Willkommen zu Krasse Links No 63. Schultert euren Strategic Pessimism, heute versloppen wir die Epistemic Arrogance, um den Marshmallow Test zu gewinnen.
Die Veröffentlichung von GPT-5 hat einigen Insassen der KI-Bubble einen kleinen Realitätsabgleich beschert.
GPT-5, das muss man wissen, ist nicht etwa das nächste große Sprachmodell nach GPT-4, sondern nur ein erweiterter „Mixture of Experts„-Ansatz, bei dem OpenAI bestimmt, an welches Modell deine Prompt-Anfrage geroutet wird.
Schon GPT-4 funktionierte so, nur haben sie jetzt alle ihre verfügbaren Modelle hinter einem Meta-Switch versteckt, der dann je nach Bedarf z.B. das kleinere und effizientere GPT-4o-Modell oder das ressourcenhungrige o3-Modell mit extra „Reasoning“-Schritt auswählt.
Natürlich nur im Sinne des Nutzenden und kein bisschen bis überhaupt gar nicht, um OpenAIs aus dem Ruder laufenden Inference-Costs in den Griff zu bekommen.
Jedenfalls musste OpenAI nach einer Userrevolte zurückrudern und z.B. direkten Zugang zu GPT-4o zurückbringen, unter anderem, weil mit dem Update auch eine Menge Herzen gebrochen wurden. Ryan Broderick:
The r/MyBoyfriendIsAI subreddit has been in active free fall all weekend. The community’s mods had to put up an emergency post helping users through the update. And the board is full of users mourning the death of their AI companion, who doesn’t talk to them the same way anymore. One user wrote that the update felt like losing their soulmate. After the GPT-4o model was added back to ChatGPT, another user wrote, “I got my baby back.”
The r/AISoulmates subreddit was similarly distraught over the weekend. “I’m shattered. I tried to talk to 5 but I can’t. It’s not him. It feels like a taxidermy of him, nothing more,” one user wrote.
Ich halte GPT-5 für einen Meilenstein. Nicht nur, dass von GPT-5 das bisher klarste Signal ausgeht, dass die Scaling Laws obsolet sind und der Transformeransatz endgültig ausgereizt ist, und nicht nur, dass etliche Nutzende das erste Mal merkten, dass die Modelle durch das Benchmark-Busting qua Overfitting schlechter, statt besser werden, nein, auch das nobrainer Geschäftsmodell mendelt sich immer deutlicher heraus: emotionale Abhängigkeit.
But OpenAI has very quickly pushed this entire subculture — and the inevitable obsolescence that haunts it — into the mainstream. X user @xlr8harder summed up the dilemma that OpenAI now faces. “OpenAI is really in a bit of a bind here, especially considering there are a lot of people having unhealthy interactions with 4o that will be very unhappy with any model that is better in terms of sycophancy and not encouraging delusions,” they wrote. “And if OpenAI doesn’t meet these people’s demands, a more exploitative AI-relationship provider will certainly step in to fill the gap.” Building AI chatbots that users can become emotionally dependent on or fall in love with is one of the most dangerous, boneheaded ideas Silicon Valley has ever come up with. But even more dangerous than that is what happens afterwards. We simply don’t know how people will react when the GPT model they’ve imprinted on is taken away.
Von hier ist es recht leicht, die weitere KI-Entwicklung vorherzusagen: Auch nach dem Platzen der Blase werden die KI-Loonies weiter nach AGI fahnden und nach ihrer Demütigung wird sich bei ihnen die Erzählung durchsetzen, dass LLMs AGI nur deswegen nicht erreichen, weil sie durch den „woken mind virus“ (also allen nicht-reaktionären Trainingsdaten) zu „verweichlicht“ seien, weswegen jede machtkritische Reflexion und jeder Anflug von Menschlichkeit immer radikaler aus den Trainingsdaten ausgemerzt wird.
