All of cole_haus's Comments + Replies

I hadn't heard that the arbitrage was illegal. Here's a little more info for others: https://www.pymnts.com/cryptocurrency/2022/south-koreas-crypto-kimchi-premium-suspected-in-3-4b-fx-investigation/

Matt Levine suggests that the key problem is accepting your own stock as collateral:

Now let’s add one more crypto element. If you are a crypto exchange, you might issue your own crypto token. FTX issues a token called FTT. The attributes of this token are, like, it entitles you to some discounts and stuff, but the main attribute is that FTX periodically uses a portion of its profits to buy back FTT tokens. This makes FTT kind of like stock in FTX: The higher FTX’s profits are, the higher the price of FTT will be. 8 It is not actually stock in FTX — in f

I haven't had a chance to look at this in detail but it may be interesting at some point to compare this with my earlier attempt: Uncertainty and sensitivity analyses of GiveWell's cost-effectiveness analyses

Note that there have been some independent uncertainty and sensitivity analyses in the past:

Uncertainty and sensitivity analyses of GiveWell's cost-effectiveness analyses (from me)

https://forum.effectivealtruism.org/posts/ycLhq4Bmep8ssr4wR/quantifying-uncertainty-in-givewell-s-givedirectly-cost (from hazelfire)

Also, I think there's a third way that this drawback might not apply

Yeah, I thought about that and meant it to be included (somewhat sloppily) in the "closely aligned" proviso.

Or like shifting your beliefs and arguments in worse ways to match the incentives on the Forum?

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

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.

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. Althou

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

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 operatio

Note that the significant figures conventions are a common way of communicating the precision in a number. e.g. $2.00\times {10}^3$ indicates more precision than $2\times {10}^3$.

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:

1. Solid empirical findings (i.e. widely and repeatedly attested within the field)
2. Falsifiable models with some explanatory depth (i.e. not just mindless curve fitting or a listing of all possib

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

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. t

Thanks for writing this up!

For those interested in more info:

• Harsanyi had two different theorems like this (his aggregation theorem and his impartial observer theorem) which rely on slightly different assumptions.

• 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–Morgenst

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. Thi

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

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:

1. 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.

5. It seems unlikely that household treatment and safe storage systems—with the possible exception of boiling—can be transformative at scale under current

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

This isn't looking at it from exactly the same angle as this post, but Incomplete Contracting and AI Alignment also looks at the alignment problem through the principal-agent lens:

We suggest that the analysis of incomplete contracting developed by law and economics researchers can provide a useful framework for understanding the AI alignment problem and help to generate a systematic approach to finding solutions. We first provide an overview of the incomplete contracting literature and explore parallels between this work and the problem of AI alignment.

I didn't see it among your links, but GiveWell has an interim intervention report on this. Their summary is:

• What is its evidence of effectiveness? Results from multiple randomized controlled trials (RCTs) suggest that distributions of clean cookstoves do not have clear evidence of effectiveness at reducing health problems attributable to air pollution. The evidence we have reviewed in our preliminary investigation finds limited impacts on women’s health and no clear impacts on children’s health under typical use. Distributions of clean cookstoves may hav

I'm also pretty uninformed on the biomarkers aspect. Beyond what they say in the paper:

One reason why we do not find significant effects on biomarkers at conventional levels may be power issues combined with relatively noisy measures. Another, related reason may be the composition of our sample: high levels of pro-inflammatory cytokines have been found for major depression; respondents in our sample, however, report, on average, only mild depressive symptomatology, pre-treatment. In fact, we find that only eight out of 133 respondents (about 6%) report s

trained facilitator

This is how they describe their facilitators:

The course is manualised and scalable: each course is led by two volunteers – screened by Action for Happiness for motivation and skills, and once approved, provided with structured resources – as facilitators on an unpaid basis in their local communities. Recruitment of course leaders follows a carefully documented, standardised process: each candidate completes a Leader Registration process sharing their motivation and skills and is given clear instructions on what is required. Once pot

As far as comparisons, they say:

Impacts on subjective wellbeing, mental health, and pro-sociality are large: the course increases life satisfaction on a zero-to-ten scale by about one point, more than being partnered as opposed to being single (+0.6) or being employed as opposed to being unemployed (+0.7) (Clark et al., 2018). It is more than double the effect of ENHANCE, a 12-week course focusing primarily on positive habits, skills, and attitudes, which is probably the most comparable intervention (Kushlev et al., 2017). 28 However, the authors are abl

Thanks for your thoughts!

