Giving Green are welcome to correct me on this (I'm invoking Cunningham's law here) -- the impression I got from their strategy report is "this isn't that straightforward to answer"

• while they don't explicitly define biodiversity loss, let alone use a single quantitative metric like you guessed, they do reference IUCN Red List-based "percent of species threatened with extinction" and David's dominance scores to justify their analytical focus on land use change as the most dominant biodiversity loss driver

• the metrics they looked at for their "problem scale" heuristic for assessing philanthropic strategies are varied:

For land use change, we looked at the surface area of land conversion avoided as a heuristic for scale, while weighing this against the importance of different biomes in terms of ecosystem services. For overfishing, we used heuristics such as the harmfulness and extent of fishing practices and the percentage of fish caught.

• they pragmatically proxied loss reduction by focusing on loss drivers instead, which are the subject of most of the report, as that's where comparative data is available:

Because biodiversity is an inherently multi-dimensional and non-fungible good,
comparing specific impact strategies in terms of scale is methodologically challenging.
For this reason, we prioritized among the five direct drivers of biodiversity loss, for which
quantitative comparisons in scale exist.

• the loss driver indicator they picked, ecosystem services, is focused on the benefits humans derive from ecosystems so my guess to your 2nd question is "probably not", but they did guardrail against strategies potentially harmful to animals, cf. these 2 guiding principles (out of 8 total) they used to identify promising funding opportunities:

Ecosystem services: While there are many indicators for biodiversity, we decided
to focus on ecosystem services as the biodiversity indicator to prioritize. Since
ecosystem services describe the benefits that humans derive from ecosystems,
this definition is closest to Giving Greenʼs mission to maximize human and
ecological well-being. In practice, there are often no concrete quantitative
indicators of ecosystem services for the strategies that we evaluate, so we often
rely on heuristics from other indicators.

Co-benefits for humans and animals: In principle, co-benefits for human health,
development, and animal welfare were not part of our prioritization, but we took
care to not recommend strategies that may cause harm.

• They referenced the Ecosystem Services Valuation Database for the data above, which yields tables like this, caveating that these estimates "are compiled across multiple studies which differ in methods and scope, and therefore should only be seen as a rough indication of the monetary value of different biomes rather than an exact comparison"

Why not just pick number of species going extinct? My guess is the argument across these scattered quotes from Founders Pledge's guide to ecosystem philanthropy, cited in GG's report:

... while biodiversity is a useful measure of an ecosystem’s organizational and structural health, it should not be used as the sole objective to maximize for philanthropists who are interested in the protection of ecosystems more broadly. Intuitively one might argue that conservation should maximize the world’s biodiversity as the abundance and diversity of species are worth protecting. However, using biodiversity as its own metric runs into various issues (see Brennan and Lo 2022 for a further overview). ...

Biodiversity vs wilderness

The focus of protecting and restoring ecosystems is to preserve the natural state of an ecosystem before human interference. This focus on wilderness (or naturalness) often comes in conflict with pure biodiversity maximization. For example, in arid ecosystems, human use can bring about higher biodiversity: a farm built in a desert landscape will provide more habitat for species than the original ecosystem did. Similarly, Brennan (1988) describes temperate forests in which limited land clearing increases the diversity of tree species. A response to this critique might be that, at least among conservation projects, one should choose those that most guard against biodiversity loss. However, even in this limited case, biodiversity is just one consideration among many. Many areas that are regarded as important to conserve, such as many US national parks, are generally lower in biodiversity and instead prized because they are deemed aesthetic or sublime (Sarkar 2005). As such, a primary focus on biodiversity would likely rule out many ecosystems widely deemed important to conserve and could even suggest actions that would go against the preservation of natural ecosystems. Rather, biodiversity should be one consideration among many.

