our theoretical analysis… could/should we be doing better? [Very interested to get people’s thoughts about that overall characterization, which even I’ll admit I’m uncertain about]
So, I’m curious if people share similar sentiment about our ability/need to improve our methods of theoretical analysis, including how people engage with the broader literature aside from the traditional (and, IMO, inefficient) paragraph-based literature reviews. If people do share similar sentiment, what do you think about that concept of epistemic mapping as a potential way of advancing some sciences forward? Could it be the key to efficient future progress in some fields? My base rates for such a claim are really low, and I recognize that I’m biased, but I feel like it’s worth posing the question if only to see if it advances the conversation.
(I might make this into an official post if people display enough interest)
I agree that such mapping seems like it could be very useful for catching people up to speed on a complicated/messy topic more quickly, particularly since I see it as a more efficient/natural way of conveying and browsing information about a controversial or complicated question.
As for the diagram you mentioned, I think that something like that might be helpful, but personally I consider that a map for broader academic questions should probably use semantically-richer relationship information than just (+) and (-). For an example of what I mean, see the screenshots of diagrams I posted in my post on the subject.
I agree the complexity level question is a tough question, although my impression has been that it could probably be implemented with varying levels of complexity (e.g., just focusing on simpler/more-objective characteristics like “data source used” or “experimental methodology” vs. also including theoretical arguments and assumptions). I think the primary users would tend to be researchers—who might then translate the findings into more-familiar terms or representations for the policymaker, especially if it does not become popular/widespread enough for some policymakers to be familiar with how to use or interpret it (somewhat similar to regression tables and similar analyses). That being said, I also see it as plausible that some policymakers would have enough basic understanding of the system to engage/explore on their own—like how some policymakers may be able to directly evaluate some regression findings.
Ultimately, two examples of the primary use cases I envision are:
Identifying the ripple effects of changes in assumptions/beliefs/datasets/etc. Suppose for example an experimental finding or dataset which influenced dozens of studies is shown to be flawed: it would be helpful to have an initial outline of what claims and assumptions need to be reevaluated in light of the new finding.
Mapping the debate for a somewhat contentious subject (or just anything where the literature is not in agreement), including by identifying if any claims have been left unsupported or unchallenged.
It seems that such insights might be helpful for a researcher trying to decide what to focus on (and/or a grantmaker trying to decide what research to fund).
I consider the issue of identifying knowledge gaps (and the semi-opposite concept: arguments/experiments which are highly influential in a field) as another good potential use case/benefit of epistemic mapping: both the importance of and lack of research on a concept may become more apparent with visualization—especially if the map/graph shows that the claim or assumption is very influential in the literature but it has not received much support or scrutiny. I’d be curious to get your thoughts on the potential usefulness/viability of such a project for such purposes.
I’m glad to see this project go live, as I (and other people) have frequently griped about so many job boards seeming to focus on positions that required experience that I, as a recent college graduate do not have.
At the same time, I’d like to reiterate/reemphasize my comment from the previous post on this project: I would strongly recommend going beyond simply providing a list of high-impact, highly-competitive positions that people like younger me probably would have looked at and said “I’ll focus on applying for these positions,” only to end up being systemically under-qualified/competitive and not get anything. For example, you could include on the site some kind of link to advice that basically says things like “don’t just apply for these positions; also apply for less-competitive internships even if they aren’t directly EA related or even if they aren’t directly related to your field.” (This is where some of the non-EA organization suggestions I’ve had in mind might come into play.)
While I’m supportive of gathering this position information in one place, I could also see it as having potential drawbacks if it causes people to over-focus on these positions: I could totally see myself (someone who has struggled for years with mediocre success to get experience in the fields I’m pursuing) falling into that trap.
On a related note, my general impression has been “if you can manage to get a position in a high-impact area early in your career, that’s great, but the reality is that most positions won’t themselves directly lead to high impact; the key is the experience, professional connections, and future application material you get from such positions.”
I’ve actually had a concept for an EA/EA-adjacent drawing/painting stuck in my head for a while now, but 1) I can’t recall/determine whether it is just closely related to something someone has already made and I saw, and 2) I suck at drawing/painting, so I was hoping to see if there were any more-artistically inclined people who might be interested in realizing the concept.
Basically, it’s a symbolism-heavy painting about anti-death/longtermism/human striving, with most (~80%) of the left side darkened/shadowed, followed by a line of people on the right edge of the shadow, containing a variety of scenes of humanity/life, including one or two people trying to pass on a torch to someone/somewhere off the canvas. (I have plenty more details written down, but I’ll leave it at the basic idea here. If anyone 1) has seen something similar that I may just be forgetting, and/or 2) is interested/inspired to work on it further, just let me know! I would be personally very interested in seeing such a painting, but I totally lack the artistic skills to make it happen)