Yes, regarding persistence they also note:

To look at treatment effect persistence, we exploit data points at follow-up in an extended sample. As all respondents have been treated at follow-up, we cannot estimate causal effects, so that results are exploratory.

Also just came across this claim in this paper:

In the nationally representative UK Household Longitudinal Survey ("Understanding Society"), for example, average life satisfaction, measured on a scale from one to seven whereby higher values denote higher wellbeing, was not significantly higher in 2016 than in 1996 (5.3 vs. 5.2), despite large rises in real incomes.

Couldn't quickly chase down source data up through 2016--best I could find was this through 2008.

How Poverty Ends: The Many Paths to Progress—and Why They Might Not Continue is from Abhijit V. Banerjee and Esther Duflo (the recent econ Nobel Laureates who won for their RCT work) and I think can reasonably be read as a response to the criticisms of Lant Pritchett (probably the most vocal advocate of the line of thinking this post represents).

Key excerpts:

Economists, ourselves included, have spent entire careers studying development and poverty, and the uncomfortable truth is that the field still doesn’t have a good sense of why some economies expand

Maybe more standing variation and population resilience which could have indirect effects on welfare over the long-term?

I'm struggling to think of non-human-animal-relevant examples of this, but it seems in principle possible to have welfare effects which depend on total population rather than density. Ideas and technological innovation are (roughly) an example of this in humans. That is, more total humans means more freely shareable ideas/innovations means more welfare. (See e.g. Population growth and technological change: One million BC to 1990.)

Thought I'd just throw it out there in case someone can think of a way to make this relevant to animals.

Some related things that come to mind:

• Challenges to Bayesian Confirmation Theory outlines some conceptual potential issues arising from the use of explicit probabilities in a Bayesian framework.
• Gerd Gigerenzer likes to claim that "fast and frugal" heuristics often just perform better than more formal, quantitative models. These claims can be linked to the bias-variance tradeoff and extreme priors.
• The optimizer's curse can be generalized to the satisficer's curse. This generalization doesn't obviously seem to differentially affect explicit probabilities

Having looked at the paper now, I definitely have a different take as to how definitive it is. My maximally contrarian take would be that it's a non-systematic review in which many (most?) of the works reviewed are in favor of an important causal link running from health to income. I do agree that the overall macro-scale evidence is weak (which is distinct from strong evidence of a weak effect), but this is exactly why people like RCTs over national development! Causal inference at a macro scale is hard!

(Health and Economic Growth: Reconciling the Micro an

It's not binary, though.

Yup, agreed.

The link I was thinking of is that migration loans are relevant for urbanization, agglomeration effects, and generally the distribution and density of humans (which seem like they fit into human geography--"Human geography attends to human patterns of social interaction, as well as spatial level interdependencies"--and urban geography).

Deworming doesn't change the geography of a place in itself but it mediates the impact of that geography on humans/the economy/society (supposing that we consider the disease environment a part of geography similar to the wa

The Easterlin paradox notwithstanding, economic growth does buy you a lot of subjective wellbeing improvement in a country.

I might not be understanding you, but it seems like this tries to smuggle in causation and assume away the problem. As I see things, there are two conflicting pieces of correlational evidence:

• Cross-country regressions show strong correlation at a point in time between income and SWB (what the post highlights)
• Time series regressions within countries show a weak correlation between income and SWB (Easterlin paradox)

I don't curren

I updated in the direction that health and education are not that important for growth at least for very poor countries

Yeah, I will have to look into this perspective more.

But it's a different question on whether we can do anything about that by ramping up health spending and ameliorate these differences and whether that's important for growth.