Biodiversity vs Ecosystem Vigor & Services

Many of the most productive ecosystems are not very species-rich. Similarly, the ecosystems that provide the most services for humans are on average lower in biodiversity (such as salt marshes for water filtration). As such, a focus on biodiversity alone might lead to prioritizing ecosystems that are high in different species but are not vibrant in the sense that they contain relatively few ecological processes or provide few services for humans (Brennan and Lo 2022). Biodiversity is therefore best understood as an element of ecosystem health rather than its own metric based on which to prioritize. ...

Heuristics for prioritization

There are various metrics in the conservation field that one might use as heuristics for prioritizing. Biodiversity, the abundance and diversity of species, for example, has intuitive appeal. However, as described above, it often runs counter to other considerations such as wilderness/naturalness and the functioning of ecosystems. Another metric, ecosystem health, provides a more holistic framework to measure the ecological integrity of ecosystems. Prominent models focus on the organization and functional structures of ecosystems and their resilience. As such, they capture a more complete range of ecosystem integrity, and align more closely with the popular notion of “protecting vibrant ecosystems”. Philanthropists should focus on interventions that look at ecosystems holistically, aiming to preserve their structure, functioning, and resilience as opposed to focussing on singular metrics such as biodiversity maximization.

also re: your 2nd question, FP's guide also has a short section on how they're "uncertain about any particular prioritization (of ecosystem protection based on reducing animal suffering) at this point", due to population ethics dilemmas and uncertainty over whether wild animal lives "are on net lives of suffering", and I'm guessing GG's report implicitly adopts this stance.

Lizka's essentials of forum discussion are the closest I know of to something official on this.

Thought to share some infographics on animal advocacy org expenses from the Stray Dog Institute's 2024 State of the Movement report, which I learned about via Moritz's excellent post. 

Most org spending is in North America and Europe: 

North American and European orgs accounted for most of the spend in sub-Saharan Africa and LATAM & the Caribbean, despite spending (say) only ~1% of their total expenses in SSA: 

I don't have any good sense of how this Global North-dominated funding potentially skews priorities, but this drill down by animal category may be a start:

As well as this drill down by intended outcome. Naively it seems that SSA's allocation looks like North America's for instance, except that the latter has a greater proportion of org spending going to increasing availability of animal-free products, which makes sense given relative wealth:

For what it's worth, here's what the funding allocations look like for animal categories as a whole: mostly terrestrial animals, mostly farmed.

I'd be keen to get takes from folks in the know on what seems underfunded here. Farmed insects jump out: just $135k out of $260m overall (~0.05%) seems nuts.

I also wonder about the skewing of priorities due to outside funding. Moritz wrote

Why this could matter:

1. Strategy and local context
   Money shapes movements. It affects which projects get tried, which organisations survive, what gets measured, and what kinds of risks are acceptable. If most capital comes from a different region, that may (subtly, unintentionally) shape priorities and assumptions. Some strategic questions are deeply context-dependent (politics, culture, institutional incentives, reputational dynamics). Local donors may bring different assumptions and highlight different opportunities or overlooked risks.

which I agree with; another angle is Tom & Karthik's point that

• Most farmed animals live in low- and middle-income countries (LMICs), but traditional Western animal advocacy tactics often fail there due to fragmented supply chains, informal markets, and weak enforcement.
• Creating meaningful change for these animals requires exploring both building infrastructure for change and trying alternative pressure points like farmer cooperatives and local institutions.

although it also isn't clear to me from the infographics above whether meaningful change in their sense would be reflected in the drill downs.

My go-to diagram for illustrating your point, from (who else?) Scott Alexander's varieties of argumentative experience:

[Graham’s hierarchy of disagreements] is useful for its intended purpose, but it isn’t really a hierarchy of disagreements. It’s a hierarchy of types of response, within a disagreement. Sometimes things are refutations of other people’s points, but the points should never have been made at all, and refuting them doesn’t help. Sometimes it’s unclear how the argument even connects to the sorts of things that in principle could be proven or refuted.

