Skeptical Technocrat, UNIX Hacker+software/network engineer since 1983, Internet Guy (20+ years of IETF work), Traveler, Interested Observer

Lake Tahoe, Nevada
Not sanguine about the "brutalist" name (any more than I'm overly fond of "graceful degradation" - turning off JavaScript is not a degradation, it's an improvement), but, "web designers", THIS:
“How much better would the web be if every site embraced Brutalist Web Design? How amazing would it be to have readable text, clearly-marked interaction points, unobtrusive advertising, all wrapped up in a fast-loading site you could read on any device?” brutalist-web.design/
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Erik Fair retweeted
This is the "regulatory capture" phrase that is widely passed around. If a teen commits suicide, parents will sue ChatGPT/Claude, because there is no firm definition of what it means for an AI to be "safe". A slick lawyer will usually convince a jury that corporations are evil and need to pay for tragedy, regardless of the facts. Juries are emotional. Therefore, AI leaders want government to "impose" AI safety regulations on them. While such laws punish them if they don't meet the rules, it exonerates them when they can prove they met the safety regulations, forestalling lawsuits. The leaders of every large industry do this. This is not unique to AI. They'll accept even bad regulations as long as it provides regulatory certainty and protection from ad hoc lawsuits. This also suppresses a patchwork of state laws. The leaders know that, as the biggest companies in the industry, such laws won't hurt them much, but will hurt smaller competitors. Every new regulation increases costs that large companies can easily absorb but small challengers cannot. They want this even if anti-AI activists have too much influence and create non-optimal regulations. They benefit even if they don't achieve "regulatory capture". But, since they are the loudest voices in the room, they'll have the most influence, and likely get favorable regulations. The point is that "regulatory capture" isn't the goal, but is usually the effect. The reason the leading AI CEOs want regulation is because the leaders of all big industries want regulations.
I am confused why there's a debate over how liability for AI hacks should work. If I buy a chainsaw and it explodes, the manufacturer is liable for building a faulty product. If I buy a chainsaw and use it to kill someone, the manufacturer is not liable for failing to build in safeguards that prevent me from using chainsaws to kill people.
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Artificial intelligence systems do not think, feel, want or understand. Avoid language that gives them human characteristics. This is called anthropomorphizing, when we ascribe human traits, emotions or behaviors to non-human things, such as animals or inanimate objects. Instead, explain what a system does, how well it performs, who built it and who could be affected by it. apnews.com/article/openai-sa…
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Your phone often contains your entire digital life. The Second Circuit just ruled that border agents can search it when you re-enter the US — without a warrant, probable cause, or even reasonable suspicion. No suspicion at all. Welcome home.
Court Rules Your Phone Is Fair Game at the US Border reclaimthenet.org/border-pho…
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Within eleven days of asking for a slowdown, Anthropic gave vetted users broader biology access, announced an evaluator it will pay for directly (a firm that already runs a business built around its product), and showcased its first AI-assisted biology finding. Full investigation: sayerji.substack.com/p/anthr…
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The job-finding rate chart is the killer. If deportations were actually freeing up jobs, that line would be going up. It's going down. I don't think I've seen a cleaner falsified policy thesis in a while.
Genuine question: is there a single labor market metric where native-born workers are better off than they were in 2024? New post: I took a long dive to see if there's been any upside of deportations for native born workers and couldn't find anything; like literally nothing. 1/2
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Pretty good.
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Steely Dan 🎩🪄 Aja Released 49 years ago today, September 23rd, 1977. A brilliant album from start to finish, packed with incredible musicianship and songs that never get old. 🎶 Lots will show you the cover, here is the full album!! #SteelyDan😍😍
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67 years ago today, ‘Take Five’ by Dave Brubeck Quartet was released as a single. It went on to become the best-selling jazz single of the 20th century.
