AI 与写作2022thewalrus.ca编辑精选
机器人正在写诗，许多人分辨不出真假
Robots are writing poetry, and many people can’t tell the difference
导读
这篇文章讨论AI写诗能否与人类诗作区分，以及机器生成诗歌的质量；评论补充了GPT-3诗歌的样本、标题与正文的落差，并辩论不同创作类型被AI替代的难度。写作者可借此思考诗歌的可记忆性、创造性层级，以及提示、筛选和编辑在AI写作中的作者角色。
可以直接用的写作要点
- 01
判断AI写作别只看标题或单个样本，要回到足够多的文本，分别考察押韵、连贯、记忆点和整体统一。
- 02
好诗不只靠“像诗”的语言，还要有能被记住的独特意象与整体安排；评估自己的作品也可用这两条。
- 03
越明确、越机械的创作任务越容易被AI模仿；依赖个人视角、思想内容和复杂结构的长篇写作仍是更难替代的方向。
- 04
使用AI生成诗句时，提示设计、挑选和编辑本身就是创作的一部分，别把生成结果直接等同于完整作者表达。
HN 评论精选
评估AI诗要基于足够样本；GPT-3在押韵和统一性上有限，但个别作品仍可能鲜活难忘。
补充：若想看GPT-3写诗在原文粗略讨论之外还能做到什么，最好的来源仍是我自己的 https://www.gwern.net/GPT-3#poetry 页面。（其中还指出，GPT-3不会押韵，所以Andrew Brown的样本在能力展示上有点误导。）让我意外的是，文章既没提也没链到它，毕竟外面的GPT-3诗并不多……原文说GPT-3的诗“死气沉沉”，永远成不了“令人难忘的统一体”。我只想说，对我来说，像《Uber-Poem》或《The Universe Is A Glitch》这样的GPT-3诗，比我费劲读《纽约客》或《巴黎评论》里绝大多数诗更鲜活、更难忘。
gwern查看英文原文
FWIW, the best source of GPT-3 poetry, if you want to see what it can do beyond the cursory discussion in OP, remains my own https://www.gwern.net/GPT-3#poetry page. (Pointing out, among other things, that GPT-3 can't rhyme and so Andrew Brown's sample is a bit misleading about capabilities.) I'm surprised it's neither mentioned nor linked, since there is not that much GPT-3 poetry out there... OP argues that GPT-3's poems 'fall dead' and never become 'a memorable unity'. I will just say that for me, a number of GPT-3's poems like "Uber-Poem" (https://www.gwern.net/GPT-3#uber-poem) or "The Universe Is A Glitch" (https://www.gwern.net/GPT-3#the-universe-is-a-glitch) struck me as a good deal more lively and memorable than the vast majority of the poems I puzzle through reading the New Yorker or Paris Review.
标题夸大了“人们分不清”；专业经验能辨差异，好诗有难以替代的具体性。
尽管标题如此，文章其实对当前机器生成诗的质量相当怀疑，除了一些关于AI“必然”能写出人类水准诗歌的空话。我在文章里没看到哪里声称“许多人分不清”。标题常由编辑而非作者拟定，这个标题和正文脱节尤其大，我觉得作者有点冤。而且这类说法一深究往往站不住。比如常被转述的品酒研究：人们“分不清红葡萄酒和加了红色食用色素的白葡萄酒”。但我记得被试是一年级酿酒学学生；我敢打赌，(a) 他们能区分加了红色素的马尔贝克和普伊-富美，(b) 品酒经验更久的人也能区分。我还想到一个广播喜剧竞答节目，笑点是“bite the wax tadpole”，大家笑是因为这大概是人类文明中这四个词第一次以这个顺序出现。AI最终也许能写出合理的东西，但好诗有非常具体的东西……
frereubu查看英文原文
Despite the headine, the article is actually pretty sceptical about the quality of current machine-generated poetry, aside from some fluff about the "inevitability" of AI being able to write human-quality poetry. There's nowhere in the article that I could see which claims that "many people can't tell the difference." (Headlines are often written by editors rather than the writers themselves, and this one seems to have generated a particularly big disconnection between the two - I think the write has been hard done by here). Besides which, often with these claims if you dig into them they start to fall apart. There's one about wine tasting that's often circulated - a study where people "couldn't tell the difference between red wine and white wine with added red food colouring". But IIRC the people in the study were first-year oenology (the study of wine) students, and I bet you (a) they'd be able to tell the difference between a Malbec and a Pouilly Fumé with red food colouring and (b) people who'd been tasting wine for longer (i.e. people who had more experience) would be able to tell the difference. I'm reminded of a radio comedy panel game where the punchline to a joke was "bite the wax tadpole", and there was quite a bit of laughter around the fact that it was probably the first time in human civilisation that those four words had been used in that order before. AI may eventually be able to write something reasonable, but there's something very specific about good poetry ("good" is of course subjective) that I think is likely to always set it apart.
