EA - Centre for Exploratory Altruism Research (CEARCH) by Joel Tan (CEARCH)

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: Centre for Exploratory Altruism Research (CEARCH), published by Joel Tan (CEARCH) on October 18, 2022 on The Effective Altruism Forum. Introduction The Centre for Exploratory Altruism Research (CEARCH) emerged from the 2022 Charity Entrepreneurship Incubation Programme. In a nutshell, we do cause prioritization research, as well as subsequent outreach to update the EA and non-EA communities on our findings. Exploratory Altruism The Problem There are many potential cause areas (e.g. improving global health, or reducing pandemic risk, or addressing long-term population decline), but we may not have identified what the most impactful causes are. This is the result of a lack of systematic cause prioritization research. EA’s three big causes (i.e. global health, animal welfare and AI risk) were not chosen by systematic research, but by historical happenstance (e.g. Peter Singer being a strong supporter of animal rights, or the Future of Humanity Institute influencing the early EA movement in Oxford). Existing cause research is not always fully systematic; for lack of time, it does not always involve (a) searching for as many causes as possible (e.g. more than a thousand) and then (b) researching and evaluating all of them to narrow down to the top causes. The search space for causes is vast, and existing EA research organizations agree that there is room for a new organization. The upshot of insufficient cause prioritization research, and of not knowing the most impactful causes, is that we cannot direct our scarce resources accordingly. Consequently, global welfare is lower and the world worse off than it could be. Our Solution To solve this problem, CEARCH carries out: A comprehensive search for causes. Rigorous cause prioritization research, with (a) shallow research reviews done for all causes, (b) intermediate research reviews for more promising causes, and finally (c) deep research reviews for potential top causes. Reasoning transparency and outreach to allow both the EA and non-EA movement to update on our findings and to support the most impactful causes available. Our Vision We hope to discover a Cause X every three years and significantly increase support for it. Expected Impact If you're interested in the expected impact of exploratory altruism, do take a look at our website (link), where we discuss our theory of change and the evidence base. Charity Entrepreneurship also has a detailed report out on exploratory altruism (link). Team & Partners The current team currently comprises Joel Tan, the founder (link). However, we're looking to hire additional researchers in the near future- do reach out (link) if you're interested in working with us. Do also feel free to get in touch if you wish to discuss cause prioritization research/outreach, provide advice in general, or if you believe CEARCH can help you in any way. Research Methodology Research Process Our research process is iterative: Each cause is subject to an initial shallow research round of one week of desktop research. If the cause's estimated cost-effectiveness is at least one magnitude greater than a GiveWell top charity, it passes to the intermediate research round of two weeks of desktop research and expert interviews. Then, if the cause's estimated cost-effectiveness is still at least one magnitude greater than a GiveWell top charity, it passes to the deep research round of four weeks of desktop research, expert interviews and potential commissioning of surveys and quantitative modelling. The idea behind the threshold is straightforward - research at the shallower level tends to overestimate a cause's cost-effectiveness, so if a cause doesn't appear effective early on, it's probably not going to be a better-than-GiveWell bet, let alone a Cause X magnitudes more important than our current top causes. ...