I’d love to see some more information about the distribution (e.g. percentiles, change since previous years, breakdown by organization size/type or by role). Is it possible to provide that while maintaining anonymity?
This is a great post and I, like @rohinmshah, feel that simply the introduction of this general class of discussion is of value to the community.
With respect to expert surveys, I am somewhat surprised that there isn’t someone in the EA community already pursuing this avenue in earnest. I think that it’s firmly within the wheelhouse of the community’s larger knowledge-building project to conduct something like the IGM experts panel across a variety of fields. I think, first, that this sort of thing is direly needed in the world at large and could have considerable direct positive effects, but secondly that it could have a number of virtues for the EA community:
Improve efficiency of additional research: Knowing what the expert consensus is on a given topic will save some nontrivial percentage of time when starting a literature review, and help researchers contextualize papers that they find over the course of the review. Expert consensus is a good starting place for a lit review, and surveys will save time and reduce uncertainty in that phase.
Let EAs know where we stand relative to the expert consensus: when we explore topics like growth as a cause area, we need to be able to (1) have a quick reference to the expert consensus at vital pivots in a conversation (e.g. do structural adjustments work?) and (2) identify with certainty where EA views might depart from the consensus.
Provide a basis for argument to policymakers and philanthropists: Appeals to authority are powerful persuasive mechanisms outside the EA community. Being able to fall back on expert consensus in any range of issues can be a powerful obstacle or motivator, depending on the issue. Here’s an example: governments around the world continue to locally relitigate conversations about the degree to which electronic voting is safe, desirable, secure or feasible. Security researchers have a pretty solid consensus on these questions—that consensus should be available to these governments and those of us who seek to influence them.
Demonstrate to those outside the community that EAs are directly linked to the mainstream research community: This is a legitimacy issue: regardless of whether the EA community ends up being broader or narrower, we are often insisting to some degree on a new way of doing things: we need to be able to demonstrate to newcomers and outsiders that we are not simply starting from scratch.
Establish continued relationships with experts across a variety of fields: Repeated deployment of these expert surveys affords opportunities for contact with experts who can be integrated into projects, sought for advice, or deployed (in the best case scenario) as voices on behalf of sensible policies or interventions.
Identify funding opportunities for further research or for novel epistemic avenues like the adversarial collaborations mentioned in the initial post: Expert surveys will reveal areas where there is no consensus. Although consensus can be and sometimes is wrong, areas where there is considerable disagreement seem like obvious avenues for further exploration. Where issues have a direct bearing on human wellbeing, uncovering a relative lack of conclusive research seems like a cause area in and of itself.
Finally, the question-finding and -constructing process is itself an important activity that requires expert input. Identifying the key questions to ask experts is itself very important research, and can result in constructive engagements with experts and others.
I agree that EAs should continue investigating and possibly advocating different voting methods, and I strongly agree that electoral reform writ large should be part of the “EA portfolio.”I don’t think EAs (qua EAs, as opposed to as individuals concerned as a matter of principle with having their electoral preferences correctly represented) should advocate for different voting methods in isolation, even though essentially all options are conceptually superior to FPTP/plurality voting.
This is because A democratic system is not the same as a utility-maximizing one. The various criteria used to evaluate voting systems in social choice theory are, generally speaking, formal representations of widely-shared intuitions about how individuals’ preferences should be aggregated or, more loosely, how democratic governments should function.Obviously, the only preferences voting systems aggregate are those over the topic being voted on. But voters have preferences over lots of other areas as well, and the choice of voting system relates only to two of them: (a) their preferences over the choice in question and (b) their meta-preferences over how preferences are aggregated (e.g. how democratic their society is).As others in this thread have pointed out, individuals’ electoral preferences cannot be convincingly said to represent their preferences over all of the other areas their choice will influence.So an individual gains utility from a voting system if and only if the utility gained by its superior representation of their preferences exceeds the utility lost in other areas lost by switching. I don’t think this is a high bar to clear, but I do think that, beyond the contrast between broadly democratic and non-democratic systems, we have next-to-no good information about the relationship between electoral systems and non-electoral outcomes.In the simplest terms possible: we know that some voting systems are better than others when it comes to meeting our intuitive conception of democratic government. But we’re concerned about people’s welfare beyond just having people’s electoral preferences represented, and we don’t know what the relationship between these things is.It is totally possible that voting systems that violate the Condorcet criterion also dominate systems that meet the criterion with respect to social welfare. We simply don’t know.It’s also not clear to what degree different voting systems induce a closer relationship between individuals’ electoral preferences and their preferences over non-electoral topics, e.g. by incentivizing or disincentivizing voter education.To reiterate, I strongly support the increased interest in approval voting and RCV that we’re seeing, and I voted for it here in NYC. I want to see my own electoral preferences represented more accurately and I don’t think there is a big risk that (at least here) my other preferences will suffer. But as consequentialists I think we are on very uncertain ground.