创作任务越明确、机械，越易被AI替代；高创造性长文本依赖思想、视角与结构，AI尚难企及。
在这件事和DALL-E 2之间，我一直在琢磨David Hilbert关于一个学生的老笑话：“作为数学家，他想象力不够。但现在他是诗人，一切都好了。”作为STEM和艺术都有经验的人，我不太介意说：有些“创造性”追求就是比另一些更有创造性。我的粗略论点是，创造性越高的一端，被AI攻陷所需时间越长。具象绘画归根到底多少是个机械问题，所以AI在那里迅速赶上人类并不奇怪。“画一只在海滩上吃冰淇淋的猫”是相当明确的要求，可接受解的范围也清楚。我认为像柏拉图《理想国》这样的长篇文字作品所体现的创造性，比普通绘画或短诗高得多。它不仅审美上美，还包含大量（当时）新颖的思想内容，经过作者个人视角过滤，并组织成精巧的逻辑结构。面对这类大规模创造性作品，AI甚至还没开始处理问题。
Jimmy查看英文原文
Between this and DALL-E 2, I’ve been ruminating on David Hilbert’s old quip about a student: “For a mathematician, he did not have enough imagination. But now he is a poet, and everything is fine.” As someone with experience in both STEM and the arts, I don’t feel particularly bad about saying that some “creative” pursuits are more creative than others, and my rough thesis is that the ones on the higher end of the scale are the ones that will take longer to fall to AI. Representational painting is, at the end of the day, a somewhat mechanical problem, so it’s not too surprising that AI is rapidly catching up to humans there. “Draw me a cat eating ice cream on the beach” is a fairly well-defined request with a clear range of acceptable solutions. I think the creativity exhibited in a long-form written work like say, Plato’s “Republic”, is of a much higher degree than your average painting or short poem. Not only is it an aesthetically beautiful work, but it contains a great deal of novel (for its time) intellectual content as well, filtered through the personal perspective of the author, and organized in an elaborate logical structure. When it comes to these types of large-scale creative works, AI hasn’t even begun to tackle the problem yet.
AI诗作往往是诗人设计提示、筛选结果后的产物，作者性在人机协作中不可忽略。
在一个例子里，美国诗人Andrew Brown让软件以一朵云俯视两座交战城市的视角来写。GPT-3交出一首押韵诗，开头不算不迷人：“我想我要开始下雨了。”Stephen Marche为《纽约客》撰稿时，给GPT-3布置了英语正典里也许最迷幻的诗：柯勒律治五十四行的《忽必烈汗》——1797年一场鸦片梦，写到一半被打断，从未完成。GPT-3的任务？续完残篇。它幻想出的内容如此精巧（“喧嚣止息，云被撕开，/月亮继续她庄严的行程”），不熟悉原诗的读者可能很难辨出柯勒律治到哪里结束、电脑从哪里开始。这不是机器人在写诗。这是诗人在用电脑。
tessierashpool查看英文原文
In one example, American poet Andrew Brown asked the software to take the perspective of a cloud gazing down on two warring cities. GPT-3 delivered a rhyming poem that began, not uncharmingly, with “I think I’ll start to rain.” Stephen Marche, writing an article for The New Yorker, assigned GPT-3 maybe the trippiest poem in the English canon: Samuel Taylor Coleridge’s fifty-four-line “Kubla Khan”—an opium dream interrupted in the middle of its composition in 1797 and never completed. GPT-3’s mission? Finish the fragment. What the program fantasized was so sophisticated (“The tumult ceased, the clouds were torn, / The moon resumed her solemn course”) that readers unfamiliar with the original poem might have had a hard time discerning where Coleridge ended and the computer began. This is not robots writing poetry. This is poets using computers.
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