There’s zero chance he’s gonna win in Idaho as an independent but Todd Achilles might win best campaign ad of the year with this

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Absolutely beyond parody. Dartmouth’s provost has been turning in 70-100-percent AI-written work (in academic journals, newspapers, and even in email correspondence!) since LLMs came out, the student paper reports. He even used AI to write an op-ed about how universities are dealing with AI cheating.

🚨 OBAMA ON AI: "If we are thinking about AI just in terms of how do we cure cancer or get better energy, you can do that without having agentic AI and having it just roaming free in the internet. The reason you are doing that is because you have to market a product that people will pay money for. That’s a misalignment between what our society needs and the commercial imperatives that these companies are facing, not because necessarily they’re trying to do bad things, but because they’ve got to justify these valuations. So, that’s one more reason why it is really important for us to have a competent government and a serious bipartisan conversation around this issue, and we have to do it fast. And I would encourage voters to pay attention to this. If somebody does not have a serious plan for how to deal with this, then they’re not meeting the moment, and you should probably look for somebody else."

>be me >discover effective altruism >apparently normal charity is inefficient >why donate to random sad thing when spreadsheet can tell you optimal sad thing >fair enough >buy mosquito nets >save lives >numbers look good >feel powerful >couple years later >someone asks an innocent question >why only count people alive today >huh >future people matter too >obviously >my grandchildren shouldn't matter less just because they haven't spawned yet >reasonable.jpg >keep following logic >what about their grandchildren >also yes >what about people in 500 years >sure >5000 years >why not >500 million years >starting to get weird but morality is morality >open calculator >humanity could survive for an astronomically long time >could colonize galaxy >could have trillions upon trillions of descendants >maybe digital people too >maybe simulated civilizations >maybe dyson spheres full of happy uploaded minds >calculator starts smoking >realize currently living humans are rounding error >8 billion people suddenly looking extremely beta >future contains potentially 10^something people >can't even fit beneficiaries in google sheets >new moral priority unlocked >protect the long-term future >stop thinking in units of "people helped" >start thinking in "fraction of cosmic endowment preserved" >malaria? >terrible >but only kills existing humans >AI extinction could delete the entire light cone >nuclear war could permanently derail civilization >bad institutions could lock in terrible values for ten million years >someone invents wrong constitution in 2140 >quadrillions suffer >better fund governance workshop now >friend says maybe we should improve hospitals >explain opportunity cost >friend says hospitals are full of actual sick people >explain scope sensitivity >friend stops inviting me to dinner >need to decide what to fund >easy >expected value >suppose project has one in a million chance of preventing extinction >sounds tiny >but extinction destroys 10^50 future lives >multiply >mother of god >$10 million project has expected value of several galaxies >charity evaluation complete >someone asks where the one-in-a-million number came from >expert judgement >which expert >us >how calibrated >extremely thoughtfully >reduce estimate to one in ten million to be conservative >still beats curing cancer by 38 orders of magnitude >epistemic robustness achieved >someone says maybe project doesn't work >assign 20% chance >still astronomical >maybe project makes problem worse >assign 5% chance >still astronomical >why 5 >because 30 felt pessimistic >publish 46-page report >contains seventeen sensitivity analyses >every sensitivity analysis begins after assuming intervention has positive sign >critic says you're multiplying enormous hypothetical stakes by extremely uncertain probabilities >yes >that's literally why it's important >critic says the uncertainty might be structural rather than numerical >make probability smaller >critic says no, I mean maybe your model is wrong >make probability smaller again >critic begins rubbing temples >discover AI safety >perfect longtermist cause >AI might kill everyone >or create utopia >or seize galaxy >or tile universe with paperclips >or create billions of conscious software minds >finally a problem with numbers big enough for me >start AI safety nonprofit >mission: prevent dangerous AI >hire smartest people available >smartest people immediately start building better AI to understand dangerous AI >interesting >we must understand capabilities to understand safety >we must scale models to study alignment >we must race ahead so less responsible actors don't get there first >we must deploy systems to learn how deployment can go wrong >we must build the thing quickly because building the thing quickly is dangerous >outsider asks why the people most worried about AI apocalypse all work at AI companies >complicated field >company releases stronger model >very concerned >company begins training even stronger model >extremely concerned >company raises $14 billion >concern reaches unprecedented levels >need to influence government >future is at stake >normal democratic process too slow >politicians don't understand exponential curves >public doesn't understand x-risk >experts must guide them >who counts as expert >people who understand x-risk >who understands x-risk >our friends >someone objects that this seems politically convenient >explain we're representing future generations >future generations unavailable for comment >develop concept of value lock-in >terrifying possibility that one ideology controls civilization forever >therefore extremely important that civilization adopts correct values before lock-in >whose values >let's circle back >begin with impartial morality >end with small group of people deciding what quadrillions of hypothetical beings would want >beautiful arc >meanwhile actual humans keep doing annoying things >voting wrong >having parochial attachments >loving family more than strangers >caring about local community >getting upset when told their suffering is cosmically negligible >evolutionary biases everywhere >explain that moral intuition cannot be trusted >except intuition that future digital people count >and intuition that extinction is uniquely bad >and intuition that our probability estimates are sane >and intuition that our institutional choices improve the future >those intuitions survived peer review >someone donates $5k to local homeless shelter >inefficient >could have funded 0.0000000000003% of an AI governance researcher >think of all the simulated people you just killed >okay maybe don't phrase it that way publicly >PR team says "future generations deserve a voice" >much better >journalist asks what longtermism means >say "future people matter" >everyone agrees >great >journalist asks what follows from that >well technically we should redirect enormous resources toward low-probability interventions affecting astronomical futures >journalist raises eyebrow >return to "future people matter" >motte has entered the chat >critic: of course future people matter >me: glad we agree >critic: I don't agree that your institute knows how to help them >me: why do you hate our grandchildren >eventually notice uncomfortable implication >if future value dominates everything >then helping people today mostly matters through effects on future >education matters because future institutions >health matters because future productivity >democracy matters because future trajectory >human beings slowly become instrumental variables in their own moral philosophy >see starving child >feel compassion >check spreadsheet >child's direct welfare contribution negligible >but perhaps childhood nutrition improves national institutional quality >compassion restored >tell myself this is impartial altruism >one day assistant asks obvious question >"how do you know your intervention actually improves the far future?" >silence >open spreadsheet >increase column width >add confidence interval >assistant asks again >"no, I mean how do you know the sign is positive?" >stare into cosmic light cone >10^50 people staring back >none of them exist >none of them can tell me >none of them can falsify my assumptions >realize I have invented the perfect constituency >infinitely important >completely silent >and always represented by me

