Why AI writing is so generic, boring, and dangerous: Semantic ablation.
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Why AI writing is so generic, boring, and dangerous: Semantic ablation.
(We can measure semantic ablation through entropy decay. By running a text through successive AI "refinement" loops, the vocabulary diversity (type-token ratio) collapses.)
https://www.theregister.com/2026/02/16/semantic_ablation_ai_writing/
@cstross Neural networks, by mathematical nature, are lossy information-compressing artefacts !
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Why AI writing is so generic, boring, and dangerous: Semantic ablation.
(We can measure semantic ablation through entropy decay. By running a text through successive AI "refinement" loops, the vocabulary diversity (type-token ratio) collapses.)
https://www.theregister.com/2026/02/16/semantic_ablation_ai_writing/
@cstross No surprise that we see the textual equivalent of mad cow disease.
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N Marianne shared this topic
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Why AI writing is so generic, boring, and dangerous: Semantic ablation.
(We can measure semantic ablation through entropy decay. By running a text through successive AI "refinement" loops, the vocabulary diversity (type-token ratio) collapses.)
https://www.theregister.com/2026/02/16/semantic_ablation_ai_writing/
@cstross ironically got a Google cloud genAI and ML ad right in the middle of that.
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Why AI writing is so generic, boring, and dangerous: Semantic ablation.
(We can measure semantic ablation through entropy decay. By running a text through successive AI "refinement" loops, the vocabulary diversity (type-token ratio) collapses.)
https://www.theregister.com/2026/02/16/semantic_ablation_ai_writing/
@cstross hmmm, that might also explain why AI seems more effective for code.
For the most part you want a reversion to the mean in code. Novel solutions are only needed at the cutting edge where you trying to make the computer do something that’s not been done before. -
@cstross hmmm, that might also explain why AI seems more effective for code.
For the most part you want a reversion to the mean in code. Novel solutions are only needed at the cutting edge where you trying to make the computer do something that’s not been done before.@Jmj Yes. Also I suspect the semantic expressiveness of programming languages is far narrower than that of human languages: they're more precise, but it's much harder (though not impossible!) to write poetry in them. So there's less risk of losing something unique by generating output that tends to occupy the middle of the bell curve.
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@Jmj Yes. Also I suspect the semantic expressiveness of programming languages is far narrower than that of human languages: they're more precise, but it's much harder (though not impossible!) to write poetry in them. So there's less risk of losing something unique by generating output that tends to occupy the middle of the bell curve.
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Why AI writing is so generic, boring, and dangerous: Semantic ablation.
(We can measure semantic ablation through entropy decay. By running a text through successive AI "refinement" loops, the vocabulary diversity (type-token ratio) collapses.)
https://www.theregister.com/2026/02/16/semantic_ablation_ai_writing/
@cstross "Model collapse", Shumailov, Shumaylov & Papernot (2024), Nature : https://www.nature.com/articles/s41586-024-07566-y
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@Sassinake @cstross
"duck speak" -
Why AI writing is so generic, boring, and dangerous: Semantic ablation.
(We can measure semantic ablation through entropy decay. By running a text through successive AI "refinement" loops, the vocabulary diversity (type-token ratio) collapses.)
https://www.theregister.com/2026/02/16/semantic_ablation_ai_writing/
@cstross I am sitting in a room different from the one you are in now. I am recording the sound of my speaking voice and I am going to play it back into the room again and again until the resonant frequencies of the room reinforce themselves...
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