一篇发表在Hacker News上的评论文章指出，AI生成的文本存在严重的可读性问题、缺乏上下文和个人声音等问题。1根据文章引用的数据，78%的读者在识别出文章由AI辅助或AI创作后会停止阅读，71%会避免阅读该作者的未来内容。1更值得注意的是，98%的读者倾向于接受作者自己撰写的文章，即便存在缺陷，也优于AI无灵魂的改写版本。1
作者强调有意义的写作应体现作者的思维、经历和个人特色，而非机械摘要。1在学术论文写作中，作者分享了AI的恰当用途——AI可用于验证技术细节、完成引用、检查拼写和语法，但从不应被用于生成段落内容。1作者指出，AI最成功的应用场景是撰写摘要，因为这是"最简洁、机械、非人性的部分"。1
对此观点的支持来自业界声音。Bryan Cantrill曾指出，"使用LLM进行写作就是违反了写者与读者的社会契约"。1哲学家Iain McGilchrist也表示，"越重要的东西，我们越要努力将其转化为语言"。1
An author has published criticism of AI-generated text on Hacker News, arguing that such content lacks readability, contextual understanding, and personal voice, and advocating for humans to maintain original writing practices 1. Research cited in the piece reveals that 78% of readers stop engaging with articles once they identify AI assistance or authorship, while 71% actively avoid the author's future work 1. Furthermore, 98% of readers prefer writing authored by humans themselves, even if flawed, over soulless AI rewrites 1.
The author shares practical experience using AI as an editing tool in academic writing, employing the technology to verify technical details, complete citations, check spelling and grammar, and format documents—but explicitly never for generating paragraph content 1. According to the author, AI's most successful application is writing abstracts, described as "the most concise, mechanical, and inhuman part" of academic work 1. The piece includes a quote from Bryan Cantrill asserting that "using LLM for writing violates the social contract between writer and reader" 1, and references philosopher Iain McGilchrist's observation that "the more important something is, the harder we must work to convert it into language" 1. The author suggests adopting tools such as the ASD-STE100 simplified technical English standard and Pangram detection utilities to improve AI writing quality 1.
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