If we were to classify disagreements themselves – talk about what people are doing when they’re even having an argument – I think it would look something like this:

Most people are either meta-debating – debating whether some parties in the debate are violating norms – or they’re just shaming, trying to push one side of the debate outside the bounds of respectability.

If you can get past that level, you end up discussing facts (blue column on the left) and/or philosophizing about how the argument has to fit together before one side is “right” or “wrong” (red column on the right). Either of these can be anywhere from throwing out a one-line claim and adding “Checkmate, atheists” at the end of it, to cooperating with the other person to try to figure out exactly what considerations are relevant and which sources best resolve them.

If you can get past that level, you run into really high-level disagreements about overall moral systems, or which goods are more valuable than others, or what “freedom” means, or stuff like that. These are basically unresolvable with anything less than a lifetime of philosophical work, but they usually allow mutual understanding and respect.

More on the high-level generators of disagreement (emphasis mine, other than 1st sentence):

High-level generators of disagreement are what remains when everyone understands exactly what’s being argued, and agrees on what all the evidence says, but have vague and hard-to-define reasons for disagreeing anyway. In retrospect, these are probably why the disagreement arose in the first place, with a lot of the more specific points being downstream of them and kind of made-up justifications. These are almost impossible to resolve even in principle. ...

Some of these involve what social signal an action might send; for example, even a just war might have the subtle effect of legitimizing war in people’s minds. Others involve cases where we expect our information to be biased or our analysis to be inaccurate; for example, if past regulations that seemed good have gone wrong, we might expect the next one to go wrong even if we can’t think of arguments against it. Others involve differences in very vague and long-term predictions, like whether it’s reasonable to worry about the government descending into tyranny or anarchy. Others involve fundamentally different moral systems, like if it’s okay to kill someone for a greater good. And the most frustrating involve chaotic and uncomputable situations that have to be solved by metis or phronesis or similar-sounding Greek words, where different people’s Greek words give them different opinions.

You can always try debating these points further. But these sorts of high-level generators are usually formed from hundreds of different cases and can’t easily be simplified or disproven. Maybe the best you can do is share the situations that led to you having the generators you do. Sometimes good art can help.

The high-level generators of disagreement can sound a lot like really bad and stupid arguments from previous levels. “We just have fundamentally different values” can sound a lot like “You’re just an evil person”. “I’ve got a heuristic here based on a lot of other cases I’ve seen” can sound a lot like “I prefer anecdotal evidence to facts”. And “I don’t think we can trust explicit reasoning in an area as fraught as this” can sound a lot like “I hate logic and am going to do whatever my biases say”. If there’s a difference, I think it comes from having gone through all the previous steps – having confirmed that the other person knows as much as you might be intellectual equals who are both equally concerned about doing the moral thing – and realizing that both of you alike are controlled by high-level generators. High-level generators aren’t biases in the sense of mistakes. They’re the strategies everyone uses to guide themselves in uncertain situations.

(also related: Value Differences As Differently Crystallized Metaphysical Heuristics and the previous essays in that series)

Regarding your "something clearly rational here that's kinda unintuitive to get a grip on", I think of it as epistemic learned helplessness as a "social safety valve" to the downside risk of believing persuasive arguments that can (potentially catastrophically) harm the believer, cf. Reason as memetic immune disorder.

There's a lot more to the study of disagreement if you're keen, shame it's mostly just one person working on it and they're busy writing a book nowadays.

I'm not sure what you mean by equalizing the methodologies. FWIW during my RTP we evaluated a few EG orgs using Founders Pledge's approach to diligencing them as a starting point, which seems to bear upon your question: https://www.founderspledge.com/research/giving-multipliers Vasco's 2023 writeup seems to be a start to answering your question too https://forum.effectivealtruism.org/posts/dBdNoSAbkG4k98GT9/evidence-of-effectiveness-and-transparency-of-a-few 

Thanks for the intriguing pushback, part of why I kept bringing this up over the years was to surface this kind of counterargument, upvoted. Flagging for myself later to look into the evidence base behind 

The evidence of "success" he cites only applies to the latter (where "success" is with respect to Brier scores and such), not the former.

because I'd always assumed it was "obviously" the former (wrongly it seems), since the latter seemed non-robust in the sense Dan Luu looked into (cf. "you really have to understand things", which multi-model aggregations are not). 

