This maybe could be assimilated under “opportunity cost”, but I think a major potential downside is skewed incentives. To avoid that drawback you’d either have to believe that posters mostly aren’t influenced by the mechanics of the Forum or that the mechanics of the Forum are closely aligned with the good.
cole_haus
Karma: 1,087
Nondogmatic Social Discounting seems very loosely related. Could be an entry point for further investigations, references, etc.
The long-run social discount rate has an enormous effect on the value of climate mitigation, infrastructure projects, and other long-term public policies. Its value is however highly contested, in part because of normative disagreements about social time preferences. I develop a theory of “nondogmatic” social planners, who are insecure in their current normative judgments and entertain the possibility that they may change. Although each nondogmatic planner advocates an idiosyncratic theory of intertemporal social welfare, all such planners agree on the long-run social discount rate. Nondogmatism thus goes some way toward resolving normative disagreements, especially for long-term public projects.
I think this post unhelpfully mixes general, systemic criticisms around innovation, public goods and IP (which I’m very interested in and sympathetic to) with the “news hook”—COVID vaccines. It strikes me as incredibly unlikely that we’ll determine and shift to a better solution in the current crisis. I think the most likely outcome of action here would be to shift us out of the local maximum but not into the global maximum. I think a proposal of an alternative system, an analysis of its cost and benefits relative to the status quo , and a plan for how to get there from here would receive a very different reception.
On Scientific Trust, Loose Summaries, and Henrich’s WEIRDest People in the World has some useful comments on the accuracy of the book.
Somewhat related:
The Limitations of Decentralized World Redistribution: An Optimal Taxation Approach
A centralized scheme of world redistribution that maximizes a border-neutral social welfare function, subject to the disincentive effects it would create, generates a drastic reduction in world consumption inequality, dropping the Gini coefficient from 0.69 to 0.25. In contrast, an optimal decentralized (i.e., with no cross-country transfers) redistribution has a miniscule effect on world income inequality. Thus, the traditional public finance concern about the excess burden of redistribution cannot explain why there is so little world redistribution.
Actual foreign aid is vastly lower than the transfers under the simulated world income tax, suggesting that voluntary world transfers—subject to a free-rider problem—produces an outcome that is consistent with rich countries such as the United States either placing a much lower value on the welfare of foreigners, or else expecting that a very significant fraction of cross-border transfers is wasted. The product of the welfare weight and one minus the share of transfers that are wasted constitutes the implicit weight that the United States assigns to foreigners. We calculate that value to be as low as 1/2000 of the value put on the welfare of an American, suggesting that U.S. policy is consistent with social preferences that place essentially no value on the welfare of the citizens of the poorest countries, or that implicitly assumes that essentially all transfers are wasted.
I know one of the examples I’ve heard of is neoliberalism and the Mont Pelerin society. You may be able to use that as a case study.
From Optimizing Engagement to Measuring Value is interesting and somewhat related:
Most recommendation engines today are based on predicting user engagement, e.g. predicting whether a user will click on an item or not. However, there is potentially a large gap between engagement signals and a desired notion of “value” that is worth optimizing for. We use the framework of measurement theory to (a) confront the designer with a normative question about what the designer values, (b) provide a general latent variable model approach that can be used to operationalize the target construct and directly optimize for it, and (c) guide the designer in evaluating and revising their operationalization. We implement our approach on the Twitter platform on millions of users. In line with established approaches to assessing the validity of measurements, we perform a qualitative evaluation of how well our model captures a desired notion of “value”.
Note that the significant figures conventions are a common way of communicating the precision in a number. e.g. indicates more precision than .
In addition to Will MacAskill’s critique of functional decision theory (MIRI-originated and intended to be relevant for AI alignment), there’s this write-up by someone that refereed FDT’s submission to a philosophy journal:
My recommendation was to accept resubmission with major revisions, but since the article had already undergone a previous round of revisions and still had serious problems, the editors (understandably) decided to reject it. I normally don’t publish my referee reports, but this time I’ll make an exception because the authors are well-known figures from outside academia, and I want to explain why their account has a hard time gaining traction in academic philosophy.