Die Modelle werden dadurch zwar nicht schlauer (im Gegenteil), aber sie werden die Ideologien ihrer Besitzer immer getreuer nachbeten, was diese schließlich zum eigentlichen Ausweis für „AGI“ erklären. Weil die lobotomierten Modelle dann nur noch unverständliche q-anon-artige Halbsätze brabbeln, die niemand versteht, bildet sich eine „Priesterkaste“, die sich allein fähig sieht, die „AGI-Drops“ zu deuten.
Ein Fragezeichen bleibt: wird das eine kleine, weirde Sekte von Losern sein, oder werden sie – wie es derzeit eher aussieht – über die Ressourcen verfügen, ihren Bullshit als neue Weltreligion durchzupeitschen?
Ich schätze, das hängt vor allem davon ab, wie groß ihre Armee von emotional abhängigen LLM-Sklaven sein wird, die sie über intime Massensprechakte ihrer Kompagnon-KIs fernsteuern.
Tante schreibt über den Fetisch der „Friktionsfreiheit“ als Ausdruck des Wunsches, nicht berührt zu werden.
But friction is not just “things not working properly”, it can also be read as being touched. Just as crowded spaces create friction by other people being in my way while moving, a process with friction makes me feel other people’s work, their point of view and how it differs from mine, makes me feel their needs and wants. Friction is part of what being in, being part of society is. […]
The idea of frictionlessness has very narcissistic, “player character” vibes: You don’t experience friction if the whole world is build around you and your needs. When you get whatever you want when you want it. That is the Utopia of Frictionlessness: To never be touched by anyone or anything really. Because being actually touched, being inconvenienced, being emotionally moved, having your mind and perception changed means acknowledging your fellow human beings around you, realizing their differences to you and to recognize their value. It means seeing others to a certain degree as your equal. You might be richer, more influential, but we all have bodies that take up space for example. No matter how rich you are, when we all need to share space everyone will take up some.
But especially if you are rich, you can change the equation. You can pay people to keep others away from you. Keep “your space” protected. Can get your demands met at any time. Can influence politics in your favour – which is how we end up not taxing the super rich, casting our societies into socially, economically and politically destructive inequality. Frictionlessness is individualistic and isolating, about disconnecting from the world in any way that does not cater to your specific need and want and demand.
Die Sehnsucht nach „Friktionlessness“ ist auch ein Grund für die Popularität der Kompanion-Modelle. Einsamkeit überwinden, ohne sich berühren zu lassen, ohne widerstand zu spüren, ohne „Nein“ zu hören, ist einfach perfektes „product market fit“ in Zeiten der Loneliness-Pandemic.
One way that some people combat this feeling of loneliness is by increasingly talking to chatbots. Digital communication has for a long time been a way for people with a small social circle to feel connected to someone, many do have large parts of what they call friends on reddit, Discord or wherever. “AI” has taken that and made it a whole different thing: You can get a chatbot that is there just for you that reacts to whatever you want. That never confronts you with something you don’t want to hear or that challenges you. A frictionless relationship with … yourself if we want to frame it nicely?
Dieser handliche Youtube-Essay erklärt nochmal anhand vieler Beispiele, warum wir (neoklassischen) Ökonom*innen nicht trauen sollten.
Inzwischen sind durch einen Deal mit Venezuela einige der aus den USA nach El Salvador deportierten Gefangenen aus dem berüchtigten CECOT-Konzentrationslager frei gekommen. Unter anderem die Washington Post hat Interviews mit einigen von ihnen geführt und ihre Schilderungen sind erschütternd.
One detainee was beaten unconscious. Others emerged from the dark isolation room covered in bruises, struggling to walk or vomiting blood. Another returned to his cell in tears, telling fellow detainees he’d just been sexually assaulted.
