The Abundance and Growth Fund goal is to raise broadly shared economic growth. We support work ranging from research to fieldbuilding to practice, with an initial focus on innovation, energy, clinical trials, housing, and state capacity. More here! open.substack.com/pub/abunda…

UPDATE: I’m launching a podcast called Tacit Knowledge. My goal is to tackle something I think will remain scarce in the age of AI: working on hard problems where the next step is unclear. Goal is to chat with my favorite doers. Feedback welcome. renaissancephilanthropy.subs…

This @TheEconomist cover story on effective altruism was interesting and IMO way more accurate (including in its critiques) than most other reporting you will read on EA these days. A couple quibbles: -I think calling EA the “the century’s big idea” is, uh, premature to say the least. But I do appreciate the acknowledgement and curiosity about how EA was so early to pandemic risks and the promise and perils of AI. -They imply that EA started off with “charitable roots” but then got weird over time, whereas I think EA has always made space for pretty weird ideas (e.g., here’s @DylanMatt in 2014: vox.com/2014/4/23/5643418/th…). And EA still puts far more money and attention than almost any other community into the kind of evidence-backed global health giving the Economist praises. -Some of the purported wild EA views they critique are just standard topics of academic philosophy debate (e.g., cambridge.org/core/journals/…). -They attribute the EA interest in AI safety to longtermism, but I think it’s been clear for years that AI safety concerns are justifiable based on potential impacts this decade, not to mention this century (x.lingyaoai.com/albrgr/status/15595748…). But I think they correctly gesture towards the IMO best critique of EA ideas, which is their totalizingness. My former colleague Holden wrote a great post about this in 2022: forum.effectivealtruism.org/… I wrote a long thread grappling with this critique a few years ago (x.lingyaoai.com/albrgr/status/15327261…). I think part of what makes EA distinctive as a community relative to the underlying academic moral philosophy is the orientation around pragmatism - Giving What We Can took off decades after Singer had articulated the underlying case because “give until the marginal giving would entail as much suffering for you as benefit for the other person” was a much worse pitch than “give 10%.” But the community doesn’t always reflect that healthy moderation, and trying to grapple with the vertiginous stakes of increasingly near-term risks from AI really can run a risk of crowding out other sources of value. At CG, our response to this has been worldview diversification (coefficientgiving.org/resear…), spreading our giving across very different views of what matters, rather than going all-in on one. Worldview diversification leaves plenty of hard questions (how do you allocate the pie across very different types of moral good?) but helps cut off some of the ways maximizing can be perilous. It’s one reason global health and wellbeing – which @TheEconomist didn’t give the space it deserved – has gotten most of our funding since 2014.

As real wage growth dips negative again (x.lingyaoai.com/mattyglesias/status/21…) it seems like a good time to tweet thread about a great paper by Christina Patterson (my wife!) and her wonderful co-authors (Erik Hurst, @NelaRichardson, and Ye Liv Wang) on exactly that topic (1/N)

As an energy transition founder: we need permitting reform now. Electrification is colliding with huge demand from AI. We need to make it easier to build the power infrastructure required. To my friends on the climate left: don’t wait for a better deal. Pass BAAJA.

🚨🚨We finally have the bipartisan permitting deal that the Build America Caucus has been fighting for over the last 18 months. Now Congress needs to pass it. Here’s why we should:

1/The permitting bill is out and it’s awesome. HUGE congrats to @SenWhitehouse and @MartinHeinrich. This took years (now we can all see why!) against the backdrop of an administration actively hostile to a lot of clean energy the whole time. 🧵

