EA - Replace Neglectedness by Indra Gesink

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Replace Neglectedness, published by Indra Gesink on January 16, 2023 on The Effective Altruism Forum.for example with Leverage, as featured in Will MacAskill’s What We Owe the Future.The second bullet point featured in the website introduction to effective altruism is the ITN framework. This exists to prioritize problems. The framework does so by considering the Importance — or scale, S — of a problem, as the number of people or quality-adjusted life years (QALYs) affected, multiplied with the Tractability, as the potential that this problem can be addressed, and Neglectedness, as the number of people already working to address this problem (ITN-framework, including Leverage). Tractibility is sometimes also called Solvability, and non-neglectedness crowdedness.Some criticisms and difficulties in interpreting the framework (1, 2, 3, 4) have preceded this forum post. The ITN framework can be interpreted - as also in the final paragraph of (1) - such that IT represents the potential that a problem can be addressed, while ITN considers the difference that any one individual can make to that problem, particularly the next individual. How much impact can the next individual make, choosing to work on this problem, on average? Why do I add “on average”? We are still ignoring the person’s unique qualities, and instead more abstractly consider an average person. Adding “personal fit” as another multiplicative factor would make it personal as well.So “How much impact can the next individual make on this problem?” really asks for the marginal counterfactual impact. Respectively this is the amount of impact that this one individual adds to the total impact so far, which would not happen otherwise. The ITN-factor Neglectedness assumes that this marginal counterfactual impact is declining — strictly — as more individuals join the endeavor of addressing the particular problem. If this is true, then — indeed — a more neglected problem ceteris paribus — i.e. not varying factors I, T (or personal fit) simultaneously — always yields more impact when fewer individuals are already addressing it. This is however not always true, as also already pointed out in the criticisms referenced above.Consider the following string of examples. Suppose a partial civilizational collapse has occurred, and you consider whether it would be good to go and repopulate the now barren lands. The ITN-framework says that as the first person to do so you make the biggest difference. However, alone you cannot procreate, at least not without far-reaching technological assistance. In fact a sizable group of people deciding to do so might very well still be ineffective, by not bringing in sufficient genetic diversity. This is captured by a well-known term in population biology: the critical or minimally viable population size (to persist). Something similar operates to a lesser extent in the effectiveness of teams. I for example once found the advice to better not join a company as the sole data scientist, as you would not have a team to exchange ideas with. Working together, you become more effective, and develop more.Advocating for policies is another area that is important and where you need teams. Consider there being multiple equally worthwhile causes to protest for, but by the logic of the ITN-framework you always join the least populated protest. And no critical mass is obtained. Doesn’t that seem absurd? See also (5). (And the third image in (3), depicting a one-time significant increase in marginal counterfactual impact, as with a critical vote to establish a majority. This graph is also called an indicator function). Effective altruists might similarly often find themselves advocating for policies which are neglected and that are thus not well known to the recipient of such advocacy. As opposed to max...