I've also assumed (2) FWIW.

the marginal giving multiplier could be at or below 1x due to diminishing returns, even while the average was 6x.

In case it helps, the best estimate of GWWC's forward-looking marginal giving multiplier is 10x by CEARCH (exec summary, full report, calcs & sources).

Subscribed :) I agree with your take there that 

Sporting decision makers made better decisions after they got serious about learning from analytical models of their games, models that often began life as blogosphere passion projects. In this front office, we believe that can happen again, one level up: sports themselves as the model for decision makers trying to improve the outcomes that matter most.

Holden used to write about sports too back in the day but stopped in 2021, which was a bummer because I liked his argument to give sports a chance that 

For someone who doesn't care about who wins, what do sports have to offer? High on my list is getting to closely observe people being incredibly (like world-outlier-level) intense about something. I am generally somewhat obsessed with obsession (I think it is a key ingredient in almost every case of someone accomplishing something remarkable). And with sports, you can easily identify which players are in the top-5 in the world at the incredibly competitive things they do; you can safely assume that their level of obsession and competitiveness is beyond what you'll ever be able to wrap your head around; and you can see them in action. ... 

What else is good about sports:

• I think it's fun when people care so deeply about something so intrinsically meaningless. It means we can enjoy their emotional journeys without all the baggage of whether we're endorsing something "good" or "bad." (My wife also loves this about sports - her thing is watching Last Chance U while crying her eyes out.) My next sports post will be a collection of "heartwarming" links and stories.
• There's a lot of sports analysis, and I kind of think sports is to social science what the laboratory is to natural sciences. Sports statistics have high sample sizes, stable environments and are exhaustively captured on video, so it's often possible to actually figure out what's going on. It's therefore unusually easy to form your own judgment about whether someone's analysis is good or bad, and that can have lessons for what patterns to look for on other topics. (My view: academic analysis of sports is often almost unbelievably bad, as you can see from some of the Phil Birnbaum eviscerations, whereas average sportswriting and TV commentating is worse than language can convey. Nerdy but non-academic sports analysis websites like Cleaning the Glass, Football Outsiders and FiveThirtyEight are good.)

the last point of which jives with your blog's thesis.

RoastMyPost by the Quantified Uncertainty Research Institute might be useful for your idea too if you have a gdoc proposal.

Curious to see that poll. I'm in that minority too.

But I do wonder how much the "someone's voice is an extension of them" view is mediated by the privilege of being effortlessly able to articulate one's thoughts in public, especially in a forum that invites scrutiny such as this one, and reliably get positive engagement. You and Brad seem to be on opposite ends of this spectrum (?). Your combination of prolificity, quality, and the fact that you do this despite having an obscenely busy day job reminds me of Scott Alexander, cf. this AMA exchange from back when he was a full-time psychiatrist:

How do you write so quickly? I find it takes me a dozen or more hours to write anything as thorough as one of your blog posts. (It's possible that I'm just unusually slow).

Scott: I guess I don't really understand why it takes so many people so long to write. They seem to be able to talk instantaneously, and writing isn't that different from speech. Why can't they just say what they want to say, but instead of speaking it aloud, write it down?

(Yeah, that level of clear thinking to clear writing translation is an insane privilege.) 

On the other hand Brad's reply to you reminds me of my younger self. I was horrible at this, and worked my rear off for years to get to essentially the starting point of my more innately articulate peers who sailed through job interviews, scholarship interviews etc I kept bombing out of. You can tell how much I care about this by the fact that I could link to a throwaway comment above from deep within the chat threads of an 8-year old reddit AMA by someone mentioning a thing they had that I didn't. I can definitely see younger me being in the majority of your poll.