Am putting together a list of economists and political scientists who rock climb for the purpose of seeing whether there are more opportunities for climbing meets, conferences, conference circuit, etc.

Why you can’t do RSI as fast as you like -

I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the takes on AI killing us all by creating dangerous viruses is total bogus.

Rabies kills ~59,000 people a year globally. At that rate, the United States should lose 2,500 people a year to rabies. But the real number is fewer than 10, partly because we've spent 30 years dropping fish-flavored ravioli out of helicopters over the Appalachians. Each one contains a rabies vaccine inside a fishmeal-coated block. Raccoons, foxes, coyotes and skunks find them by smell, bite through, and enjoy the treat. Four to six weeks later, they carry rabies antibodies. Enough of them in one area and the virus runs out of animals to move through. USDA Wildlife Services has been doing this this line since 1995. It runs roughly from Maine down through Alabama, and its job is to stop raccoon-variant rabies from crossing into the central US, where it has never established. A single course of post-exposure shots runs into the thousands of dollars, and every rabid raccoon in a suburb produces a cluster of them: the kid who got scratched, the dog that tangled with it, etc. US rabies prevention costs between $245 and $510 million a year and avoids over a billion in medical spending. Long Island is probably our best case study for this program. A $2.6 million baiting program eliminated raccoon rabies from the zone, and paid for itself in eight years on avoided shots and testing alone. The biggest question I hear about this is: what happens if my dog finds one? And the answer: nothing bad. This vaccine has been safety-tested in over 60 species at varying doses with no adverse reactions observed, regardless of how much was given. About 250 million doses have been distributed worldwide since 1987 with no documented deaths in wildlife or domestic animals. The most severe adverse reaction observed was upset stomach.

I’m in a group chat with economists in a variety of fields - all are in 90th percentile or greater of ai use in the profession Fwiw no one’s noticed a step change from 5.6 to 6. Bottleneck for Econ research is not what the models are being rl’ed on. Might be that economic research is not economically valuable, or at least not valuable enough that labs are willing to pay the high price for those rl environments relative to those for example for financial analysts