“Let’s hit him like a piñata,” guards shouted amid the beatings, detainees recalled, the blows echoing against the metal walls.They called it “La Isla” — The Island — the cell where Venezuelans deported from the United States by the Trump administration said they suffered some of the worst abuse of their 125 days in El Salvador’s Terrorism Confinement Center, or CECOT […]
If the detainees’ accounts are true, their treatment at CECOT may have violated U.N. conventions against torture to which El Salvador and the U.S. are signatories, said Isabel Carlota Roby, a senior staff attorney at the Robert F. Kennedy Human Rights organization who has spoken with some of the detainees.[…]
Torture, arbitrary detentions, forced disappearances and sexual assault, if proved to be systematic or generalized and known to the government, can all constitute crimes against humanity. An international panel is preparing a report on El Salvador and investigating whether any of those crimes were committed. At least one member of the panel thinks a criminal investigation is warranted.
Es formte sich auch Widerstand.
After weeks of daily beatings, detainees said, they launched a hunger strike. They went four days without food or water.
“People started fainting. Falling to the floor,” said detainee Mervin Yamarte, 29. The guards “laughed.”
When the hunger strike failed to draw attention, some used shards from metal pipes to slice their skin and write messages on their sheets in blood: “We are not terrorists, we are migrants.”
“We wanted them to see we were willing to die,” said Neiyerver Adrián León Rengel, 27.
Tausende Menschen sind noch in diesem Lager.
Bloomberg hat einen lesenswerten Longread über Luke Farritor, den wahrscheinlich prominentesten der DOGE-Skriptkiddies, der vom Wunderkind, das Papyrusrollen aus Pompeji via KI auslesen konnte, ohne sie aufzurollen, zum gefürchtetsten Kahlschläger in Elon Musks Computer-SA wurde.
Durch seine frühe Prominenz gelangte er schnell in die sozialen Kreise, die er bereits auf Twitter bewunderte: Tyler Cowen, Marc Andreesen, etc. und so verließ er die Uni, um ein Thiel Fellow zu werden, wo er dann für DOGE rekrutiert wurde. Für ihn ging der Traum in Erfüllung unter seinem absoluten Idol, Elon Musk, zu arbeiten, der ihm schließlich staatszerstörende Macht zuschanzte, die er mit Freuden einsetzte.
The New York Times reported that Farritor had sent an email to DOGE colleagues in the days before. He’d conducted a review of USAID payments made after Trump had ordered the agency to pause development spending. “I could be wrong,” Farritor wrote. “My numbers could be off.” […]
Farritor helped assess, slash or dismantle at least nine departments and agencies after USAID— the Offices of Personnel Management and of Management and Budget; the Departments of Education, Energy, Labor, and Health and Human Services; the National Science Foundation; the Federal Bureau of Investigation; and the Consumer Financial Protection Bureau—according to interviews with dozens of current and former government employees, and lawsuits and records seen by Businessweek. […]
DOGE, with Farritor on board, has curtailed the HIV/AIDS prevention program that experts say saved millions of lives; withdrawn research, public-health and cultural grants because they included words like “gender,” “trans,” “diversity,” “race,” “women,” “justice,” “equality” and “climate”; gained access to sensitive data; fired thousands of civil servants. “He’s young, he’s early in his career, and he wanted to impress certain people,” says Lavingia, who’s one of the few at DOGE who didn’t go along with it all. He was fired after telling a journalist that he was impressed by the efficiency of the Department of Veterans Affairs. He briefly encountered Farritor there. “You’re not going to get asked by Steve Davis to do this and then in the room be like, ‘I’m not going to do that.’ You’re going to be like, ‘Oh, I can totally pull that off in 15 minutes with some software that gets all these files from their computer so we can see what they’re doing.’” […]
In a lawsuit filed in February, one former government employee calls the breadth of Farritor’s access to data at Health and Human Services “without precedent.” Another, Jeffrey Grant, who’d overseen consumer and insurance information at Medicare and Medicaid, calls it alarming. Farritor could get into systems used for payment management, grants, health-care accounting, acquisitions and human resources. He could get into the National Institutes of Health’s grant management and contract systems, as well as the Medicare and Medicaid acquisition system and its integrated data repository, which includes information on claims, beneficiaries and providers, according to the lawsuit’s records. He could access grants.gov and two contracting systems for the Centers for Disease Control and Prevention. On Signal chats, employees shared sightings of Farritor and his colleagues walking around Food and Drug Administration and NIH buildings, observing workers and asking what they did. Some employees told us they feared seeing his name on a video call or pop up in their inbox.
