HN有多少是AI？

HN有多少是AI？
How much of HN is AI?

原始链接: https://lcamtuf.substack.com/p/how-much-of-hn-is-ai

作者对 Hacker News 抱有爱恨交织的情感，虽然经常有负面情绪，但仍将其视为重要的流量来源。最近，他们观察到网站内容发生了显著变化，人工智能相关内容占据了压倒性的地位。对 2026 年 2 月份的五条热门文章分析显示，大部分日期的至少四项内容都与人工智能相关。进一步使用 AI 检测工具 Pangram 的调查表明，这些文章中有很大一部分是由人工智能*撰写*的，该工具能够准确地标记出表现出大型语言模型典型风格模式的文章。作者指出，AI 检测并不需要检测“非人类”写作，而是识别当前 LLM 持续存在的风格特征。他们认为 Pangram 的发现是准确的，强调了一种令人担忧的趋势，即人工智能生成的内容正在饱和一个以前“极客导向”的平台。

## 黑客新闻与人工智能的兴起：摘要最近黑客新闻上的讨论集中在人工智能生成内容——包括帖子和评论——在该平台上的日益增加。用户们争论是否应该将人工智能相关内容单独分类，类似于 Reddit 的主题孤岛，但承认 HN 的理念抵制这种划分。担忧范围从对持续人工智能讨论的厌烦，到对在线互动未来的更深层焦虑。一些人担心人类写作风格会趋向于人工智能的“习惯”，而另一些人则质疑如果内容仅仅被算法消费，那么创作内容的价值何在。许多人认为，很大一部分新账户是机器人，可能出于未知目的操纵对话。有一种感觉是，HN 的重点已经发生了巨大转变，人工智能占据首页的程度甚至超过了加密货币热潮。这归因于人工智能投资的巨大规模，从而推动了关注和讨论。最终，这场对话凸显了人们对人工智能对在线社区的真实性和价值日益增长的不安。

原文

I have a complicated relationship with Hacker News. The site is the most important aggregator of geek news and a major source of traffic to this blog. At the same time, it has a fair number of toxic commenters, making it a dependable source of insults hurled in my general direction; if you want a taste, this article has been called “watered-down” and “slop”.

The site is run by geeks and for geeks, so it’s not immune to tech trends; for example, around 2018, it had a fair number of stories focused on cryptocurrencies and NFT. That said, the recent shift feels more profound: almost every day, it feels that the lineup is dominated by stories focused on AI, written by AI, or commented on by AI.

To get a sense of how much of the feed is occupied by AI-related topics — often vendor announcements — I took a sampling of the daily top #5 for February 2026:

So, yep. AI took four out of five spots on Feb 4 and Feb 12, plus arguably the entire line-up on Feb 5 (story #3 was submarine marketing for an AI vendor). The only days without LLM news in the top 5 were February 1 (with the first AI story at #7, then #9), February 9 (first at #8), and February 25 (with AI at #6, #9, #10).

For the second part of the experiment — to figure out which stories are likely AI-written — I tapped into Pangram. Pangram is a remarkably good, conservative model for detecting LLM-generated text. These detectors have a bad rep among techies, but the objections are often based on outdated assumptions or outright misconceptions. For the tools to work, AI writing doesn’t need to be in any way “inhuman”. It’s enough that the default voice of the current crop of LLMs is quasi-deterministic: ask for the same essay twice and you’ll get a stylistically similar result. The individual mannerisms are human-like, but it’s very unlikely that your writing combines the exact same set.

To validate the results, I also reviewed all the flagged stories and I think the findings make sense; if anything, Pangram had a couple of false negatives. To give you a sense of what was flagged, have a look at the #3 story on February 19 (“AI is not a coworker, it’s an exoskeleton”). In my opinion, it has a wide range of red flags.

HN有多少是AI？ How much of HN is AI?

HN有多少是AI？
How much of HN is AI?