I just feel like it’s hard to come away with much of long-term value. I sort of nod along as I read thinking, “That’s plausible,” and that’s about it. (To be concrete: I make Anki cards for most nonfiction I read and I’ve only made around 1o or 12 across 200 pages which is way fewer than normal for me.) I think I generally want my non-fiction to have at least one of:
Solid empirical findings (i.e. widely and repeatedly attested within the field)
Falsifiable models with some explanatory depth (i.e. not just mindless curve fitting or a listing of all possible causal factors)
Insightful conceptual analysis (e.g. mutually exclusive and collectively exhaustive taxonomies)
Regarding 1, several empirical studies are mentioned but they don’t seem to add up to a coherent or even non-contradictory whole.
There’s basically none of 2.
The book is probably closest to achieving number 3, but still not great. I would have liked, for example, if they talked about why the classic agenda of “collective action frames”, “mobilizing structures”, and “political opportunities” is a better organizational scheme than the alternatives.
The book also focuses more on apportioning credit and on the history of the thinking in the field than I’d prefer.
All that said, I understand different readers are looking for different things.
I remain pretty confused by this line of argument. I basically parse it as: we should strive to make the actions of developing countries similar to the (best) actions of developed countries. But actions seem of merely instrumental interest and what we actually care about is states (conditions) that are conducive to development.
The recommendations from these two perspectives (actions vs states) converge only insofar as the best actions are invariant across states. But this is quite a big claim and contradicted by e.g. Rodrik who insists that “Institutional innovations do not travel well”.
It seems like the development interventions we commonly see can be readily justified by the state-based view. For example, no, we didn’t see widespread deployment of insecticidal nets in the US, but, yes, we did see deliberate effort to achieve and good returns from achieving a low burden of infectious disease in the US. No, we didn’t have women’s self-help groups, but, yes, we did achieve a state of increased gender equality and of increased integration of women into the formal economy.
TL;DR: Why would we expect the same actions to produce the same end state given different starting states?
Another book in this area is Handbook of Social Movements Across Disciplines. Unfortunately, I’m most of the way through and it’s a bit underwhelming.
Here’s a half-baked argument for natalism vis-à-vis climate change:
Carbon emissions in the highly developed countries most EAs live in are generally trending in the right direction (i.e. there seems to be at least relative decoupling between emissions and consumption). The bulk of emissions growth over the next several decades will be in other large, rapidly developing countries like India and China. Green technology transfer is a way that highly developed countries can positively influence emissions in the critical rapidly developing countries (see e.g. this). Economic models generally propose that a larger population generates more ideas and a higher rate of technological change (e.g. Population Growth and Technological Change: One Million B.C. to 1990). Therefore, the (smallish?) direct impact of increased emissions from greater population in highly developed countries might be outweighed by more green technology and technology transfer to the crucial rapidly developing countries like China and India.
Thanks for writing this up!
For those interested in more info:
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Harsanyi had two different theorems like this (his aggregation theorem and his impartial observer theorem) which rely on slightly different assumptions.
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The main arguments against Harsanyi’s theorems were made by prominent economist Amartya Sen in what has become known as the “Harsanyi-Sen debate” or “Harsanyi-Sen-Weymark debate” (searchable terms). The gist of the counterargument is that “while Harsanyi has perhaps shown that overall good is a linear sum of individuals’ von Neumann–Morgenstern utilities, he has done nothing to establish any connection between the notion of von Neumann–Morgenstern utility and that of well-being, and hence that utilitarianism does not follow.”.
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Chloramphenicol is an approved drug, but not approved for this purpose. Approving Chloramphenicol as a coronary treatment requires human trials that will probably cost $25 million.
I am extremely far from an expert here so there may be some subtlety, but off-label uses are generally possible. From Wikipedia:
However, once a drug has been approved for sale for one purpose, physicians are free to prescribe it for any other purpose that in their professional judgment is both safe and effective, and are not limited to official, FDA-approved indications. This off-label prescribing is most commonly done with older, generic medications that have found new uses but have not had the formal (and often costly) applications and studies required by the FDA to formally approve the drug for these new indications.
Edit: The full post at the link acknowledges this:
As an approved drug (though for another purpose) any doctor can prescribe Chloramphenicol for any purpose. Of course, they don’t know to do this. And — perhaps more importantly — such bold action can get American doctors sued for malpractice.
