EA - Reasoning Transparency by Lizka

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: Reasoning Transparency, published by Lizka on September 28, 2022 on The Effective Altruism Forum. I think “reasoning transparency” (and/or epistemic legibility) is a key value of effective altruism. As far as I can tell, the key piece of writing about it is this Open Philanthropy blog post by Luke Muehlhauser, which I’m cross-posting it to the Forum with permission. We also have a topic page for "reasoning transparency" — you can see some related posts there. Published: December 01, 2017 | by Luke Muehlhauser We at the Open Philanthropy Project value analyses which exhibit strong “reasoning transparency.” This document explains what we mean by “reasoning transparency,” and provides some tips for how to efficiently write documents that exhibit greater reasoning transparency than is standard in many domains. In short, our top recommendations are to: Open with a linked summary of key takeaways. [more] Throughout a document, indicate which considerations are most important to your key takeaways. [more] Throughout a document, indicate how confident you are in major claims, and what support you have for them. [more] 1 Motivation When reading an analysis — e.g. a scientific paper, or some other collection of arguments and evidence for some conclusions — we want to know: “How should I update my view in response to this?” In particular, we want to know things like: Has the author presented a fair or biased presentation of evidence and arguments on this topic? How much expertise does the author have in this area? How trustworthy is the author in general? What are their biases and conflicts of interest? What was the research process that led to this analysis? What shortcuts were taken? What rough level of confidence does the author have in each of their substantive claims? What support does the author think they have for each of their substantive claims? What does the author think are the most important takeaways, and what could change the author’s mind about those takeaways? If the analysis includes some data analysis, how were the data collected, which analyses were done, and can I access the data myself? Many scientific communication norms are aimed at making it easier for a reader to answer questions like these, e.g. norms for ‘related literature’ sections and ‘methods’ sections, open data and code, reporting standards, pre-registration, conflict of interest statements, and so on. In other ways, typical scientific communication norms lack some aspects of reasoning transparency that we value. For example, many scientific papers say little about roughly how confident the authors are in different claims throughout the paper, or they might cite a series of papers (or even entire books!) in support of specific claims without giving any page numbers. Below, I (Luke Muehlhauser) offer some tips for how to write analyses that (I suspect, and in my experience) make it easier for the reader to answer the question, “How should I update my views in response to this?” 2 Example of GiveWell charity reviews I’ll use a GiveWell charity review to illustrate a relatively “extreme” model of reasoning transparency, one that is probably more costly than it’s worth for most analysts. Later, I’ll give some tips for how to improve an analysis’ reasoning transparency without paying as high a cost for it as GiveWell does. Consider GiveWell’s review of Against Malaria Foundation (AMF). This review. .includes a summary of the most important points of the review, each linked to a longer section that elaborates those points and the evidence for them in some detail. .provides detailed responses to major questions that bear on the likely cost-effectiveness of marginal donations to AMF, e.g. “Are LLINs targeted at people who do not already have them?”, “Do LLINs reach intended destinations?”, “Is there roo...