I’m doing a lit review on the effectiveness of lobbying and on some of the relevant theoretical background that I’m planning on posting when I’m done. I feel like this is potentially very relevant but I’m not sure if people will be interested.
Just want to follow up to acknowledge that I see that you’re already conducting a survey and that I’m proposing you add a set of questions about personal beliefs/stances/positions.
This is a really cool project! Just want to plug this as a really good opportunity to rigorously study how EA ideas spread: a quick 5-minute pre- and post-survey asking participants Likert-style questions about their positions on various EA-relevant topics and perhaps their style of argument/conversation would be potentially high-value here.
Since assignment will be randomized, there’s a real opportunity here to draw causal conclusions about how ideas spread, even if the external validity will be largely restricted to the EA population.
Thanks for your response! I still have some confusion, but this is somewhat tangentially related. In your CBA, you use an NPV figure of $3752bn as the output gain from growth. This is apparently derived from India’s 1993 and 2002 growth episodes.
The CBA calculation calculates the EV of the GDP increase therefore as 0.5*0.1*3572 = $178.56 bn. You acknowledge elsewhere in your writeup that efforts to increase GDP entail some risk of harm (and likewise with the randomista approach) so my confusion lies with the elision of this possible harm from the EV calculation.
Even if the probability that a think tank induces a growth episode—e.g. the probability that a think tank influences economic policy in country X according to its own recommendations—is 10%, then there is still obviously a probability distribution over the possible influence that successfully implemented think tank recommendations would have. This should include possible harms and their attendant likelihoods, right?
I recognize that the $3,572bn figure comes directly from Pritchett as part of an assessment of the Indian experience, but it’s not obvious to me that the number encapsulates the range of possibilities for a successful (in the sense of being implemented) intervention. I may be missing something, but it seems to me that a (perhaps only slightly) more rigorous CBA would have to itself include an expected value of success that incorporates possible benefits and harms for both Growth and Randomista approaches in the line of your spreadsheet model reading “NPV (@ 5%) of output loss from growth deceleration relative to counter-factual growth.”
I understand that what you’re envisioning is a sort of high-confidence approach to growth advocacy: target only countries where improvements are mostly obvious, and then only with the most robustly accepted recommendations. I still think there is a risk of harm and that the CBA may not capture a meaningful qualitative difference between the growth and randomista approaches. In principle, at least, the use of localized, small-scale RCTs to test development programs before they are deployed avoids large-scale harm and (in my view) pushes the mass of the distribution of possible outcomes largely above 0. No such obstacle to large harms exists, or indeed is even possible, in the case of growth recommendations. Pro-growth recommendations by economists have not been uniformly productive in the past and (I think) are unlikely to be so in the future.
I still favor this approach you suggest but, given the state of the field of growth economics—and the failure of GDP/capita to capture many welfare-relevant variables that you cite at the end of the writeup—I’d be keen to see more highly quantified conversation around possible harms.
Thanks for writing this! I am coming somewhat late to the party , but I wanted to add my support for what you have both written here. I back the concerted research effort you propose and believe it somewhat likely that it will have the benefits you suggest are probable.
I was digging through the Pritchett paper in hopes of doing my own analysis, and I do have a question: how did you calculate the median figure for Vietnam that you reference in section 4 ($6,914 GDP per capita)? I’ve been looking at the Pritchett paper and I can’t quite figure it out. It seems close to the median absolute growth in $PPP presented in Pritchett’s Table 4, but I imagine that’s not right since Table 4 only lists the top 20 growth episodes from the full set of about 300. When I look at the those figures in Appendix A, though, it seems like the median growth episode calculated using PRM (without reference to dollar size) is somewhere around Ecuador’s negative growth in 1978, which doesn’t seem like it would line up even with the conversion to $PPP.
I see that you’ve written that Vietnam/89 is the median growth episode “to be affected by a think tank,” and a little research reveals that Vietnam began a concerted economic liberalization in 1986, so perhaps you have a secondary subset of growth episodes that you believe were affected by think tanks?
I can also sort of see a case for selecting the median from Table 4 of the top 20 but that seems strange since (a) the cutoff is arbitrary and (b) it doesn’t factor in the risk of harm from a think tank-influenced growth episode.
