If you ever need a classic rap song to communicate your desire to be more influential in animal philanthropy, just say: I wish I was a little bit taller I wish I was a Bollard

One reflection I've had in the whole "AI use in the encyclical" affair is to slightly increase my trust in traditional media, especially non-American traditional media, and slightly decrease my trust in social media/new media. I tried my best to promote my analysis as legibly and reasonably as I could and focused on logos rather than ethos: I didn't frame my article with institutional affiliations and intentionally chose not to include obvious, flashy, but irrelevant signaling. Stuff I could've done but explicitly chose not to: get an ML professor to cosign my analysis, publish on Arxiv instead of Substack and LessWrong, highlight my past ML experience at Google, etc.  The traditional media response were somewhere between neutral and positive. There were some disappointments (eg a famous media org won't run the article without confirmation from a "primary source" -- aka the Vatican which is of course a non-starter). But mostly the traditional media just looked at the analysis and said "yeah looked reasonable." and either ran it as "Unconfirmed but seems right" or just "Unconfirmed, Period." Which seems fine. On the other hand, the social media attacks were very aggro. People just didn't seem to entertain it at all, many without reading it. And I got personally attacked a ton[1]. Also it wasn't picked up at all[2] by new media afaict (unless you count Russia Today as new media). This is exactly the type of story you might expect new media to be good for: story of institutional decay in the Old Guard, investigation by someone without credentials carefully laying out an epistemically rigorous and systematic case. And traditional media was happy to report it[3], social media kept yelling at me, and new media just got crickets. 1. ^ Don't worry, I didn't take it personally at all. Very much a "yapping of chihuahua in a tiny purse" moment. 2. ^ This is a slight exaggeration. Other than Russia Today a bunch of small AI news aggregators (AI news i

I sometimes hear complaints from non-native English speakers about how banning undisclosed LLM use in writing is unfair. Possible pro-tip for non-native English speakers who want to write well but don't want to sound like AI: Just write an article you want to write in your native language, polish it until you're proud of it in your native language, and then ask a frontier LLM (Opus 4.8, Gemini 3.1 Pro, ChatGPT 5.5 Pro) to translate it to English, while reasonably adhering to your original intent and writing. In my experience and tests, the LLMs are sufficiently faithful in their translations that even the naivest possible way to do this (just one-to-one translation by a LLM without any further changes) would not trigger Pangram. I strongly suspect they wouldn't trigger human allergies either[1]. I suspect if you're upfront about your process, most people would be happy to read your translated words as well. Just explicitly state at the top of your post that you wrote the whole thing in Chinese/French/Romanian/Portuguese (with link to your draft) and you asked an LLM to translate it. If enough people do this, I think we'll have a natural new equilibrium where some people opt out of LLM-mediated translations, but the vast majority of your old readers will come back. I think this is also much healthier and less tenuous than the current equilibrium where people clearly use LLMs to formulate their writing, lie about it, and then when confronted hide behind "non-native speaker" as an excuse. (Optionally, you can ask the LLM to explain the non-trivial translation choices it made in its translations, which can help you with deciding whether to approve of the changes or not, and also learn English more in the mean-time. Though my guess is that it's not strictly necessary.) [1] (I've asked native speakers of other languages to test this, one for Swahili and one for Chinese. Both agreed that the results sound generic compared to the original writing but do not sound like

Lots of EA orgs say they struggle to hire for ops, marketing and comms. But when they post listings for these roles the salaries are often much lower than what they offer for research and engineering, which they generally find easier to fill. My guess is that orgs are just benchmarking against normal market rates for these roles. But the EA labour market is very different to the normal labour market, if these roles are undersupplied inside EA, I think orgs should be willing to pay more for them.

Our board now has more roles than before (1600+), and a public Airtable version that you can use to set up custom views and automations (including with Slack). A quick guide for using the new Airtable: 1. Open the public Airtable and click "Use this data". Make sure "Create a synced table" is selected. Choose which Airtable base you'd like the jobs data to live in. This creates a read-only synced table with our published roles. 2. Create a filtered view in the new table (e.g., filter by cause area, location, or role type). 3. From here, you can set up Slack notifications: 1. Trigger: "When record enters view", selecting the filtered view you created in step 2.  2. Action: "Send a Slack message" (via Airtable’s built-in Slack integration) 3. Compose your message using field tokens to pull in live data from each role, e.g. New role: {Job Title} at {Org Name} | {Job URL}. Use markdown for basic formatting like bold or italics.  If you use our job board, here’s a few ways you can help us to help you: * Test out the new Airtable and let us know if there are any issues or if you do anything cool with it. * If you land a role that you found on the job board, please get in touch! Even a short message about how our services helped you makes a huge difference to our ability to continue providing these services. * If you know of any orgs you think we should monitor for the board (including ones you work for), please share them! * If you work at an org that's listed on the board, note that links to your roles from our job board automatically include utm_source=probablygood_board so if you track referral sources, you'll be able to see applications that came via us. If you have a question on your application forms regarding where candidates heard about the role, please also consider adding "Probably Good" as an option.  * If you’re a hiring manager/recruiter who ends up hiring a candidate who found your role through our job board, please let us know! Othe