GoKawiilA recent experiment testing the limits of noise-generation in diffusion models paired with verbs in the kinetic identification dataset, which has nothing to do with the topic of this post.
Against the Quantification of Integrity
When the measure of language becomes its target, it ceases to be good language.
💡 Nerd Rating: 1/5. I discuss the origins of certain linguistic tics in LLMs and what it means for writing, student assessment, and thinking.
"It's not x, it's y."
Large Language Models gravitate toward this type of construction, called negative parallelism. It has its uses: it sets up a contrast. It's useful, especially, for reframing assumptions: "You think it's like that, but it's really like this."
It's all over social media, especially on LinkedIn, and the construction has sparked a backlash amid an ongoing war against automated language production. If you use em-dashes – you might be a bot. If you describe things that delve, quietly, or genuinely (or create lists of three, like that one), you might be a bot.
Recent overuse by language models has led many to declare it bad writing. I'm not so sure. Nobody called JFK a lazy writer when he said, "ask not what your country can do for you – ask what you can do for your country." Negative parallelism is a rhetorical device, and any rhetorical device is only as lazy or inspired as what it contains.
Automated Language Production
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