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When the Algorithm Gets Lost

CET-4

When Douyin's recommendation algorithm failed for a night, users realized how much they depend on it.

语速点单词查词 · 点 ▶ 听句子

On the evening of August 31, something strange happened on Douyin, one of China’s most popular short video apps. Many users suddenly saw videos that had nothing to do with their interests. The topic Douyin recommendations are terrible quickly became the number one hot search on Weibo, with over 550 million views.

This event makes us think about how much we depend on recommendation algorithms. Every day, when we watch videos, shop online, or read news, the algorithm quietly studies our behavior. It learns what we like and keeps sending us more of the same. This is convenient. We can find interesting content without searching. But it also has a downside. If we only see what we like, we may fall into a filter bubble. We stop seeing different ideas, and our world becomes smaller and smaller.

The one-night failure of the algorithm was like a small wake-up call. It reminded us that algorithms are made by humans and are not perfect. They can make mistakes. More importantly, we should not let machines decide everything we see. It is a good idea to sometimes explore new topics, read different opinions, and step out of our comfort zone.

Technology should serve us, not control us. The next time your phone suggests a video, remember: it is just a tool. The real choice is always in your hands.

Words to know:

长难句拆解 · what 名词性从句与 if 条件句

① Many users suddenly saw videos that had nothing to do with their interests. 主干是 Many users saw videos(许多用户刷到了视频)。that had nothing to do with their interests 是定语从句修饰 videos;have nothing to do with 是固定搭配,译作「与……毫无关系」,反义表达是 have something to do with。否定词 nothing 直接内嵌在搭配里,比 not…anything 更地道。

② If we only see what we like, we may fall into a filter bubble. 主干是 we may fall into a filter bubble(我们可能掉进信息茧房)。If 引导条件状语从句;从句里 what we like 是 see 的宾语从句,what 相当于 the things that,既起连接作用又作从句宾语;主句用 may 表示可能性,语气比 will 弱,是议论文留余地的常用手法。

同义替换 · 雅思阅读利器

定位的关键,是识破题目对原文的「同义改装」。先抓题干里的信号词,再回原文找变体,命中率会高很多。本文可迁移的替换组:

  • had nothing to do with → were unrelated to(与……无关高频)
  • the number one hot search → the top trending topic
  • depend on → rely on
  • fall into a filter bubble → get trapped in a filter bubble
  • makes us think about → prompts us to reflect on
  • smaller and smaller → increasingly narrow
  • step out of our comfort zone → break out of our comfort zone
阅读自测 · 3 题
  1. 判断(T / F / NG) — Over 550 million people viewed the hot topic on Weibo.
  2. 简答(不超过 6 个词) — What may we fall into if we only see what we like?
  3. 判断(T / F / NG) — The writer believes technology should control us.
参考答案与解析
  1. NG — 原文只说「over 550 million views」,浏览量不等于浏览人数,题干把 views 偷换成 people,无从判断,属「偷换概念」。
  2. A filter bubble. — 用 if we only see what we like 定位第二段,原词「a filter bubble」就是 fall into 的宾语。
  3. F — 原文落点是「Technology should serve us, not control us」,题干只留后半句并去掉否定,属「正反混淆」。
中文译文

8月31日晚,中国最热门的短视频应用之一抖音发生了怪事。许多用户突然刷到与自己兴趣毫不相干的视频,话题「抖音推荐烂透了」迅速登上微博热搜榜首,阅读量超过5.5亿。

这件事让我们思考自己对推荐算法依赖有多深。每天看视频、网购或读新闻时,算法都在悄悄研究我们的行为,学着投其所好、不断推送同类内容。这很方便,不用搜索也能发现有趣内容,但也有弊端:如果只看自己爱看的,我们可能掉进过滤气泡,渐渐看不见不同观点,世界越缩越小。

算法这一夜的失灵如同一次小小的警钟,提醒我们算法由人编写、并不完美,也会出错。更重要的是,我们不该让机器决定自己看到的一切。偶尔探索新话题、阅读不同观点、走出舒适区,不失为良策。

技术应当服务人,而非控制人。下次手机给你推荐视频时请记住:它只是个工具,真正的选择权始终在你手里。