Thanks for your response. I think I should make clear (as I really didn’t do in my initial post) that I mean my comment more broadly: when EAs think about doing ballot initiatives, they should strongly consider doing public opinion polling. In a setting where an EA advocacy group is trying to select (a) which of X effective policies to advocate and (b) in which of Y locales to advocate it, it seems (to me, at least) that polling is cost-effective, since choosing between X*Y potentially large number of independent options is a nontrivial problem that requires a rigorous approach.
In your setting, however (making the binary choice of whether or not to advocate for policy P in location L), I understand why you chose the strategy you did. Your point about the relative cost-effectiveness of talking to local politicians versus conducting an (arguably) expensive poll is well-taken. I don’t have any idea how Swiss referenda work and I conclude from your comment that voters largely follow the lead of their representatives.
I’m not sure how you’re thinking about future efforts along these lines, but if you’re planning on selecting from a longer list of policies and cantons, I think polling—in a cheap way—could challenge your legislative strategy for cost-effectiveness, at least as a guide for initial research investment.
Fantastic work! In your post introducing this initiative you wrote that the base rate for passage of ballot initiatives was 11%. A conservative reading of the data here (taking the low value of $20m for development funding raised) seems to indicate a 100:1 return on investment. Taking the base rate, this $10 in effective development aid for $1 spent on advocacy (in expectation). If the development aid is effectively spent, the implication here is that money spent on an initiative like this might be ten times as effective in expectation as money donated directly to a top-rated charity. This assumes, of course, that the base rate is accurate.
In that initial post, you had an exchange with Stefan Schubert about the relevance of your assumed base rate. You discussed the importance of polling at that point but it’s not clear to me where you left off.
This success really seems to highlight the importance of public opinion polling here. The value of information in this domain is very high, since you’re trying to identify the avenue which will provide the greatest leverage. Choosing the wrong avenue has no value, and potentially even minor reputational costs for your organization or for EA in general. Choosing the right avenue has huge upsides.
Public opinion polling seems crucial to this end. In this scenario, prior polling might have allowed you to identify a reasonable figure beforehand (avoiding the $87 million overreach). More importantly, though (if I understand the procedure correctly), it might have enabled you to avoid the counterproposal process and to pinpoint an optimal figure to ask for—perhaps one higher than the one you ultimately got.
I don’t want to diminish the achievement here, which I think is huge; I just want to point out that extremely useful information for this effort can be retrieved from the public at relatively low cost. In the future, this information can be used to reduce the uncertainty around efforts to fund ballot proposals and increase the expected value of these efforts by lowering the probability of failure in expectation.
I think that it’s unnecessary to go to such great (and risky) lengths to find out what the public believes with respect to issues relevant to EAs. A well-constructed survey conducted via Mechanical Turk, for example, would (in conjunction with a technique like multilevel regression and poststratification) yield very accurate estimates of public opinion at various arbitrary levels of geographic aggregation. I’d be supportive of this and would be interested in helping to design and/or fund such a survey.
Since I started donating 10% (not very long ago), the only part of my discretionary spending that has taken a hit are my “dumb” expenses: nice new clothes, fancy meals, just overall waste. It turns out that stuff added up to 10%. But YMMV.
If you’re worried, and I think it’s reasonable to be, why don’t you start by pledging 1% and notching it up bit by bit? There’s no need to rush to take the 10% pledge. There is nothing special about that number and you need to figure out what works for you.
Given standard models of rational voter ignorance (and rational irrationality, etc.), this shouldn’t be surprising. Oversimplifying for a moment, the electorate’s middle are in all likelihood systematically mistaken about the sort of policies that would advance their interests; and when you pair these voters with political leaders who are incentivized to pander, we have a recipe for occasional disaster. I see no reason why this wouldn’t occur in a system with approval voting in the same way that it occurs in our current system.
I can think of one reason: rational ignorance is partially a consequence of the voting procedure used. People have less of an incentive to be ignorant when their votes matter more, as they would with approval voting. I don’t have a strong stance on this, but I think it’s important to recognize that studies about voter ignorance are not yielding evidence of an immutable characteristic of citizens; the situation is actually heavily contingent.
In the first few pages of The Myth of the Rational Voter, Bryan Caplan makes (implicitly) the case that voter ignorance isn’t a huge deal as long as errors are symmetric: ignorant voters on both sides of an issue will cancel each other out, and the election will be decided by informed voters who should be on the “right” side, in expectation. Caplan claims that systematic bias across the population results in “wrong” answers.
