You should volunteer at your first EAG! (Especially if you are a student or early career) * If you don’t have a network in EA, EAG’s can be overwhelming. Volunteering gives you a ready-made, organic network. * Volunteering is pretty chill - a lot of the shifts aren’t that hard. * At your first EAG, it’s unlikely that you are using your time so efficiently that a few hours of volunteering would cut into the value of your conference.

We recently published an interview with Matthew Coleman - another entry in our Career Journeys series. Matthew is the Executive Director of Giving Multiplier, a platform that encourages donations to highly effective charities through donation matching. Before this, he completed a PhD in psychology, researching the psychology of altruism. The interview covers quite a lot of ground, but a few of the things we talked about include: * The gap between what a career looks like from the outside and what it's actually like day-to-day. * Advice for people wanting to make an impact through psychology. * The tension between keeping your options open and committing to a path. Here’s one of our favorite extracts from the full interview: On engaging with the (often mundane) realities of academic research: I learned a lot. By the time I started my lab manager role, I was fairly confident I wanted to do a PhD. But my research lab in undergrad, which I loved, was a very small lab where I was working closely with the faculty advisor, and I wanted to try out a larger lab studying different topics to explore a bit more. As the lab manager of an unusually large lab, I got a bird’s-eye view of a lot of the research projects going on and understood what the day-to-day looked like, whether that was grant applications, hiring and onboarding, or actually conducting research myself alongside my colleagues. I found the experience amazing and fascinating and really intellectually stimulating, which confirmed that I wanted to go the PhD route, so I followed through on my original plan from undergrad. […] I was certainly very fortunate to have gotten a lot of hands-on experience in research as an undergraduate, so I think I had a better sense of the day-to-day than many people do. But I do think it’s a very important point, and some related advice I like to give is: when you wake up on a random Tuesday in February, do you actually want to do the things that you have to do? Not just do y

LLM disclosure: used to search references, and to proofread in the end. Lighting has been getting ridiculously cheaper. And for the most part we seem to be not taking advantage of that positive externality: reducing crime through better lighting. This has been battle-tested as one of the effective ways for public security, see Chalfin, Hansen, Lerner & Parker (2022), an RCT in NYC public housing finding ~36% reductions in nighttime outdoor index crimes from added street lighting. Many, many major cities still haven't copied this at the right levels! But we're also getting substantially negative externalities of bright lighting. Office buildings that never turn off their lights because why would they care. Apropos the new office building that just opened next to my housing. This may alimentate NIMBY spirits in me, God forbid. Kyba et al. (2017) document that Earth's artificially lit outdoor area grew 2.2% per year from 2012 to 2016, with the LED transition producing a rebound effect instead of getting savings. Jevons paradox and such. Also, this has all sorts of annoyances. I think malls, pharmacies, and hospitals have all become much brighter since my childhood. I may be more sensorially overloaded than most people, but this does meaningfully affect my qualia, so much that Pigou himself would collect taxes from the pharmacies with dozens and dozens of LEDs, while Coase would advocate that I have the natural property right of not being assaulted with that much lumen while buying a Tylenol. This does affect wellbeing of more than just me (Cho et al. 2015). But lightly enough, ha, to not be a topic of discussion.

FYI, next week we will be highlighting the first batch of articles from In Development, @Lauren Gilbert's new global development magazine.  Lauren and most of the authors will be on the Forum to answer your questions throughout the week. More info to come on Monday, but I figured I'd mention in case anyone wanted to read the articles in advance (they are here, and all authors apart from Paul Niehaus will be around to answer questions).  I'm looking forward to the discussion. 

Just was watching Dwarkesh/David Reich podcast, fascinating stuff. Looking back at how I was taught taxonomy and anthropological history I find it frustrating. Note that I don't know much about (evolutionary) biology or genetics or the frontier of what genetic-history research so this is my layman attempt to explain why it's generally been puzzling for me how i have had this explained by other people who probably don't understand either, not trying to propose that I understand something david reich doesn't.  My main gripe is that we are taught evolutionary history mostly from the lens of evolutionary trees. But evolutionary history probably looks like a graph/stochastic process/markov chain, and only at very specific underlying parameters/ level of abstraction is well modeled by a tree. The reason we use trees is because that is the most sensible simple abstraction in some ways, if you are thinking about, "how did we get here?". But it's not a great way to think about "what happened/was happening".  I had chatgpt try to make the difference below (don't look too into the details, it did some hallucinating, just the general vibe).    Taking plausible parameters here to me would be thinking mixture isn't extremely likely over short time spans because of distance/etc but quite likely and almost certain over hundreds/thousands of years. So what did the near east look like genetically 60k years ago? It could easily look like below.      It seems totally possible that for long periods of hominid history genetics were well modeled by pretty smooth stochastic graphs with generally corresponding smooth genetics across geography (obviously with tons of exceptions or less true when you zoom in, e.g. bell beaker/corded culture), and yet when you look at our specific lineage it doesn't quite look like that (due to extinction, gene selection, or some other reason). I don't have a clear enough vision to say much more, but I think there are some interesting implications about w