I think this has to do with the fact that I think mostly nonverbally, which makes the thought to writing / speech translation much harder. I suspect vast swathes of the population are similar. (The wordcel vs rotator thing is related, although I dislike the discourse around it.) This makes us, relatively speaking, voiceless in public fora, so discourse gets dominated by verbal thinkers which skews the intellectual environment and culture.

So when Brad said 

Going back and forth with AI, reviewing, and drafting can turn a writing process that might take several days to a week or more, into an hour or two, or less

I went "yeah definitely for nonverbal-ish thinkers, and I think this has the potential to reduce the skew and improve intellectual variety in discourse and culture, and separately I expect verbal-ish thinkers won't appreciate this benefit" and sure enough your reply confirmed the latter. 

That said, I do mostly agree with you that I haven't been very impressed by the heavily AI-assisted writings I've seen, and like you I really dislike "AI voice", so to me this has been more potential than realised benefit so far. Some guesses:

1. I'm wrong about the above
2. AI isn't good enough yet to properly bridge the translation gap between heavily nonverbal-infused thinking and and writing. (Or it is but people aren't using the paid versions)
3. Nonverbal-ish thinkers just don't reason as clearly as they think they do, and they never noticed this because unlike verbal-ish thinkers they hadn't often translated their thoughts into writing which exposes thinking gaps, and AI-assisted writeups of their half-baked thoughts fill in those gaps with slop
4. The written word isn't the right translation target for nonverbal-ish thinking, it's something else, and (more advanced than today's) AI can potentially assist with this too. I'm thinking of Bret Victor's humane dynamic medium, dangit I should've just quoted these sections instead of subjecting you to my rambling:

What do you mean by “medium”?

A way in which people conceive and share thoughts. An idea might be expressed as a speech, a song, a drawing, a video, an essay, an equation, a tweet... These are different media.

Certain media open up new threads of thought that are otherwise inconceivable. Greek drama was made possible by writing; Shakespearean drama was made possible by print; Newtonian physics was made possible by equations.

The deepest effects are realized when a medium is diffused throughout a culture, not in the hands of a select few. A literate society is one in which all people participate in the exchange of written ideas, where the visual organization of words is second nature in the cultural consciousness. Societies with designated scribes do not enjoy the most significant benefits of literacy.

What do you mean by “dynamic medium”?

The conceiving and sharing of ideas represented computationally.

Computers can be used for efficiently distributing static media, as when reading an article or watching a video. But by “dynamic medium”, we mean the representation of ideas in which computation is essential, by enabling active exploration of implications and possibilities.

The modern world is shaped by vast complex systems — technical systems, environmental systems, societal systems — which cannot be clearly seen nor deeply understood via non-dynamic media. The dynamic medium may enable humanity to grasp and grapple with this century’s most critical ideas.

What do you mean by “humane dynamic medium”?

A dynamic medium which is communal, gives all people full agency, and is part of the real world. [more]

By “communal”, we mean bringing people together in the same physical space, with a medium that supports and strengthens face-to-face interaction, shared hands-on work, tacit knowledge, mutual context, and generally being present in the same reality.

By “agency”, we mean a person’s ability and confidence to view, change, extend, and remake every aspect of a system that they rely on, especially for fluently exploring new ideas and improvising solutions in unique situations. In the case of computing systems, this implies top-to-bottom programmability and composability, in a form that is accessible and human-scale.

By “real world”, we mean that material in the medium physically exists, and all of our human abilities and human senses can be applied to it. People are free to make use of their whole selves, every feature of their physical body and of the physical world, instead of interacting with a simulation through an interface.

“Real world” also refers to being situated in reality — understanding what’s actually happening and how things actually work instead of just abstractions; awareness of larger contexts — and especially the local reality of local needs and local knowledge rather than top-down centralized mass-produced solutions.