Owen Cotton-Barratt of the Global Priorities Project wrote an article on comparing human and animal interventions. His major conclusions include:

1. Indirect long-term effects dominate considerations.
2. Changing behavior of far-future humans matters more than alleviating immediate animal suffering.
3. Helping humans has better flow-through effects than helping non-human animals.

The analysis effectively concludes that helping humans is more important than helping non-human animals but I believe it misses a few important considerations.

(These are fairly quick thoughts about which I have a lot of uncertainty; I’m publishing them here for the sake of making the conversation public.)

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Here are some research topics on cause prioritization that look important and neglected, in no particular order.

1. Look at historical examples of speculative causes (especially ones that were meant to affect the long-ish-term future) that succeeded or failed and examine why.
2. Try to determine how well picking winning companies translates to picking winning charities.
3. In line with 2, consider if there exist simple strategies analogous to value investing that can find good charities.
4. Find plausibly effective biosecurity charities.
5. Develop a rigorous model for comparing the value of existential risk reduction to values spreading.
6. Perform basic analyses of lots of EA-neglected or weird cause areas (e.g. depression, argument mapping, increasing savings, personal productivity–see here) and identify which ones look most promising.
7. Reason about the expected value of the far future.
8. Investigate neglected x-risk and meta charities (FHI, CSER, GPP, etc.).
9. Reason about expected value estimates in general. How accurate are they? Do they tend to be overconfident? How overconfident? Do some things predictably make them more reliable?

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In my recent post on cause selection, I constructed a model where I broke down by category all the charities REG has raised money for and gave each category a weight based on how much good I thought it did. I put a weight of 1 on my favorite object-level charity (MIRI) and gave other categories weights proportional to that. I put GiveWell-recommended charities at a weight of 0.1–that means I’m about indifferent between a donation of $1 to MIRI and $10 to the Against Malaria Foundation (AMF).

Buck criticized my model, claiming that my top charity, MIRI, is more than ten times better than AMF and I’m being too conservative. But I believe that this degree of conservatism is appropriate, and a substantially larger ratio would be epistemically immodest.

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Content note: Proofs involving computation and Turing machines. Whether you understand the halting problem is probably a good predictor of whether this post will make sense to you.

I use the terms “program” and “Turing machine” interchangeably.

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What is consciousness?

We can divide theories about consciousness into three categories:

1. Consciousness is a special non-physical property (dualism).
2. Consciousness is the result of the physical structures of the brain (identity theory).
3. Conscious mental states are the result of their functional role within a process (functionalism).

In particular, I want to talk about Turing machine functionalism, a specific form of functionalism which states that consciousness is computation on a Turing machine. I want to talk about Turing machine functionalism in particular because it is probably correct.

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Disclaimer: I am not a financial advisor. This is not financial advice.

Effective altruists often debate the question of whether to give now or later. One common approach is to give a regular donation each year. This approach makes a lot of sense: here Holden Karnofsky suggests a few reasons why we should give regularly.

But one problem arises with the “give regularly” strategy. If you’re young, and especially if you’re still in school, you probably aren’t earning much money right now, so you can’t donate much. You will earn a lot more money five or ten years from now, which means you’ll also be donating a lot more. If you’re currently a student and you follow the “donate however much I can afford every year” strategy, you end up leaning heavily toward giving more later.

This mirrors the problem described by Ayres and Nalebuff in Lifecycle Investing: if you’re saving for retirement, you end up saving a lot more money later in life. They recommend that most people leverage investments when they’re young and hold more bonds when they’re older in order to spread risk more evenly across their investing lifetimes (or, as they put it, to improve temporal diversification).

We can apply a similar principle to donations. If you don’t earn much now but expect to earn substantially more in the future, you can “leverage” your donations by donating more than you normally would given your income.

It’s not obvious how to do this. There are three basic methods I can see: taking out loans, foregoing savings, and donating trust fund savings. None of these is perfect, but they’re worth considering.