My point in bringing this up is just that the existence of large numbers of ignorant voters doesn’t have to be a major issue: large elections are decided by relatively small groups. Different voting procedures have very different ramifications for the composition of these small groups.
Thanks for the writeup!
If the recent Bill Gates documentary on Netflix is to be believed, then Gates first became seriously aware of the problem of diarrhea in the developing world thanks to a 1998 column by Nicholas Kristof. It’s hard to assess the counterfactual here (would Gates have encountered the issue in a different context? Would he have taken the steps he ultimately did after reading the Kristof piece?) but it seems plausible that Kristof’s article constitutes a cost-effective intervention in its own right (if a not particularly targeted one).
I bring this up because I’m intrigued by the viral coverage of your clean energy research. It’s not possible to quantify the impact of an article like this in any realistic way, but perhaps we can agree that a plausible distribution of beliefs about its value is close to strictly positive.
Future Perfect being what it is, it’s obviously the case that Vox constitutes an unusually receptive channel for EA-adjacent research. But I’m curious if you consider the wide propagation of your research in the news media a “risky and very effective” project, and if your research products have been intentionally structured toward this end. If you have some takeaways from your big success so far, it could be very helpful to post them here- widely taken-up tweaks to make research propagate more effectively through the media are marginal improvements with potentially very high value.
Thanks for your thoughts. I wasn’t thinking about the submerged part of the EA iceberg (e.g. GWWC membership), and I do feel somewhat less confident in my initial thoughts.
Still, I wonder if you’d countenance a broader version of my initial point- that there is a way of thinking that is not itself explicitly quantitative, but that is nonetheless very common among quantitative types. I’m tempted to call this ‘rationality,’ but it’s not obvious to me that this thinking style is as all-encompassing as what LW-ers, for example, mean when they talk about rationality.
The examples you give of commonsensical versions of expected value and probability are what I’m thinking about here- perhaps the intuitive, informal versions of these concepts are soft prerequisites. This thinking style is not restricted to the formally trained, but it is more common among them (because it’s trained into them). So in my (revised) telling, the thinking style is a prerequisite and explicitly quantitative types are overrepresented in EA simply because they’re more likely to have been exposed to these concepts in either a formal or informal setting.
The reason I think this might be important is that I occasionally have conversations in which these concepts—in the informal sense—seem unfamiliar. “Do what has the best chance of working out” is, in my experience, a surprisingly rare way of conducting everyday business in the world, and some people seem to find it strange and new to think in that fashion. The possible takeaway is that some basic informal groundwork might need to be done to maximize the efficacy of different EA messages.
The EA movement is disproportionately composed of highly logical, analytically minded individuals, often with explicitly quantitative backgrounds. The intuitive-seeming folk explanation for this phenomenon is that that EA, with its focus on rigor and quantification, appeals to people with a certain mindset, and that the relative lack of diversity of thinking styles in the movement is a function of personality type.
I want to reframe this in a way that I think makes a little more sense: the case for an EA perspective is really only made in an analytic, quantitative way. In this sense, having a quantitative mindset is actually a soft prerequisite for “getting” EA, and therefore for getting involved.
I don’t mean to say that only quantitative people can understand the movement, or that there’s something intellectually very special about EAs.
Rather- very few people would disagree that charity should be effective. Even non-utilitarians readily agree that in most contexts we should help as many people as we can. But the essential concepts for understanding the EA perspective are highly unfamiliar to most people.
An awareness of the abilities and limitations of social science
You don’t need to be an expert in any of these areas to “get” EA. You just need to be vaguely comfortable with them in the way that people who have studied microeconomics or analytic philosophy or mathematics are, and most other people aren’t.
This may be a distinction without a difference, but I want to raise the perspective that the composition of the EA movement is less about personality types and more about intellectual preparation.
This part of the discussion really rang true to me, and I want to hear more serious discussion on this topic. To many people outside the community it’s not at all clear what AI research, animal welfare, and global poverty have in common. Whatever corner of the movement they encounter first will guide their perception of EA; this obviously affects their likelihood of participation and the chances of their giving to an effective cause.
We all mostly recognize that EA is a question and not an answer, but the question that ties these topics together itself requires substantial context and explanation for the uninitiated (people who are relatively unused to thinking in a certain way). In addition, entertaining counterintuitive notions is a central part of lots of EA discourse, but many people simply do not accept counterintuitive conclusions as a matter of habit and worldview.
