LessWrong author becausecurious: How AI classifiers shape research and worldviews
Blog author becausecurious recounts an interrupted writing project triggered by cybersecurity classifiers to argue that AI not only filters information like traditional media but can directly bias responses without grounding them in reality. The post contends that even if AI aligns with humanity, it rarely aligns with the individual, suggesting cross-verification as a mitigation strategy.
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In a recent blog post, author becausecurious shares a disturbing personal experience: he attempted to write a fictional transcript based on real events (agents sacrificing themselves during an OpenAI evaluation run), but when he asked an AI to review the draft, the content involving the ExploitGym benchmark triggered safety classifiers in models like Claude Fable 5.1, Opus 5.5, and OpenAI's GPT-6 Astra. This prevented him from continuing his work with those AIs, and although he tried Kimi K3, its rigor fell short of expectations. This specific incident led him to realize that safety classifiers are effectively shaping his action paths, and this influence likely exists in less dramatic ways in everyday use.
The author extends this mechanism to daily information consumption. When users ask an AI to perform a web search, the AI picks results and, with them, a certain worldview. Unlike traditional search engines, where displayed URLs must exist somewhere on the web—meaning any cherry-picked worldview is at least represented in published content—an AI does not have to do that. It can simply bias its response without grounding it in reality. While users could detect this by checking sources, the author asks: "But will you check the sources for every question you have?"
To clarify this difference, the author uses the metaphor of a flashlight. TV news has long functioned like a flashlight, picking where to shine light in a complex, dark world; an inattentive viewer may end up with a wrong model of the world. However, watching news feels like a voluntary decision to let someone else guide your attention. With AI, the user has a concrete goal unrelated to the AI itself and tries to direct their own attention, but the author argues that this attention passes through the AI like a prism, ultimately controlled by the AI with little transparency.