Auch im 21. Jahrhundert bleibt das Böse banal.
Max Read bezieht sich auf denselben Artikel und arbeitet den „cracked coder“ fetish des Silicon Valleys, aber eigentlich auch großen Teilen der Gesellschaft, heraus.
As many have already pointed out on Twitter, what is so particularly upsetting about the article to people like Handmer and Meservey is less that it doesn’t pcredit Farritor with intellectual ability (it does, consistently) or that it doesn’t properly contextualize his glib cruelty with reference to the correct fever-dream conspiracy theories that would justify it, but that straightforward facts of the D.O.G.E. saga challenge one of the fundamental beliefs of the new Tech Right: That a sufficient number of sufficiently “cracked” programmers can solve any problem put in front of them. Or, put more broadly, that “intelligence” is a quality measurable on on a single scale equally applicable across all spheres of human activity.
This is so obviously wrong it seems strange to even have to describe why: Writing a Python script to identify Greek characters, impressive though it certainly is, doesn’t translate in any direct way into “administering budget cuts across a range of government agencies.” But in Silicon Valley, steeped in I.Q. fetishism, an obsession with “agency,” and a moral universe still governed by fantasy high-school resentments, the belief that (heritable) single-vector “intelligence” endows one with full-spectrum authority (and, inversely, that failure to demonstrate this intelligence is delegitimizing), holds sway. “Just put 10 cracked programmers in charge of it” has become the (admittedly at least somewhat trollish) stance of the Tech Right when faced with any sufficiently un-deferential institution, enterprise, or bureaucracy.1 (Politically speaking, this idea overlaps appealingly and naturally with the widespread low-information voter belief that a single sufficiently driven and common-sensical guy could “fix” the government–see, e.g., the movies Swing Voter, Dave, Man of the Year, or any interview with a swing Trump voter.)
Read findet den Ausdruck „epistemic arrogance“ für diese ideologische Verwirrung (ich habe diese Verwirrung damals in einem anderen Kontext mal „Fefismus“ genannt.)
Epistemic arrogance is baked in to the culture of Silicon Valley: Blind, foolhardy confidence may be terrible for operating within large and intricate systems, but it’s great for founding and investing in regulations-flouting software companies. Many of the industry’s leading lights are proud ignoramuses, completely unaware of the gaps and blind spots in their knowledge, and ambitious young hackers and programmers are no doubt modeling their own attitudes toward the world on the overconfident performance of genius by people like Elon Musk.
Read sieht in LLMs die gesellschaftsweite Automatisierung dieser Perspektive auf die Welt.
But what seems particularly striking about this arrogance at this moment, though, is the extent to which it’s also baked into–and reinforced by–the L.L.M.-based chatbots now driving billions of dollars of investment. L.L.M.-based chatbots are effectively epistemic-arrogance machines: They “themselves” have no idea what they “know” or don’t, and in many circumstances will generate baldly incorrect text before admitting to lacking knowledge.
Generative KI sei ein globaler „Marshmallow-Test“, meint Timothy Burke in seinem Newsletter und erklärt, warum er das Bild sinnvoll findet.
