running the agi survey really reminded me just how brutal statistical significance is, and how unreliable anecdotes are. even setting aside sampling bias of anecdotes, the sheer sample size you need to answer a question like "do more people this year know what agi is than last year" is kind of depressing - you need like 400 samples for each year just to be 80% sure you'd notice a 10 percentage point increase even if it did exist, and even if there was no real effect you'd still think there was one 5% of the time. this makes me a lot more bearish on vibes in general.

Do we have some page containing resources for rationalist parents, or generally for parents of smart children? Such as recommended books, toys, learning apps, etc. I found tag https://www.lesswrong.com/w/parenting but I was hoping for some kind of best textbooks / recommendations / reference works but for parents/children.

What constitutes cooperation? (previously) Because much in the complex system of human interaction and coordination is about negotiating norms, customs, institutions, constitutions to guide and constrain future interaction in mutually-preferable ways, I think: 1. 'institution and constitution design' deserves special attention. This is despite it perhaps (for a given 'coordination moment') being in theory reducible to preference elicitation or aggregation, searching outcome space, negotiation, enforcement, ... There are failure modes (unintended consequences, concentration of power, lost purposes, corruptability, poor adaptability, plain old inefficacy) and patterns for success (stabilising win-win equilibria, reducing inefficiencies, improving collective intelligence and adaptability) which are specific to this process of negotiating and developing institutions (there are patterns, because the complex system has emergent structure like trust, corruption, coalitions, information propagation, ...). Said briefly: much (most?) coordination is about coordination because a) humans are that type of creature and b) we live in a highly iterated world.

My preference ordering over approaches to surviving the next decade, assuming I had unlimited political capital, is (don't build ASI and): 1: Solve mind uploading 2: ... or at least intelligence amplification (before proceeding, and then maybe do) 3: Imitation learning (with radically improved theoretical foundations) 4: ... or corrigibility / oracles (and don't) 5: Try to build aligned (or controlled) autonomous ASI agents Unfortunately 5 seems to be profitable, in the short term, so I guess that's what we're doing. In fact, the "plan" seems to be the exact reverse or so of my preference ordering on what it should be. 

I feel like there was a time just after ChatGPT became big where there were so many different new & competing frameworks for what exactly was going on, shard theory and simulators in particular but also active inference the MIRI views and all the people rolling their own ontologies with which to understand LLMs, and notably trying to make those ontologies explicit and comparing them against each other. Maybe I'm just around very different people now or doing very different work than I was (I am on both counts), but those conversations aren't really happening anymore. I don't know whether its for good or ill all things considered, but I do get nostalgic for them sometimes.

Gpt5.2 seems to have been trained specifically to be better at work tasks, especially long ones. It was also released early, according to articles about a "code red" in openAI. As such, (I predict) it should be a jump on the metr graph. It will be difficult to differentiate progress because it was trained to do well at long work tasks from the results of the early release and from any actual algorithms progress. (An example of algorithms progress would be a training method for using memory well - something not specific to eg programming tasks.)

Learned about 'Harberger tax' recently. The motivation is like * private assets (private use and excludable) incentivise investment/productive improvement/development well * but private ownership of non-liquid, non-fungible, idiosyncratic things (factories, houses, natural resources maybe, AI systems maybe?) acts like a monopoly, distorting allocation (more productive/valued uses aren't often realised) * e.g. NIMBYism * e.g. 'holdout pricing' * e.g. inefficient bargaining due to information asymmetry * common ownership and lease auctioning incentivises efficient allocation The pitch is like, can we do something in between? * self-assessment of value (reveals something close to honest valuation) * pay some rate of tax on that self-assessment * you have to sell at that self-assessed value if someone wants to buy They claim this keeps most of the benefit of investment incentivisation, because things are mostly private in practice, but substantially improves allocative efficiency by lubricating the more valuable trades. Anyway, mainly it's interesting because getting into the gubbins of particular proposals helps me learn about the relevant dynamics in general, but also I wondered if there's something in this vicinity that could work nicely for AI development and AI deployment. (Like maybe a Harberger tax on compute, or on AI systems, or...)