First, we argue that the appeal of effective altruism (henceforth, EA) depends significantly on a certain empirical premise we call the Heavy Tail Hypothesis (HTH), which characterizes the probability distribution of opportunities for doing good. Roughly, the HTH implies that the best causes, interventions, or charities produce orders of magnitude greater good than the average ones, constituting a substantial portion of the total amount of good caused by altruistic interventions. Next, we canvas…
Read moreFirst, we argue that the appeal of effective altruism (henceforth, EA) depends significantly on a certain empirical premise we call the Heavy Tail Hypothesis (HTH), which characterizes the probability distribution of opportunities for doing good. Roughly, the HTH implies that the best causes, interventions, or charities produce orders of magnitude greater good than the average ones, constituting a substantial portion of the total amount of good caused by altruistic interventions. Next, we canvass arguments EAs have given for the existence of a positive (or “right”) heavy tail and argue that they can also apply in support of a negative (or “left”) heavy tail where counterproductive interventions do orders of magnitude more harm than ineffective or moderately harmful ones. Incorporating the other heavy tail of the distribution has important implications for the core activities of EA: effectiveness research, cause prioritization, and the assessment of altruistic interventions. It also informs the debate surrounding the institutional critique of EA.
