Feed Curation

Feed curation is the practice of deliberately shaping the information and social streams that train attention, judgment, and desire. In E45 孟岩对话李继刚：人何以自处, Li Jigang / 李继刚 describes cutting thousands of WeChat contacts down to a smaller set, watching only a few people’s posts, limiting public accounts and RSS feeds, and using paper books and AI-processed papers as higher-signal inputs.

The episode’s rule is that a lower-level constraint can create higher-level freedom. Restricting the feed looks like less input, but it can create more thinking room, deeper relationships, and more legible memory. Meng Yan / 孟岩 summarizes the point as “your feed is your fate”: the material that repeatedly enters attention becomes part of who the person is becoming.

154.四十岁感言：不做那只温水里的青蛙 adds 大卫翁’s midlife autonomy version. He notices heavy phone use and worries that feeds plus AI can make attention reactive, while also describing the deliberate act of listening to opposing or unfamiliar worldviews as a way to test the limits of one’s own frame without surrendering judgment.

159.算法的六副面孔：它是如何从处理数据，变成定义我们是谁的 adds a platform-comparison response. The episode accepts that each algorithmic feed has bias, but argues that using multiple platforms, long audio, books, and conversation can make those biases visible to the user instead of allowing one filter to become the whole world.

Feed curation extends Attention Industrialization from critique to practice. If platforms and AI systems can industrialize mental intake, the user needs active input governance rather than relying on willpower after the feed has already been optimized against them.

164.算法的“兔子洞”：为什么你总在看完新闻后滑向娱乐？｜对谈黄圣淳教授 adds a feedback-specific rule through Algorithmic Media Literacy / 算法媒介素养. Curation is not only choosing who to follow; it includes noticing when anger, correction, or curiosity is about to become a signal in a Platform Feedback Loop / 平台反馈循环, and sometimes refusing to click or comment so the feed does not learn the wrong thing.

167.柏拉图、卢梭、哈耶克、阿伦特四大哲学家会如何解释算法时代？｜串台独树不成林 adds a philosophical reason for curation. If feeds are caves and rankings invite reason outsourcing, then comparing platforms, seeking context, and using search or long-form media become ways to notice the projection mechanism.

Key Claims

• A feed is not a neutral stream; it trains what the person notices, wants, fears, and remembers.
• Fewer high-signal inputs can produce more freedom than abundant low-signal inputs.
• Social curation can make people visible again instead of turning contacts into undifferentiated noise.
• Feed design connects to Personal Knowledge Ecology because inputs become notes, questions, memories, and future frames.
• AI-era speed makes feed curation more important because models can multiply whatever input diet the user provides.
• Episode 154 adds that curation includes choosing when to expose oneself to disagreeable views for worldview testing, not only reducing noisy inputs.
• Episode 159 adds that comparing multiple algorithmic filters can be a curation method when the user treats difference as evidence.
• Episode 164 adds that withholding feedback from rage bait and entertainment drift can be a deliberate curation move.
• Episode 167 adds that curation can be cave-awareness: one cannot leave all mediation, but can keep one filter from becoming the whole world.

Connections

• Attention Industrialization — platform-level problem feed curation responds to.
• Autonomy Under Information Flow / 信息流中的自主性 and Information Cocoon / 信息茧房 — episode 154’s autonomy and worldview-testing extension.
• AI Use Pacing — practical discipline for limiting AI and information overrun.
• Human Agency Under AI and Wet-State Human Agency — agency requires chosen inputs and protected volition.
• Personal Knowledge Ecology and AI-Assisted Reading — curated inputs feed the user’s knowledge system.
• Flow Environment Design — adjacent method of shaping environment so attention can settle.
• Rumination Vs Reflection — input noise can feed rumination instead of useful thought.
• Algorithmic Diversity Dividend / 算法多样性红利, Public Relevance Algorithms / 公共相关性的算法, and Information Cocoon / 信息茧房 - episode 159’s platform-comparison and anti-cocoon extension.
• Algorithmic Media Literacy / 算法媒介素养, Platform Feedback Loop / 平台反馈循环, Affective Polarization / 情感极化, and Algorithmic Entertainment Redirect / 算法娱乐重定向 - episode 164’s feedback-aware curation extension.
• Algorithmic Cave Allegory / 算法洞穴隐喻, Algorithmic Reason Outsourcing / 算法理性外包, and Algorithmic Diversity Dividend / 算法多样性红利 - episode 167’s political-philosophy curation extension.