This is a special post for quick takes by tyleralterman. Only they can create top-level comments. Comments here also appear on the Quick Takes page and All Posts page.
Sorted by Click to highlight new quick takes since:

Apropos of the "Criticism and Red Teaming Contest," I am curious about how critiques have historically shaped EA:

a. What critiques have resulted in large and tangible changes in the movement?

b. What were the means by which these critiques were "metabolized?" Eg did they require a prestigious champion? Was there a highly shared article that changed people's minds? etc

I have no proof it mattered, but a few years before the big pivot to longtermism, 80k debated some leftists who emphasised the sheer scope of systemic change and measurability bias. And we moved.

Curated and popular this week
 ·  · 11m read
 · 
Does a food carbon tax increase animal deaths and/or the total time of suffering of cows, pigs, chickens, and fish? Theoretically, this is possible, as a carbon tax could lead consumers to substitute, for example, beef with chicken. However, this is not per se the case, as animal products are not perfect substitutes.  I'm presenting the results of my master's thesis in Environmental Economics, which I re-worked and published on SSRN as a pre-print. My thesis develops a model of animal product substitution after a carbon tax, slaughter tax, and a meat tax. When I calibrate[1] this model for the U.S., there is a decrease in animal deaths and duration of suffering following a carbon tax. This suggests that a carbon tax can reduce animal suffering. Key points * Some animal products are carbon-intensive, like beef, but causes relatively few animal deaths or total time of suffering because the animals are large. Other animal products, like chicken, causes relatively many animal deaths or total time of suffering because the animals are small, but cause relatively low greenhouse gas emissions. * A carbon tax will make some animal products, like beef, much more expensive. As a result, people may buy more chicken. This would increase animal suffering, assuming that farm animals suffer. However, this is not per se the case. It is also possible that the direct negative effect of a carbon tax on chicken consumption is stronger than the indirect (positive) substitution effect from carbon-intensive products to chicken. * I developed a non-linear market model to predict the consumption of different animal products after a tax, based on own-price and cross-price elasticities. * When calibrated for the United States, this model predicts a decrease in the consumption of all animal products considered (beef, chicken, pork, and farmed fish). Therefore, the modelled carbon tax is actually good for animal welfare, assuming that animals live net-negative lives. * A slaughter tax (a
MarieF🔸
 ·  · 4m read
 · 
Summary * After >2 years at Hi-Med, I have decided to step down from my role. * This allows me to complete my medical residency for long-term career resilience, whilst still allowing part-time flexibility for direct charity work. It also allows me to donate more again. * Hi-Med is now looking to appoint its next Executive Director; the application deadline is 26 January 2025. * I will join Hi-Med’s governing board once we have appointed the next Executive Director. Before the role When I graduated from medical school in 2017, I had already started to give 10% of my income to effective charities, but I was unsure as to how I could best use my medical degree to make this world a better place. After dipping my toe into nonprofit fundraising (with Doctors Without Borders) and working in a medical career-related start-up to upskill, a talk given by Dixon Chibanda at EAG London 2018 deeply inspired me. I formed a rough plan to later found an organisation that would teach Post-traumatic stress disorder (PTSD)-specific psychotherapeutic techniques to lay people to make evidence-based treatment of PTSD scalable. I started my medical residency in psychosomatic medicine in 2019, working for a specialised clinic for PTSD treatment until 2021, then rotated to child and adolescent psychiatry for a year and was half a year into the continuation of my specialisation training at a third hospital, when Akhil Bansal, whom I met at a recent EAG in London, reached out and encouraged me to apply for the ED position at Hi-Med - an organisation that I knew through my participation in their introductory fellowship (an academic paper about the outcomes of this first cohort can be found here). I seized the opportunity, applied, was offered the position, and started working full-time in November 2022.  During the role I feel truly privileged to have had the opportunity to lead High Impact Medicine for the past two years. My learning curve was steep - there were so many new things to
Ozzie Gooen
 ·  · 9m read
 · 
We’re releasing Squiggle AI, a tool that generates probabilistic models using the Squiggle language. This can provide early cost-effectiveness models and other kinds of probabilistic programs. No prior Squiggle knowledge is required to use Squiggle AI. Simply ask for whatever you want to estimate, and the results should be fairly understandable. The Squiggle programming language acts as an adjustable backend, but isn’t mandatory to learn. Beyond being directly useful, we’re interested in Squiggle AI as an experiment in epistemic reasoning with LLMs. We hope it will help highlight potential strengths, weaknesses, and directions for the field. Screenshots The “Playground” view after it finishes a successful workflow. Form on the left, code in the middle, code output on the right.The “Steps” page. Shows all of the steps that the workflow went through, next to the form on the left. For each, shows a simplified view of recent messages to and from the LLM. Motivation Organizations in the effective altruism and rationalist communities regularly rely on cost-effectiveness analyses and fermi estimates to guide their decisions. QURI's mission is to make these probabilistic tools more accessible and reliable for altruistic causes. However, our experience with tools like Squiggle and Guesstimate has revealed a significant challenge: even highly skilled domain experts frequently struggle with the basic programming requirements and often make errors in their models. This suggests a need for alternative approaches. Language models seem particularly well-suited to address these difficulties. Fermi estimates typically follow straightforward patterns and rely on common assumptions, making them potentially ideal candidates for LLM assistance. Previous direct experiments with Claude and ChatGPT alone proved insufficient, but with substantial iteration, we've developed a framework that significantly improves the output quality and user experience. We're focusing specifically on