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Cross-posted to the EA Forum. If you want to leave a comment, you can post it there.

Last edited 2015-09-24.

In this essay, I provide my reasoning about the arguments for and against different causes and try to identify which one does the most good. I give some general considerations on cause selection and then lay out a list of causes followed by a list of organizations. I break up considerations on these causes and organizations into five categories: Size of Impact; Strength of Evidence; Tractability; Neglectedness/Room for More Funding; Learning Value. This roughly mirrors the traditional Importance; Tractability; Neglectedness criteria. I identify which cause areas look most promising. Then I examine a list of organizations working in these cause areas and narrow down to a few finalists. In the last section, I directly compare these finalists against each other and identify which organization looks strongest.

You can skip to Conclusions to see summaries of why I prioritize the finalists I chose, why I did not consider any of the other charities as finalists, and my decision about who to fund.

TL;DR

I chose these three finalists:

• Machine Intelligence Research Institute (MIRI) makes the strongest case for an extraordinarily high impact.
• Animal Charity Evaluators (ACE) makes a strong case for high impact and the strongest case for high learning value.
• Raising for Effective Giving (REG) produces a donation multiplier¹ for both MIRI and ACE, so it potentially has an even larger impact.

Based on everything I considered, REG looks like the strongest charity because it produces a large donation multiplier and it directs donations to both MIRI and ACE (as well as other effective charities).

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There are a few cause areas that are plausibly highly effective, but as far as I know, no one is working on them. If there existed a charity working on one of these problems, I might consider donating to it.

Happy Animal Farm

The closest thing we can make to a hedonium shockwave with current technology is a farm of many small animals that are made as happy as possible. Presumably the animals are cared for by people who know a lot about their psychology and welfare and can make sure they’re happy. One plausible species choice is rats, because rats are small (and therefore easy to take care of and don’t consume a lot of resources), definitively sentient, and we have a reasonable idea of how to make them happy.

I am not aware of any public discussion on this subject, so I will perform a quick ad-hoc effectiveness estimate.

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Cross-posted to the EA Forum.

Introduction

Note: When I speak of extinction risk in this essay, it refers not just to complete extinction but to any event that collapses civilization to the point where we cannot achieve highly good outcomes for the far future.

There are two major interventions for shaping the far future: reducing human extinction risk and spreading good values. Although we don’t really know how to reduce human extinction, the problem itself is fairly clear and has seen a lot of discussion among effective altruists. Values spreading is less clear.

A lot of EA activities could be classified as values spreading, but of very different sorts. Meta-organizations like Giving What We Can and Charity Science try to encourage people to value charity more highly; animal charities like The Humane League and Animal Ethics try to get people to assign greater weight to non-human animals. Many supporters of animal welfare interventions believe that these interventions have a large positive effect on the far future via spreading values that cause people to behave in ways that make the world better.

I believe that reducing extinction risk has a higher expected value than spreading good values, and there are a number of concerns with values spreading that make me reluctant to support it. This essay lays out my reasoning.

Personal note: In 2014 I directed my entire donations budget to The Humane League, and in 2015 I directed it to Animal Charity Evaluators. At the time, I generally agreed with the arguments that values spreading is the most important intervention. But recently I have considered this claim more carefully and now I am more skeptical, for the reasons outlined below.

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Cross-posted to the EA Forum.

The cause selection blogging carnival is well under way, and we already have a few submissions. But before the blogging carnival began, some folks had already written some of their thoughts on cause selection. Here I’ve compiled a short list of links to a few such writings supporting a variety of cause areas. Maybe some of these will give you ideas or even convince you to change your mind.

Jeff Kaufman explains why he supports global poverty.

Brian Tomasik discusses where he donates and why.

Topher Hallquist explains why he believes animal rights organizations look most promising.

Luke Muehlhauser claims that AI safety is the most important cause.

GiveWell staff members discuss their personal donations for 2014.