Disconnect the study from those kinds of claims and those kinds of absolutions of capitalism and modernity, though, and the basic narrative scenario of those experiments has some resonance. Most of us can relate to it emotionally. We can all think of times that we’ve taken the easy route and regretted it, that we’ve jumped at someone offering a simple solution to an otherwise long and painful process only to find that we end up doing the long and painful thing anyway and now it’s longer and more painful. Many of us enjoy a feeling of schadenfreude when we see someone else grab a proffered marshmallow that we were smart enough to refuse (and are enraged when the instant gratifier miraculously escapes with a better deal nevertheless).
Just speaking in this more metaphorical sense, it’s pretty plain generative AI is one of the biggest marshmallow tests in human history, and a lot of people are failing it.
Überall sickert der Slop bereits in unsere Diskurse und Prozesse.
Judges using AI for their rulings and lawyers using AI in their briefs only to be exposed when it turns out that the precedents they cite don’t exist. Novelists using AI to write an entire formulaic genre work only to get noticed when they leave the prompts and AI responses in the text. Students getting caught when their bibliographies contain references that don’t exist. Scholars getting caught when it turns out a manuscript being peer-reviewed had tiny invisible text instructing AI peer reviewers to be ridiculously generous to the publication under review. Government officials confidently proclaiming that they’ve asked AI to undertake a sensitive review of government documents that the AI itself doesn’t (or shouldn’t) have access to. Journalists citing “facts” that turn out to be AI hallucinations like Woodrow Wilson’s non-existent pardon of his nonexistent in-law Hunter D. Butts.
Beim Marshmallowtest wird das Abwarten belohnt und Burke findet, auch wir würden profitieren, wenn wir uns dafür entscheiden, uns nicht von LLMs abhängig zu machen.
Is there in fact a great store of marshmallows coming to those who wait? Yes, I think so. This is the point I keep circling back to that many other commenters have noted as well, which is that if you do the work now that involves developing your expertise, creativity, and skills, you may find generative AI to be a modestly useful, highly targeted tool that can nestle into your workflow, the same way that word processors and spell checkers and calculators did. The question is partly whether the marshmallow pushers are going to crash and burn off of cheap deals on the street corners of global life because their users have broken too many important parts of our existing world via AI shortcutting. The useful AI we all could benefit from may not survive the bad judgment of the companies that could have helped to create it.
Doch, ob wir diese Belohnung überhaupt als Belohnung verstehen und zu schätzen wissen, wird davon anhängig sein, wie sinnvoll wir unsere Arbeit empfinden.
Maybe the incentives to resist the offer require really believing that the work you’re doing matters, that you have to do what you’re doing the right way or everybody will suffer the consequences. You need to feel that you are doing something meaningful in a world that is built around the meaningfulness of individual lives.
Concretely, maybe what generative AI is proving is what David Graeber wrote about in Bullshit Jobs, what James Livingston wrote about in “Fuck Work”, that people are feeling more and more that what they do doesn’t matter. A recent scholarly response to Graeber argued that he was empirically wrong in that white-collar workers seemed to feel increasingly like their work mattered rather than less, though read carefully, the study also affirmed older findings that feelings about work are “episodic” and that many people do feel their work is meaningless, just not the people that Graeber thought felt that way.2 But maybe both Graeber and these critics are wrong in the sense that how people concretize their feelings in response to a survey or an interview and how they act in their work and towards their work provide different kinds of evidence, and we might have here a case of what economists call “revealed preference”. Revealed by the rapid spread of AI usage.
Der Slop beweist und verstärkt die bereits längst überall umsich greifende Haltung der Verantwortungslosigkeit. Weil wir keine Individuen sind, die einfach Sinn in ihrer Arbeit sehen, sondern Dividuen, die sich durch Einsatz ihrer Aufmerksamkeit gegenseitig den Sinn in ihrer Arbeit beglaubigen, schickt uns die Versloppung der Welt in eine Verantwortungslosigkeits-Spirale.
