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All Fall 2026 projects

AI safety news & research in Chinese (AI 安全科普)

Communications Generalist

Create articles, infographics, or videos in Chinese for broad audiences.

About the project

New developments in AI safety and governance research are sometimes only covered in English and receive limited high-quality coverage in Chinese. This project aims to fill that gap.

In this project, mentees will create accessible, engaging content in Chinese that explains new ideas in AI safety and governance. This could take the form of blog posts, infographics, or short videos on a variety of popular platforms.

Mentees will be self-directed and will choose their own topics and formats.

Theory of change

Great research communication in Chinese enables a broader audience to engage with ideas in frontier AI safety and governance.

Your role

See above

Prerequisites

Native-level Chinese

Can explain AI topics in Chinese for general audiences clearly and accurately

Knowledgeable about AI safety or governance

Application question(s)

For all questions, answer in Simplified Chinese.

  1. Please link to a writing sample in Chinese. This can be casual or formal, preferably about AI.
  2. Browse https://metr.org/zh-Hans and explain one of the ideas there in a simple, accessible way (150 characters)
  3. What AI safety or AI governance topics would you be excited to communicate? What platforms and formats would you like to try?
  4. Optional: If you have experience creating content for a general audience in Chinese, tell us briefly about it and share any relevant links.
  5. Optional: Share a link to a short, unscripted video of yourself explaining a topic in AI safety in an engaging manner. No need to worry about production quality.

About the mentors

Michael Chen

Michael Chen

University of Oxford

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DPhil Affiliate of the Oxford Martin AI Governance Initiative

Yilin Huang

Yilin Huang

MATS

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Yilin Huang is a MATS Scholar researching US-China AI governance and coordination, specifically focusing on how different Chinese actors frame recursive self-improvement. She previously researched AI R&D automation risk thresholds at the University of Chicago Existential Risk Lab. She also directs AI Safety at Amherst and is translating & facilitating the first frontier AI governance course in Chinese.

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