The way the movement is structured now, I fear that large swaths of the population are basically excluded by these obstacles. I think we have a tendency to write these people off. But in the “network” sense, many of these people probably have a lot to contribute in the way of skills, money, and ideas. There’s a lot of value—real value of the kind we like to quantify when we think about big cause areas—lost in failing to include them.
I recognize that EA movement building is an accepted cause area. But I’d like to see our conception of that cause area broaden by a lot— even the EA label is enough to turn people off, and strategies for communication of the EA message to the wider world have severely lagged the professionalization of discourse within the “community.”
I want to caveat the following suggestions with the information that although I have achieved a high degree of success when it comes to getting first-round interviews (>40% response rate), my track record of actually getting the jobs that I want is not particularly high. So take these bullet points as tried-and-true advice on how to get the interview, not on how to get the job (that part is up to you).
Think hard about the UI of your CV.
Your résumé should look really, really good! If you know InDesign, use it. If you don’t, learn it. People who are hiring genuinely and sincerely try not to care about things like this. They still do. It can make a difference.
Tailor your resume to fit the jobs you’re applying to. Do this for every job. This may mean moving your education to the top, highlighting your skills, or front-loading certain accomplishments. Think of your resume as a prior distribution that you’re going to hand to a hiring manager who’s trying to estimate your potential fit for the job: you don’t want to supply every hiring manager with the same prior, since they’re estimating fits for different jobs. You want to maximize the likelihood that you’ll be considered a fit for any given job. Not tailoring your resume is not “more honest” than modifying it to fit the job— it’s just providing hiring managers with an uninformative prior.
Organize and file your past applications
Make a subfolder for each application you do containing the resume and cover letter you used for that application. You should be adjusting your resume and cover letter for each job, but as you apply for more jobs, you’ll be able to simply adjust the materials from similar previous applications. This will reduce friction for you and make you more productive in your application process.
Cold-emailing never hurt anyone
If you’re interested in working somewhere, email them, even if there’s not a job posted. Don’t send them your resume at first. Just say you’re interested, give a sentence or two of background, and ask if there’s some way you can get involved. In the worst case, your email with disappear into the void. Often, though, your email will be treated as a serious indicator of genuine interest when a job is posted. This puts you in a very good position. In the best case, someone will actually set an interview with you (this has happened to me more than once).
Always, always, always follow up after your initial application
This is a no-brainer. It takes ten seconds, demonstrates interest, and brings you to the top of the pile for disorganized hiring managers.
Two anecdotes: (1) I wouldn’t have gotten my first job ever if I hadn’t followed up after submitting my application: their CRM had lost my resume, and they wouldn’t even have known about me if I hadn’t emailed. (2) I recently went through a process where the hiring manager only moved me forward after follow-ups after every stage of the process. I imagine this is a way of weeding out less interested candidates.
Be disciplined about your job search
When you’re looking for a job, you’ll feel like you have to be constantly looking. This is a mistake and will drain your energy. You’ll have a few sites to check once a day. Check them. Then Google around if you have any ideas for finding new jobs to apply to. Don’t do this for more than half an hour a day- you’ll hit negative returns in terms of both your state of mind and opportunity cost. You can instead use that time to...
Make things that show you can do the job
This obviously can’t work everywhere, but for some jobs it will go a long way. I think this has become standard advice in tech and EA, but it’s worth repeating: it takes a big investment to work for free on a project that perhaps no one will see, but the expected return is much higher than that on throwing a CV into the void.
Networking is overrated
Perhaps the only potentially controversial item on this list. People will tell you “it’s who you know.” I think this is true in a limited way: people who you’ve worked with in the past and who are familiar with you in a professional context will, indeed, recommend you, meet with you, think of you for future positions, and occasionally go out on a limb for you. People you have just met will not, generally speaking, do this. They may or may not “pass your resume along” after you grab a coffee with them, but the fact that you barely know them will register with whoever they pass your resume to.
I’ll post a summary lit review here on the forum when I’m done with my research. Spoiler alert: political scientists don’t have a great idea of how/why/whether lobbying works and research on its effectiveness is almost strictly limited to trade policy and large publicly traded firms. So you get expressions of effects like “$140 in additional shareholder value for every $1 spent on lobbying.” Interesting, but not particularly generalizable.
It seems like CES’s strategy so far has been to start small, which makes obvious sense. I’m curious to know when/if you make the decision to withdraw from a local advocacy effort that seems like it’s not paying off. It’s not obvious to me that public support is monotonically increasing in dollars spent on advocacy— what’s your stopping rule?