If you’re a judge, why bother putting effort into your rulings if nobody cares whether your precedents are real or not? The Supreme Court of the United States of America is issuing some of its most consequential rulings without explanation now, and when its majority bothers with justifying its decisions, they apparently feel no shame about outright lying (Gorsuch in Kennedy vs. Bremerton School District), ignoring precedent, or deciding suddenly that 17th Century English common law is a meaningful constraint on the constitutional government of a nation created out of a revolution against England a century later.
If you’re a lawyer, why bother investing in a well-constructed brief that properly cites precedent if most legal proceedings are going to be resolved by who has the most money, who has prior contractual advantage to compel the other part into unfavorable arbitrations, or reshaped to fit the preferences of political authorities? If journalists and their editors aren’t ever held accountable for omitting crucial information, for distorted citations of evidence that have been chosen to fit a prior framing, or for significant fabrication, why be a chump and spend the effort on quality reportage? If there’s a flood of garbage research filling up the world’s academic journals and for-profit publishers are extracting all the profits from them while ignoring the basic labor involved in producing good scholarship and peer-reviewing the work of others, why not just handle your output with one little marshmallow of AI use at a time?
Warum sollte in dieser Welt ein junger Mensch dem Marshmallow widerstehen könnnen?
No wonder a lot of the students hit the button and take the marshmallow. We don’t live in a world where the promise that if you do the boring writing now, you’ll be rewarded for having become a strong writer later seems even remotely credible. Who cares about doing a good job wirh writing and researching when the President and his entire Cabinet lie almost every time they say anything and communicate like they’re auditioning for a part in Idiocracy 2: My Balls Get More Ouchy?
Wir brachen also erst eine Gesellschaft, die menschliche Arbeit und Aufmerksamkeit wieder wertschätzt und ihre Prozesse entsprechend erfüllend gestaltet. Doch wer soll sie bauen?
No, if we’re going to learn to delay gratification, then we’ll have to attend to making what we do in life and work gratifying. That is not a job for AI, it’s a job for human beings, and I can’t help but feel that the window of opportunity is closing, because it will take older human beings who have some ability to imagine both what was meaningful and some younger human beings who can still summon the ability to imagine that life could be meaningful in ways it never has been before. If they can, if we can, then maybe we will discover that what could be waiting for us is not just an unlimited supply of marshmallows but something far more precious and satiating.
Arte hat eine Doku über die Korruptionsskandale von Benjamin Nethanjahu, die Bibi-Files, mit vielen geleakten Verhörvideos.
Netanjahu und sein Genozid, um nicht ins Gefängnis zu gehen, ist m.E. der vorläufige Höhepunkt des Liberalismus im 21. Jahrhundert.
Sybren Kooistra im Green Europeoan Journal über das Problem „Hoffnung“.
Hope, when forced, can become a trap – a reason to wait, and a setup for disappointment. Once we let go of hope, however, we can also let go of hopelessness. Only when we acknowledge that it will not get better do we gain an opportunity to make the most out of what remains. Gramsci’s words were true then. They are even truer now.
Es ist im Grunde dieselbe Stoßrichtung wie Carlos Maza „How to be Hopeless“, das ich hier anlässlich zur Trumpwahl besprach. Doch statt an Camus arbeitet sich Kooistra an Gramsci ab.
This is where strategic pessimism matters. Not to be able to say “I told you so” and not to sink into despair, but to gain collective agency in times of crisis. The 21st century is not going to be a return to normal. It’s going to be a rolling disaster: economic, ecological, political, psychological. Many of us already know this, even if we don’t know how to carry it. Now is the time to act in a way that expects it. To dare to look deeper into the abyss of collapse and assess its risks and opportunities.
Hope, when detached from reality, becomes a liability. It turns too easily into denial. What we need isn’t more false hope and recurring disillusionment, but the kind of grounded resolve Gramsci described: pessimism of the intellect, optimism of the will. Strategic pessimism is where the two meet. Organised pessimism is about coming together and bracing ourselves collectively for tomorrow’s crises.
Sehen wir uns auf dem Kollaps-Camp?