I do think it's an open question though.

Yup, agreed that none of the linked things are on growth per se. I just think the link to the systemic change objection is useful because it gives hints as to what problems there might be with the growth-focus argument, how people are likely to react to the growth-focus argument, which arguments are persuasive, etc.

Yup, agree that the argument I outline is not definitive and thoughtful work in this area is worthwhile. I think I may be more pessimistic on the politics aspect (i.e. I may think it's a more tightly-binding constraint and harder for outsiders to work on), but my sense of that is kind of inchoate and not worth much at the moment.

not really understanding how ordinal moral theories are really meant to work

Yeah, I think this is where I'm at too. It seems inescapable that ordinal preferences have cardinal implications when combined with empirical uncertainty (e.g. if I prefer a 20% chance of A to an 80% chance of B, that implies I like A at least four times as much). The only choice we really have is whether the corresponding cardinal implications are well-formed (e.g. Dutch bookable). The best distinctions I can come up with are:

• In a purely deterministic world without lotteries,

China’s growth acceleration from 1977 onwards produced $14 trillion NPV in cumulative economic output. Thus, if the only thing the economics profession achieved in 50 years was to increase by 4 percentage points the probability that the Chinese government shifted to this new economic strategy, then it would have had greater economic benefits than the Graduation approach.

I think this argument equivocates between the probability of any reform and the probability of a particular reform. Because the reform policy was academic-economist-inflected, denying th

Here's a central argument against focusing on growth per se that I find fairly plausible:

Obviously terrible growth-related policies are at historic lows. Our ability to produce more detailed/refined policy prescriptions is weak (see Pritchett's acknowledgement of the lost decades and the transition depression). In fact, many of the greatest successes of development (China, Singapore, etc.) defied the economic orthodoxy in the details. Rather, they implemented policies that were tailored to and required deep understanding of local conditions. The key barrie

Wild speculation:

I think one reason this area may get less attention in EA is that if you're willing to sign up for high-risk high-return scenarios that are more theory-driven and less retrospective-data-driven (like economic growth), you're also more sympathetic to long-termist areas like x-risk. And once you're comparing x-risk to economic growth, there's no guarantee that growth wins.

In other words, I think economic growth may be competing against x-risk--not RCTs--among EAs.

(Though certain ethical views may argue against long-termist interventions like

RD has moved in an entirely different direction. Instead of replicating this success, it asks: among interventions that we can test with RCTs, what is most impactful? In the wake of the period with by far the greatest progress in human welfare of all time, this change in strategy is difficult to justify.

I think one possible explanation (I've not heard this anywhere explicitly; it's just me making things up.) that I find moderately persuasive is:

Development RCTs rose to prominence in the wake of the '“lost decades” in Latin America and the “transition de

This should lead us to be sceptical about RD. Growth is arguably the major driver of human progress, but proponents of RD rarely argue that the interventions that they recommend do increase growth.

To the extent that this is true, I think there are pretty benign possible explanations:

• The data on growth (e.g. GDP) and RD interventions typically operate at different scales. Even if GiveDirectly substantially increases the long-term growth in a village, that's not going to show up in national aggregate data.
• Making empirical growth claims requires data a

Thus, many RCT-backed interventions do not seem to explain much of the cross-national variation in GDP per capita. What does? There are a range of factors including:

• Growth-friendly policies
• Geography
• Natural resources
• Human capital
• Culture

I'm confused here. It seems like there are examples of RCTs addressing at least:

• Geography: It seems like No Lean Season, Duflo's fertilizer nudges, and deworming (edit: I try to make the link between these and geography more obvious in a grandchild comment.) are all examples of RCTs targeting various aspects of

The reason these things are unlikely to be the best way to increase growth is that they play no role in the causal story of the huge differences in GDP per capita across space and time.

...

But given the story above, it would be very surprising if this was the case: differences in rates of deworming explain a miniscule fraction of the variation in individual economic outcomes across the world. No-one argues that deworming is among the top 1000 causes of the huge economic transformation documented above.

These seem like clearly insufficient arguments.