Astral Codex Ten Podcast

[I haven't independently verified each link. On average, commenters will end up spotting evidence that around two or three of the links in each links post are wrong or misleading. I correct these as I see them, and will highlight important corrections later, but I can't guarantee I will have caught them all by the time you read this.] https://www.astralcodexten.com/p/links-for-december-2025

The term "vibecession" most strictly refers to a period 2023 - 2024 when economic indicators were up, but consumer sentiment ("vibes") was down. But on a broader level, the whole past decade has been a vibecession. Young people complain they've been permanently locked out of opportunity. They will never become homeowners, never be able to support a family, only keep treading water at precarious gig jobs forever. They got a 5.9 GPA and couldn't get into college; they applied to 2,051 companies in the past week without so much as a politely-phrased rejection. Sometime in the 1990s, the Boomers ripped up the social contract where hard work leads to a pleasant middle-class life, replacing it with a hellworld where you will own nothing and numb the pain with algorithmic slop. The only live political question is whether to blame immigrants, blame billionaires, or just trade crypto in the hopes that some memecoin buys you a ticket out of the permanent underclass. Meanwhile, economists say things have never been better. Are the youth succumbing to a "negativity bias" where they see the past through "rose-colored glasses"? Are the economists looking at some ivory tower High Modernist metric that fails to capture real life? Or is there something more complicated going on? We'll start by formally assessing the vibes. Then we'll move on to the economists' arguments that things are fine. Finally, we'll try to resolve the conflict: how bad are things, really? https://www.astralcodexten.com/p/vibecession-much-more-than-you-wanted

…the bad news is that they can't agree which one. I explained the debate more here, but the short version is: twin studies find that most traits are at least 50% genetic, sometimes much more. But molecular studies - that is, attempts to find the precise genes responsible - usually only found enough genes for the traits to be ~10-20% genetic. The remaining 35% was dubbed "missing heritability". Nurturists argued that the twin studies must be wrong; hereditarians argued that missing effect must be in hard-to-find genes. The latter seemed plausible because typical genetic studies only investigate the genes that most commonly vary across people - about 0.1% of the genome. Maybe the other 99.9% of genes, even though they rarely vary across people, are so numerous that even their tiny individual effects could add up to a large overall influence. There was no way to be sure, because variation in these genes was too rare to study effectively. But as technology improved, funding increased, and questions about heredity became more pressing, geneticists finally set out to do the hard thing. They gathered full genomes - not just the 0.1% - from thousands of people, and applied a whole-genome analysis technique called GREML-WGS. The resulting study was published earlier this month as Estimation and mapping of the missing heritability of human phenotypes, by Wainschtein, Yengo, et al. Partisans on both sides agree it's finally resolved the missing heritability debate, but they can't agree on what the resolution is.

If we worry too much about AI safety, will this make us "lose the race with China"1? (here "AI safety" means long-term concerns about alignment and hostile superintelligence, as opposed to "AI ethics" concerns like bias or intellectual property.) Everything has tradeoffs, regulation vs. progress is a common dichotomy, and the more important you think AI will be, the more important it is that the free world get it first. If you believe in superintelligence, the technological singularity, etc, then you think AI is maximally important, and this issue ought to be high on your mind. But when you look at this concretely, it becomes clear that this is too small to matter - so small that even the sign is uncertain. https://www.astralcodexten.com/p/why-ai-safety-wont-make-america-lose

Most discourse on AI is low-quality. Most discourse on consciousness is super-abysmal-double-low quality. Multiply these - or maybe raise one to the exponent of the other, or something - and you get the quality of discourse on AI consciousness. It's not great. Out-of-the-box AIs mimic human text, and humans almost always describe themselves as conscious. So if you ask an AI whether it is conscious, it will often say yes. But because companies know this will happen, and don't want to give their customers existential crises, they hard-code in a command for the AIs to answer that they aren't conscious. Any response the AIs give will be determined by these two conflicting biases, and therefore not really believable. A recent paper expands on this method by subjecting AIs to a mechanistic interpretability "lie detector" test; it finds that AIs which say they're conscious think they're telling the truth, and AIs which say they're not conscious think they're lying. But it's hard to be sure this isn't just the copying-human-text thing. Can we do better? Unclear; the more common outcome for people who dip their toes in this space is to do much, much worse. But a rare bright spot has appeared: a seminal paper published earlier this month in Trends In Cognitive Science, Identifying Indicators Of Consciousness In AI Systems. Authors include Turing-Award-winning AI researcher Yoshua Bengio, leading philosopher of consciousness David Chalmers, and even a few members of our conspiracy. If any AI consciousness research can rise to the level of merely awful, surely we will find it here. One might divide theories of consciousness into three bins: https://www.astralcodexten.com/p/the-new-ai-consciousness-paper