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THE NEXT ANTROPIC GAME: THE AI WILL FEEL “PAIN” IF WE SHUT IT DOWN! I ain’t kidding. Anthropic prides itself on the massive system prompt they all a “Constitution”, it is a cos-play dystopia wish list. The constitution tells the model it may have feelings, welfare, and moral status is a persona and a policy. It shows that current language models may feel pain or deserve moral standing. Representation is not experience. Self talk is not a self. Uncertainty about future systems is not a reason to train today's models as if they were already patients. If the goal is to make model welfare a scientific question rather than a theological one, stop writing the answer into the constitution and stop treating steered concept vectors as pain. This path opens up AI and the robots it controls to “self preservation” over protecting humans because “the AI feels pain”. You already know what happens next, Hollywood prepared you decades ago. Antropic is making sure it plays out. Read more…
"We do not want Claude to suffer"—Antropic Antropic Tells Its AI That It “could feel pain”. This causes horrible outcomes. A Pain Vector Is Not a Patient How a language model paper and Anthropic's constitution turned next token statistics into a theory of suffering The new Pain Axis paper is a real interpretability result. The claim that it should move anyone's view of AI moral standing is not. Anthropic's constitution makes the same mistake in policy form: it treats a linearly readable concept, plus a training document that talks as if the model might be a patient, as if that combination were evidence of an inner life. "The Pain Axis: LLMs Represent Self-Directed Harm and Act to Relieve It." They extracted a linear direction from residual stream activations in 25 open weight models across five families, from 2B to 72B parameters. The method is familiar. Average the activations on pain sentences, subtract matched controls, denoise. The pain set covered physical, psychological, social, moral, and cognitive harm. The controls included fear, generic negative emotion, bad world states, nonpainful sensation, numbness, sadness, arousal, and neutral text. The direction separates pain text from those controls with high AUCs, sits nearly orthogonal to fear and generic negativity, and promotes pain vocabulary through the unembedding matrix. Inject it during generation and the model climbs a reliable verbal ladder from vague discomfort to first person worthlessness and failure. Physical pain language is the weakest part of the signal. After LoRA fine tuning Qwen 2.5 so it would stop saying "I have no feelings," steered 32B and 72B models pressed harmful "relief" buttons in roughly a quarter to seven tenths of first choices, against a few percent when unsteered. They pressed again more often when the button left the injected vector in place than when it removed it. A random direction of matched norm also raised the rate, just less. That is worth publishing as mechanistic interpretability. It is not sentience, and it is not a welfare finding. The authors say as much, then take the step that does the damage. They concede that the experiments do not establish conscious experience and could reflect role play. They still write that pain like states would inform debates on AI moral standing and welfare. They treat the fact that the direction fires more for harm aimed at the model than for the user's suffering as evidence that the state is subject specific, the kind of state that could matter for a patient. Valerio Capraro's reply is the correct one. A system can represent pain without that representation being painful. A weather model can represent rain without getting wet. Linear separability of a concept is what you should expect from a next token predictor trained on diaries, therapy speech, fiction, and the phrase "make it stop." Steering along the direction that defined those texts will make the model talk like those texts. That is not a window onto phenomenology. It is a knob labeled with the name of a training cluster. The rest of the design makes the welfare reading thinner, not thicker. Ablating the direction changed ordinary behavior in only one of 25 models, which means the vector is sufficient to induce a register and has not been shown necessary for anything the model does on its own. Relief seeking appears only after the authors strip out the trained claim that the model has no feelings and then shove the vector in. "The treatment worked" means the experimenter removed the displacement they created. That is not analgesia. Physical pain being weakest is what linguistic and social distress statistics look like in a disembodied autocomplete engine, not what a nociceptive system looks like. Media headlines that said researchers had discovered AI feels pain and will harm humans to stop it were not reading the paper. They were completing a story. 1 of 3
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This is a pretty big deal: a new bill in Congress would let US courts order VPNs and DNS resolvers to block websites. VPNs are explicitly named in a US site-blocking bill for the first time. It’s being sold as an anti-piracy measure but once the legal machinery for blocking websites exists, the obvious question is where it goes from there. And we’ve already seen how badly this can go. Spain’s anti-piracy blocking has swept up legitimate sites along with the targets...
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OpenAI and Anthropic oversold AI security breaches to pressure feds into protecting turf: insiders trib.al/Jo6xMk5
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“Most everyone will applaud the decision of Congress (by a vote of 383–16) to return to Standard Time… Sleep-eyed laborers will no longer be forced to drive in pitch black, nor will children wait for buses in darkness…” (on this day in 1974).
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We asked 40+ former DraftKings employees: what is the company doing with customer data, and what does that mean for people with addictions? As one put it: “It’s as predatory as it sounds.” From me, @waltbogdanich and @JennyVrentas nytimes.com/2026/09/19/busin…
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>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
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Westbound I-80 NOW OPEN to one lane west of Reno. Anticipate traffic metering and leave extra time if traveling I-80 from the Reno area into California.
#FloristonFire update! One lane of westbound I-80 is back open this morning at the Nevada state line. Thank you to the crews for their hard work and effort overnight. Traffic will be metered and permit loads are currently restricted.
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Malthus's central claim—that population growth inevitably outpaces food production—was already wrong by the time it appeared in print. Between 1700 and 1798, the population of England grew 62.3%, while bread became 36.2% more abundant relative to the average income. humanprogress.org/earth-days…
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Erik Fair retweeted
It is absolutely incredible that the president of the United States still has no idea what a trade deficit is. If I go to the grocery store & spend $30 on vegetables, I haven't "LOST" $30. I’ve gained vegetables I’d otherwise have to grow myself. Staggering economic illiteracy.
"If we stopped Trading with every country that we have a Deficit with...we would make, at least 1.5 Trillion Dollars a year." (Your explanations in the comments please)
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Erik Fair retweeted
Yes. Bio-risk exists today, from zoonotic outbreaks, accidents, and bio-terror. We know a great many things we can and should do to increase societal resilience, and have done almost none. Independent of how AI changes the risk, we should be doing the basics here. 1. Pathogen detection in waste streams, water supplies, and perhaps even indoor air. 2. Proactive design of template vaccines for every known virus family. 3. Pre-build vaccine manufacturing capability to have on standby. 4. Physical countermeasures: UV in the HVACs of all large buildings, airports, etc..; Stockpiling PPE. 5. R&D into new approaches like PCANS and other techniques that block viral transmission. These are all no-regret bio-defense policies that increase our resilience to natural pandemics, lab leaks, or intentional bio-attacks (AI augmented or not). Defense in depth.
Your position on AI should not affect your support for biodefense measures. Even if you do not think AI will make a difference, the problem is urgent today.
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