There is no qualitative distinction between investors and retroactive funders on an impact market. Rather they will de facto fall along a spectrum of how altruistic they are. That is because investors will (1) expect investments into well-defined prize contests to be less risky than fully speculative investments, and will (2) expect more time to pass before they can exit fully speculative investments, so that a counterfactual riskless benchmark investment represents a higher threshold for them to consider impact markets at all.

We want to create a market to trade “impact certificates” – a variation on social impact bonds.

SquigglyPy uses sampling to allow you to do math with arbitrary probability distributions in two dimensions – e.g., you can plot a thousand traces of how economic growth might pan out over the next couple of millions of years.

I’ve asked the titular question in the EA Forum. I also posted some answers of my own from the get go, but other people added more, and I, too, posted another answer later. You can find all answers in the EA Forum. (I’ve reproduced my question and my initial answers here.)

Some programs, platforms, apps, extensions, services, lifehacks, etc. that I’ve found useful.

Arif Ahmed’s Evidence, Decision, and Causality (2014) is a dense, mathematical book-length argument against causalism and for the merits of evidential over causal decision theory. It’s not a light read, so I decided that others, including future me, may benefit from a short, informal summary. I think this summary will be most interesting for people who are new to decision theory. The subsection “EDT Money Pump” may be more generally interesting, unless I’m wrong.

Some of the people on earth who are most similar to you are likely your own person moments from other points in time. Your degree of similarity to them informs (though I haven’t worked out how) what the density is of you-like computation in the universe. This question is interesting for evidential cooperation as I hope that it can help to disentangle evidential cooperation from infinite ethics. Here I tested how similar my decisions in the board game Othello are today compared to 2015. The result was that I chose the same move in 57% of positions for a peculiarity of 0.41 (explained below). The 2015 move was among the 2020 plausible moves in 76% of positions for a plausibility of 0.52 (explained below).

Over the past three years, I’ve collected some 60-odd questions that I now finally have the time to investigate further. I summarize some of them here. This post may be helpful for you if you want to snatch one of these from me and investigate it yourself and helpful for me if you have pointers for any of them.

These are some rather introspective worries of mine to the effect that the longtermist community may be missing out on people with a particular knack for finding counterexamples.

In this article I summarize my current thinking on how I want to make my actions robustly positive on a normative level by choosing the moral goals to focus on according to cooperativeness heuristics on five levels.

Prepared opportunism may be a neglected strategy in effective altruism.

I pose the question whether we’re again building too much momentum toward what we think is best and thereby erode our ability to react to new insights and adjust our strategy.

This article documents my current thoughts on how to make the most out of my experiment with earning to give. It draws together a number of texts by other authors that have influenced my thinking and adds some more ideas of my own for a bundle of heuristics that I currently use to make donation decisions. I hope the article will make my thinking easier to critique, will help people make prioritization decisions, will inspire further research into the phenomena that puzzle me, and will allow people to link the right books or papers to me.

The suffering that the North Korean regime inflicts on its citizens is a lesser source of suffering than malaria worldwide (but not compared to individual highly malarial countries of similar population as North Korea) or industrial agriculture in US states of similar population. However, it may be on par or even exceed that inflicted on the US American prison population, a cause prioritized by the Open Philanthropy Project. There are risky but promising interventions, which could be scaled up if more funding were available. The cause area seems well suited for hits-based giving by major donors looking for funding gaps. The government change in South Korea of May 9, 2017, may further increase the marginal utility of funding.

A year or two ago, I first noticed that the way I thought about impact, who causes it, and what replaceability meant did not quite make sense. These concerns lead first to my article “The Attribution Moloch” and now to this one, an addendum of sorts. Here, I will introduce several considerations that should lead us to value preparatory work – in particular research – higher or even higher than we already do.

I converted Brian Tomasik’s How Much Direct Suffering Is Caused by Various Animal Foods? to Guesstimate. We now have ranges, distributions, and the sensitivity analysis to draw on to refine the estimates. I also added two columns to determine the suffering of the average per capita consumption, which seems to me like the more intuitive figure; refined the estimates with additional research; and added organic eggs for comparison.

I present a rather speculative argument whose most likely implication is that if we’re in a simulation, then the root is occupied by a superintelligence, and probably not a value-aligned one. If you’re new to the topic, this is probably not a good introduction, since I mostly wrote it for myself so not to forget it all. I recommend Nick Bostrom’s Superintelligence instead.

I argue that sufficient resource scarcity can exacerbate the effects of tiny differences in value alignment to the point where charities with almost identical goals will compete rather than cooperate. Further, a skewed perception of how impact is created as well as mere ignorance can cause prioritization to aggravate failures of coordination.

Brian Tomasik has written about the Gains from Trade through Compromise. In practice I have repeatedly been in a position where I needed to refer back to specific scenarios discussed throughout the essay, so I resolved to categorize and number them and give them names. The result is an attempt at a taxonomy of modes of values spreading.

This is a proposal for a donor coordination system that aims to empower donors to harness the risk neutrality that stems from their combined work toward agent-neutral goals.

This article argues that donor coordination is even more important than we already thought because it is a more efficient way to bridge the recommendation gap I described in the context of expected utility auctions.

This article reports the results of an online survey with 167 respondents on the influence different styles of effective altruism outreach have on them. While we could not find evidence for our hypotheses, the exploratory data analysis yielded a ranking of the levels of motivation and curiosity our prompts induced.

Some people do not lack in altruism and are well aware of effectiveness considerations too, but the sheer magnitude of suffering that effective interventions would force them to face is too unbearable for them to acknowledge. I give tips on how they can use dissociation to put altruism on a more scalable basis.