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Ken Liu on AI and Freedom

this show was such a treat

Jordan Schneider, Phoebe Chow, and Irene Zhang
May 06, 2026
∙ Paid
This post originally appeared in ChinaTalk.

“The real danger from AI is that humans will start treating other humans as machines. It’s the gradual mechanization and reduction of humans into components of a machine — that is the relentless pattern of modernity.”

Ken Liu graces ChinaTalk with his presence. He is the author of the Dandelion Dynasty silkpunk fantasy series and a brilliant short fiction writer — one of his stories was recently adapted into Sam Altman’s favorite show, Pantheon. We all know his translation work on the first and third volumes of the Three-Body Problem trilogy, but even better was his absolutely brilliant translation and commentary of the Dao De Jing. As much as I hoped that project would get him fully on the classical Chinese translation train, he followed it up with a very different direction — a techno-AI thriller, All That We See or Seem, released late last year. Irene Zhang of ChinaTalk joins us to co-host.

In a wide-ranging conversation, Ken Liu argues that:

  • Technology is the most human thing we do — humans have always externalized our minds into the world and then allowed those creations to reshape who we are.

  • AI “slop” won’t stop humans from making art that matters, and the real distinction isn’t quality versus slop, but between desire-fulfilling machines and artists who draw from the collective unconscious.

  • The deeper danger of AI isn’t machines replacing humans, but systems that train humans to behave like machines.

  • Science fiction isn’t prophecy, but mythology — and ideologies are just mythology’s cheaper, hack cousins. Orwell, Shelley, Tolkien, and Le Guin endure not because they predicted the future, but because they gave us metaphors powerful enough to think with across generations.

  • Large language models are intelligent, but can’t be wise. Drawing on Laozi and Zhuangzi, Ken explains why everything that truly matters lies beyond language.

Listen now on your favorite podcast app.

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