Agile Governance: Tsinghua's Xue Lan on How China Regulates What It Can't Fully Predict

**SPEAKER_1** (0:00)
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**Kaiser Kuo** (0:36)
Welcome to this special edition of the Sinica Podcast, a weekly discussion of current affairs in China. Coming to you this week from Dalian, from the Davos On Air booth at the World Economic Forum's annual meeting of the new champions, also known as Summer Davos. In this program, we look at books, ideas, new research, intellectual currents, and cultural trends that can help us better understand what's happening in China's politics, foreign relations, economics, and society. Join me each week for in-depth conversations that shed more light and bring less heat to how we think and talk about China. I'm Kaiser Guo. For over 20 years now, I've had the distinct privilege of working with the World Economic Forum as an official writer.
This year, they've asked some podcasters to team up with them, to bring you shows both under the World Economic Forum banner and under the banner of their own podcast. I'm delighted to be able to do this this year. With Sinica, listeners, please support my work by becoming a paying subscriber at sinicapodcast.com.
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Technology has always run ahead of the rules meant to govern it. Scholars call this the pacing problem, the chronic lag between what innovators can do and what regulators have figured out how to actually handle. We've seen this with nearly every major new wave of technological innovation. Recent examples would include Uber and Airbnb, for example, or how regulation really had to catch up much earlier than that. You could go back to the advent of the automobile. Cars hit the roads before anyone had invented things like speed limits, or driver's licenses, or traffic lights, or even the concept of jaywalking. I was lucky enough to be in China and to have a front row seat to watch this whole thing unfold when the internet really took off in China in the late 1990s. In recent years, artificial intelligence has turned that lag into a real chasm, and nowhere is the dilemma more vivid than in China, a country trying to do two things at once that often can pull in opposite directions, to on the one hand unleash technological development at extraordinary speed, and on the other to keep that development firmly within bounds that the state can manage.
Out of that tension has come an idea, Agile Governance that has worked its way into the global policy vocabulary. The question I want to explore today is whether it's a genuine model that others can borrow or whether it's something so deeply rooted in China's particular system that it can't really be transplanted. And there's no better place to ask it than here in Dalian, and where this year's theme is innovating at scale. It makes the governance question really more urgent than ever because scaling at innovation, scaling innovation itself, also means scaling the risks of technology. So my guest is one of the people who has thought longest and hardest about all of this.
Xue Lan is Dean of Schwarzman College at Tsinghua University and because I've been involved with Schwarzman for many years, really since its inception, that's how I know Dean Xue best. But he's also Director of Tsinghua's Institute for AI International Governance. He's a Cheung Kong Distinguished Chair Professor with a doctorate in engineering and in public policy from Carnegie Mellon University in Pittsburgh. He chairs China's National Expert Committee on the Governance of Next Generation AI. And some of you may recall that he was one of those from China who spoke to Senator Bernie Sanders of Vermont on cooperation on AI governance back on April 30th of this year. Crucially for our purposes today, he is also one of the intellectual architects of this very concept of agile governance as a concept in Chinese policy making. So there are few people who are better placed to tell us what it really means and whether it travels. Dean Xue, it is a real pleasure to have you at last here in Dalian, and a warm welcome to Sinica.

**Xue Lan** (5:00)
Thank you. My pleasure.

**Kaiser Kuo** (5:02)
So Dean, let's start with the basic problem. Every regulator faces what's been called this pacing problem, technology evolving faster than the rules that can keep up with it. This isn't genuinely new, but it does seem newly acute.