Quick Takes

Someone recently shared an interesting minimal model of electoral politics with me. Elected officials are influenced by two primary groups: voters and donors. Sometimes voter and donor interests align, but often they don't. Voters are the ultimate deciders, but they are only really swayed by the top-3 most salient issues. On those issues, elected officials side with voters, but on the rest they tend to side with donors. It's simply too costly for elected officials to go against donors on low-public salience issues; they can spend the donated money on campaigning for the top-salience issues, after all! One interesting low-salience issue is AI policy. Voters are generally anti-AI (they don't like datacenters, automated surveillance, or recommender systems) but donors (often tech billionaires) are pro-AI. As AI is currently a low-salience issue for US voters (at least relative to the broader economy, healthcare, and immigration), politicians are siding with donors. For meaningful political action on AI, one would need either: AI to become a top-3 salience issue to voters (e.g., via job loss, weaponization, or warning shots); or more anti-AI donors to mobilize.

It's getting increasingly easy to farm karma on LessWrong by making almost substantive-less posts that just articulate a position most people agree with. Imo this is a really huge problem, karma matters, it shapes what people see and it sets incentives. As your good deed for this week, find something to strong-downvote that you agree with. I'd guess most people do that far too infrequently, maybe never.

@Daniel Kokotajlo easily won our bet on task lengths:  I've expected to lose for a couple of months but I have to admit I'm still surprised by the score for Opus 4.6. I now believe that very short timelines are more likely than not (though still with a heavy-tailed distribution). I'll write soon about how my position has changed (and particularly how my model of what is going on with LLMs has held up - the predictions in that post were probably wrong, but certain "downstream" predictions e.g. difficulty of getting neuralese to work seem to have held up). Of course, my updates are not based only (or even primarily) on this specific metric. I'm pivoting towards research that looks likely to yield results sooner and career choices that provide more influence over the near term future. In the meantime, Daniel should reach out to me with payment details. Congratulations on getting this right, though of course we both hoped you'd lose :)

I wanted to make brownies today and only had mass market cocoa powder, so I tried to learn a bunch about the cacao economy in West Africa. I might or might not end up writing a thing called something like "Toward Chocolate Utopia: The Cacao Disaster and How Rich Westerners Can (and Can't) Help". In case I don't, here's the likely summary: * Most of the world's chocolate is sourced from cacao farms in Ghana and Côte d'Ivoire. There are a few interlocking systems that perpetuate a lot of fucked-up-ness about cacao farming in that region, including the slavery and deforestation you may have heard of. * If you feel icky buying mass market slave chocolate and wanna do something to help, it's really hard to beat donating to any of GiveWell's current top charities. None of the interventions that directly target the chocolate industry looks as promising as reducing the overall desperation of rural West African cacao-farming families who are stuck in the poverty cycle, and illness prevention is probably a great way to do that. * Two things that might possibly beat this if you want to do some real work in a neglected high-leverage area: 1) Get a solid system of land titles going in Ghana and/or Côte d'Ivoire, where people currently can't prove that they own their land, which is a major piece of the puzzle for both the poverty cycle and deforestation, and 2) (I'm less sure about this one but also now may be an unusually good moment for it) partner with a Licensed Buying Company to make an SMS-based digital delivery-and-payment-tracking system. * Things that almost certainly don't bring us closer to Chocolate Utopia than donating to GiveWell's top charities: Any sort of fair trade certification programs, programs that monitor for child labor, any demand-side shifts. Boycotting all the chocolate makers who source through Barry Callebaut, Cargill, or Olam and eating only bean-to-bar chocolate from high-transparency brands might not even be at all helpful from farmworker well

Some infectious disease graphs I would like to see but haven't been able to find: * Effectiveness of covid and flu vaccines vs time since injection. * Contagiousness with cold/flu/covid vs time since infection. * Decrease in infection probability vs distance from infected person.

Some results from a lumenator RCT I ran on myself [1] . Stand-outs: Having the lumenator on increases some variables by a lot, reliably, especially the subjective length of day and happiness, but also contentment, relaxation, and horniness [2] . So the original reasoning for lumenators stands up. It does not improve productivity (surprising!) or creativity. Also factor basically measures how well my flashcard content was, which also increased, though I don't trust those numbers particularly much since I only started doing flashcards towards the end of the experiment. The lumenator plausibly worsens meditations, but also a bit fraught given that only some experiment days had me doing meditation. absorption mindfulness productivity creativity sublen happy content relaxed horny ease factor ivl time d -0.4451 -0.7275 0.2087 0.0140 0.5061 0.5518 0.3823 0.4046 0.2238 0.1079 0.5192 -0.1511 -0.0449 λ 3.0944 9.0917 2.4987 0.5691 10.2831 31.0045 15.6398 28.3924 7.6674 2.5491 43.8971 4.6378 0.4189 p 0.4101 0.0079 0.5265 0.9208 0.0029 0.0000 0.0000 0.0000 0.0245 0.5161 0.0000 0.1864 0.9447 dσ -0.0269 -0.0866 0.0233 0.0144 0.0310 -0.2440 -0.3504 0.5453 -0.4503 -0.0670 -232.2879 29.1267 577.4129 k 32.0000 32.0000 50.0000 50.0000 50.0000 198.0000 198.0000 198.0000 198.0000 295.0000 295.0000 295.0000 295.0000 1. Writeup maybe sometime, maybe never. I still haven't properly written up my Pomodoro Method RCT or my Vitamin D₃ RCT either. ↩︎ 2. This one's not above the 0.05 threshold if Bonferroni-corrected though. ↩︎

I recently learned from Simon Willison's Feb 7th blog about StrongDM, who are implementing a Dark Factory level of AI adoption where nobody even looks at the agent-written code, and for security software to boot (I'd be keen to get @lc's take on what they're doing). StrongDM's public description of what they're doing is here. Quote: Thought to signal-boost and get takes on what StrongDM are doing after seeing Gordon's comment that because it made me go "but StrongDM is already there?".  This also brings to mind a few other examples, although none of them are at StrongDM's level (dark factory + group not solo + security software): * Liu Xiaopai, the infamous Beijing vibe coder, although of course code quality is well down his list of priorities (that would be maximising revenue growth for his Claude Code-driven budding conglomerate) * Peter Steinberger seems close behind but he's building for himself and none of his projects are security software AFAICT  * From this interview at 16:17 onwards with Boris Cherny (creator and head of Claude Code at Anthropic) I'd guess he's somewhere ahead of Gordon and behind Peter, in that he "ships something like 10-30 pull requests a day" and "hasn't edited a single LoC by hand since Nov '25", although he still "looks at the code" because he doesn't think they're at the totally hands-off point "especially when there's a lot of people running the program" I mostly pay attention to this because I keep being reminded of Rudolf L's 2025-27: Codegen, Big Tech, and the internet section of his "history of the future" whenever I see recent developments, it's become quite a useful and underrated intuition pump since it's so granular.