I just finished reading Democracy for Realists recently which argues that:
They demonstrate that voters—even those who are well informed and politically engaged—mostly choose parties and candidates on the basis of social identities and partisan loyalties, not political issues. They also show that voters adjust their policy views and even their perceptions of basic matters of fact to match those loyalties. When parties are roughly evenly matched, elections often turn on irrelevant or misleading considerations such as economic spurts or downturns beyond the incumbents’ control; the outcomes are essentially random. [...]
Achen and Bartels argue that democratic theory needs to be founded on identity groups and political parties, not on the preferences of individual voters.
I’m not fully settled on how much weight to give to this perspective, but I think it’s important to remember the empirical facts of voting as it happens in the real world and not just the idealizations of social choice theory. Presumably this leads to a quite different notion of the optimal electoral system and the optimal series of electoral reforms.
(This isn’t meant to say that the social choice theory perspective and the points brought up in this post are unimportant. I just thought it was an interesting book and a good reminder to look at this whole other set of criteria.)
A few of the summary points in Safe Drinking Water for Low-Income Regions are interesting and may provide reason for a bit of pessimism:
Safe drinking water from “source to sip” consists of a series of interactions between technologies, their delivery models, their scales and costs of production, and consumer uptake and consistent use. Safe drinking water is a system, not a product or an intervention.
It seems unlikely that household treatment and safe storage systems—with the possible exception of boiling—can be transformative at scale under current prices, delivery models, and preferences, but they are effective and protective in specific contexts.
Cost analyses for “low-cost” systems are usually reported on a partial basis, with installation costs and some operational costs included. The enabling costs of social marketing, mobilization, education, reminders, and community- or household-based unpaid labor are mentioned but not explicitly accounted for.
Delivery models and business models significantly affect costs and uptake, at all three scales of service. Yet they are rarely made explicit.
Safe water systems can be highly effective, but consumers undervalue drinking water quality and have low willingness and/or ability to pay for safety. This is a particular challenge for arsenic mitigation or avoidance, as arsenicosis is only evident after several years of exposure.
Without an in-depth of understanding of either deworming or WASH, it seems like the implementation issues for WASH may be more severe?
This doesn’t directly engage with the point of this post, but Safe Drinking Water for Low-Income Regions is a pretty good introduction to WASH IMO:
Well into the 21st century, safe and affordable drinking water remains an unmet human need. At least 1.8 billion people are potentially exposed to microbial contamination, and close to 140 million people are potentially exposed to unsafe levels of arsenic. Many new technologies, water quality assessments, health impact assessments, cost studies, and user preference studies have emerged in the past 20 years to further the laudable goal of safe drinking water for all. This article reviews (a) the current literature on safe water approaches with respect to their effectiveness in improving water quality and protectiveness in improving human health, (b) new work on the uptake and use of safe water systems among low-income consumers, (c) new research on the cash and labor costs of safe water systems, and (d) research on user preferences and valuations for safe water. Our main recommendation is that safe water from “source to sip” should be seen as a system; this entire system, rather than a discrete intervention, should be the object of analysis for technical, economic, and health assessments.
(Providing Safe Water: Evidence from Randomized Evaluations too.)
Yeah, I thought about that and meant it to be included (somewhat sloppily) in the “closely aligned” proviso.
Or shifting your attention.
I think things like upvotes and comments here provide multiple incentive gradients which seem possibly harmful. For example, I think based on a vague gestalt impression that the Forum tends to:
Encourage confidence and simplicity over nuance at some margin less than the IMO optimal
Disproportionately reward critiques and “drama” of a certain sort
Discourage highly technical content
Encourage familiar content and content areas
Many of these claimed problems are very understandable and seem hard to avoid in this kind of setting. People like things they’re familiar with (looseley: https://en.wikipedia.org/wiki/Mere-exposure_effect); understanding and evaluating highly technical content either demands more time from readers or outright limits the audience size; if you don’t have the expertise to evaluate and contextualize claims, confident claims seems more informative than cautious ones; etc.
Obviously, my claims here are pretty subjective and fuzzy and others could disagree.