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From Bruce Schneier: "All it takes to poison AI training data is to create a website:

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    @mathieui@piaille.fr Thanks for engaging with this. I appreciate the pushback, and I think some of your concerns are worth taking seriously. That said, I want to clarify something about my position: TGPL (or any specific licensing mechanism) is just one possible avenue among many. The broader argument isn't tied to any single instrument. Regulatory pressure on governments to mandate that models trained on public data be returned to the public, expanded public funding for open research infrastructure, international treaty reform—these are all on the table. The point is strategic pluralism, not a bet on one tool. On the copyright concern: yes, major players have shown contempt for copyright. But that's precisely why I think purely technical or market-based solutions are insufficient, and why political and legislative pressure matters. The history of generic medicine access is instructive here—no single mechanism won that fight, but the combination of compulsory licensing advocacy, treaty pressure, and public funding reform produced real change over time. Now, your Luddite parallel: I actually think it argues for my position rather than against it. You're right that the weavers never reclaimed the technology. But the lesson I draw from that isn't “therefore reclamation is impossible.” It's that refusing or destroying the means of production doesn't work. What eventually produced change was organized labor movements that took the existence of that technology as a given and fought over who controls it and under what conditions. That's exactly the kind of struggle I'm advocating for here. The real question you're raising, I think, is about the subject: is there an organized political force capable of carrying this through? That's a fair and hard question. But it's an argument for building that force, not for abandoning the goal.
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    @77nn @pluralistic > puoi usare una AI per tradurloLOL
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    🤖 Grok è sotto un’altra indagine in UE (ancora).Motivo: generazione di immagini intime non consensuali.Secondo un report, in 11 giorni sarebbero state create circa 3 milioni di immagini sessualizzate.23.000 coinvolgerebbero minori.L’Irlanda ha aperto un’inchiesta su #X per verificare la conformità al #GDPR.Prima c’erano già state mosse da parte di Francia e Regno Unito.Qui l'articolo originale: https://mashable.com/article/elon-musk-x-grok-eu-investigation-ireland-ai-generated-nonsconsensual-imagesQuando #GrokImagine è stato lanciato, diversi osservatori avevano notato che i sistemi di protezione contro i #deepfake sessuali erano deboli - per usare un eufemismo, ecco.Non assenti. Ma deboli.Deboli.Come uno dopo l'influenza.Debole.A dicembre scorso, molti utenti hanno iniziato a testare i limiti di Grok, con richieste di immagini di persone reali.Immagini intime generate SENZA consenso, di celebrities, persone reali e "altro" - mi fa schifo solo a pensarlo!È lì che la cosa è diventata ingestibile.E #X che ha fatto? Una cosuccia: ha cambiato policy, messo restrizioni (alcune) e, ovviamente, vietato immagini sessualizzate di persone reali.Ma.. ma per i regolatori europei conta il tempo tra il problema e la correzione stessa.Ora, la domanda tecnica è: se un #LLM genera contenuti illegali perché può farlo, è un bug? Un abuso? O una scelta progettuale troppo permissiva?Costruire un sistema generativo, vuole anche dire saper decidere/prevedere quali abusi saranno possibili.Di chi è allora la colpa?
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    @treyhunner I work for a big tech with a lot of LLM availability. It actually *has* helped my Python programming. We are also forced to use it for text generation for things like quarterly goals, employee reviews and more. It is useful but requires a critical user and is never a shortcut. That said, as a human, I value process over product, and I think LLM represents everything wrong about capitalism and how it regards human beings.