🚨 WE HAVE A PERMITTING DEAL🚨 And it is easily the best permitting bill we've ever gotten! - The Bipartisan American Affordability and Jobs Act is HUGE (400+ pages) and both sides got a LOT. - The bill is much bigger and better than either Manchin post-IRA in 2022 or Manchin-Barrasso in 2024. Once I finish reading the text I'll publish an explainer. For now, here are a few high level takeaways. 1. Transmission: The bill is absolutely HUGE for transmission, going further than Manchin-Barrasso. Includes: interregional transmission, limited federal backstop authority, interconnection queue reforms, directives for advanced grid-enhancing tech, and oversight of utilities. It's absolutely AMAZING all of this got in. 2. NEPA: The bill has BIG changes to NEPA, including fixes for judicial review that underpins the law's costs. Still reading but this is even better than I expected! 3. Certainty: The bill includes strong provisions to push back on misuse of permitting, like we're seeing with the admin's abuses against offshore wind. 4. Historic Preservation: The bill includes changes to the NHPA 106 process, including changes to judicial review that will help right-size the process. 5. Clean Water: The bill fixes problems with section 401 by adding new requirements for states and makes section 404 nationwide permits easier to comply with. 6. Geothermal: The bill includes big wins for geothermal, including parity with oil and gas catexs. 7. Mining: The bill fixes the "Rosemont decision" 8. Endangered Species: The bill creates a new path for states to take on endangered species consultation. 9. Hydro: Fixes for certain hydroelectric projects 10. Ratepayer protection: The bill adds protections for ratepayers from added data centers. Looks to be stronger than the House passed bill by quite a bit.

Excited to announce Living Science! Papers have been the de facto unit of knowledge in science. But science is not static and a paper is not meant to be the final destination, especially in empirical research. Empowered by AI agents, we're revisiting influential research as new data, models, and methods arrive, starting with economics. 🧵

LLM classification of where 37k inventions listed on Wikipedia were invented. From nber.org/system/files/workin…

Great piece but also distressing! The secret IMO is to lower the bar for hosting: - don’t cook food, order takeout - include kids, accept messiness - don’t overdo the # of invites Esp bc of the decline @DKThomp notes, this toned down version is great and >> alternative (nothing)

Happy Friday! Iʼve created a game for you to play! Will AI cure all diseases in 10 years? Inspired by bottlenecks discourse, I created a game to help build your intuitions. Play it here: game.clinicaltrialsabundance… Naturally, it’s bottle-themed with bubbles and there are leaderboards too.

Over the past two years, I4R partnered with Psychological Science on a large reproducibility project. 67 independent teams reproduced 64 articles published in 2024–2025, about 44% of eligible papers. Paper: econstor.eu/bitstream/10419/… Here's what we learned 🧵

My session for the IFP short course on the economics of innovation is now online!

Many assume it's super hard to predict paper citations, but it's really not. Authors can pretty reliably predict* which of their papers will be more highly cited * potential confound: authors may promote their favorite papers more, causing more citations

One reason we might see fancy people using a lot of AI in writing is that offloading writing tasks is natural for them. The difference is that previously they offloaded writing to research assistants or junior staff. Thought leader types often say yes to a lot of things and have tons of ideas, but have limited bandwidth, so they delegate their thought leadership to subordinates. For some, working with AI might actually be a step towards sharing their own thoughts because they don't have to take what comes from an assistant and decide whether they like it. They can just tell a machine what they think, and it spits out an essay. When I worked in government, we contracted with a rock star faculty member to do a research project and then I spent the next six months arguing with their first year PhD student RA about methods. Basically before there was AI slop there was RA slop.

Really nice report. Follow up: why has the fall in AI prices been so fast? When you plot the price decline against cumulative R&D investment rather than time, you get the elasticity of price declines to R&D investment. By this margin, AI is not unusual – its price elasticity to R&D investment is squarely in the middle of Epoch's considered technologies. So the AI price fall is historically unprecedented because we've dumped money into AI R&D at a historically unprecedented rate – and that R&D has paid off at a very average rate.

Vought is increasingly isolated on medical science funding - on Appropriations, Uniform Grants Regulation, and the EO, he has been beaten back. Merit-based science backers need to go on offense, now: the forward funding & grant freezes at NIH need to stop, too.