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.
Writing my summary of Evidence, Decision, and Causality, I got interested in how EDT might be able to succeed by precommitting, and how different simulation schemes that a predictor might run of the transparent Newcomb’s problem might affect the way EDT and CDT reason about the problem. Precommitments hinge on an aspect of sophisticated choice that I haven’t been able to find information on. Indexical (or anthropic) uncertainty seems to do the trick unambiguously. Be warned that these things were probably only new to me, so if you know some decision theory you may end up bored, and I wouldn’t want that.
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.
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.
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.
From 2011 to 2015, I’ve been involved in charity fundraising efforts that raised over $300,000 for several charities. I hope others can draw on some of the experiences documented here to repeat this success. This is the third of three articles and contains my recommendations for anyone who might want to replicate our efforts.
From 2011 to 2015, I’ve been involved in charity fundraising efforts that raised over $300,000 for several charities. I hope others can draw on some of the experiences documented here to repeat this success. This is the second of three articles and gives a detailed account of how we organized specific campaigns.
From 2011 to 2015, I’ve been involved in charity fundraising efforts that raised over $300,000 for several charities. I hope others can draw on some of the experiences documented here to repeat this success. This is the first of three articles and gives a chronological overview of our work.
A quantitative analysis – using Guesstimate – of the harm the North Korean government inflicts on its general population and its prisoner population, and a comparison to the harm from malaria in Mozambique and Angola.
Visualizing distributions of long-lasting insecticide-treated mosquito nets in the epidemiological context. My master’s thesis in computer science at the Department of Computer Science of the Freie Universität Berlin. Please read the PDF version of the thesis as I haven’t fully recreated the formatting in Markdown.
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 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 is my contribution to the EA blogging carnival on cause selection. I compare cause areas and attempt a quantitative comparison between LLIN distributions and advocacy for farmed animals. In short, I will continue to fundraise for the first but but personally donate more to prioritization research within the latter area.
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.
I give an explanation for a phenomenon in the effective altruism community (related to this presentation) that might look like the streetlight effect, propose an idea for a software that might help to further optimize this area, and ask you for your input.
Effective altruism has seen much welcome criticism that has helped it refine its strategies for determining how to reach its goal of doing the most good—but it has also seen some criticism that is fallacious.
Precise Altruism is a service that reads a number of news feeds of effective altruism organizations and general news aggregators, classifies news articles according to their relevance to altruism and effective altruism, and posts matching articles to Tumblr, Twitter, and Facebook under the name of Altrunews.
Effective altruism allows donors to make confident, evidence-based giving decisions that turn even small donations into life-changing events for those in need. (Here’s a recent “Introduction to Effective Altruism” that will hopefully continue to be updated in light of new insights.)
Effective altruism employs rational, evidence-based methods to optimize how effectively we spend our various limited resources on improving the world. (Here’s a recent “Introduction to Effective Altruism” that will hopefully continue to be updated in light of new insights.)
Amber Rose has freshly moved to Canterlot and is eager to start her journalism degree. Little does she know that she is expected by an old acquaintance who has spent years on a time travel spell to eradicate a formative experience from Amber’s past. Amber succumbs and finds herself battling the ghosts of her own adolescence—but life lets her choose again.