📢China just released its much-anticipated regulation on generative AI.
🧵below w/ my initial notes/reactions.
TLDR: the final version is *much* less strict than the April draft version. This reflects a very active policy debate in 🇨🇳 + econ concerns.
https://t.co/fblFYZ5bVbcac.gov.cn/2023-07/13/c_1…
2/x Scope: Article 2 dramatically narrows the scope of AIGC activities covered. The draft version included R&D, general use of AIGC, and provision of AIGC services to the public.
This version cuts R&D and general use, and covers just providing AIGC to public. *Big* change
3/x Training data:
Lowers requirements from (impossible) demand that you adopt measures to "ensure" truth of training data, to more reasonable demand that you "elevate the quality" & strengthen truthfulness, etc
Tranlsation of draft by @ChinaLawTransl8 https://t.co/89hC5UEELdchinalawtranslate.com/en/gen-ai-draf…
4/x AIGC outputs:
Softens requirements from the (impossible) demand that AIGC outputs "shall be true and accurate", to requiring providers increase accuracy, reliability, etc.
Also, divides things by service type so AIGC sci-fi images don't need to be "accurate".
5/x Lots more to say on specific requirements but I'm short on time so couple big picture things.
#1 This regulation is explicitly "provisional" (暂行). Chinese regulators are taking an iterative approach, trying things out, getting feedback, making changes. More to come here.
6/x CAC was the sole author of the draft regulation (as it has been for all AI regs), and we got 6 more orgs co-signing this one.
Many were expected (S&T, etc), but its notable that the NDRC is listed second. Reframes it from a purely technical/information reg to an econ one.
7/x In terms of why the requirements have softened, there was lots of active debate and pushback (or suggestions for improvement) on the draft from Chinese academics, policy analysts and companies. The economy is also a huge concern right now, and that was def a factor.
8/x To learn more about China's AI governance regime, and how the country actually sets AI regulatory policy, give my recent (this week!) report on exactly that.
https://t.co/cQzqaKJIqscarnegieendowment.org/2023/07/10/chi…
9/9 Lastly: I'm not a lawyer or a professional translator, and these are very off-the-dome takes. Welcome all corrections.
Look out for proper translations by @DigiChn @ChinaLawTransl8
And analysis from many others, including @kendraschaefer @hlntnr and many more. 🫡
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Back in 2017 I started wondering what 🇨🇳 scientists & policymakers thought about AI safety. I asked around, didn’t find much. I’ve followed this closely since but been skeptical it’s getting real attention.
2/ Few years ago it was rare to see Chinese research / public discussion of AI safety. There were exceptions, w/ influential scientists like Gao Wen talking about AGI risks, & Ministry of S&T docs referencing "ensuring human control over AI."
But these were far from mainstream.
3/ ChatGPT changed that (similar to 🌎). Starting in 2023 some of China’s most influential AI/computer scientists expressing AI safety concerns. These were members of the elite scientific community, advisers to the gov on AI.
In China, academics hold more sway than biz execs👇
But “China” or even “the Chinese government” isn’t one thing. Several different ministries are angling to lead on Chinese AI governance at home & internationally.
Short 🧵 on what we do/don’t know, about those bureaucracies:
1st, to dispel common myth: Not all 🇨🇳 AI governance comes directly from Xi Jinping. Xi gives high-level guidance & nothing happens if he explicitly opposes it.
So who are key players in Chinese AI governance?
Cyberspace Administration of China (CAC) = lead internet content regulator + main author of all 3 existing Chinese AI regs.
Ministry of S&T (MOST) = leads R&D policy, promotes its own (soft-law) AI gov approach
MoFA = public face
A key Chinese standards body released a draft standard on how to comply w/ China's generative AI regulation. It tells companies how to red team their models for illegal or "unhealthy" information.
🧵 on a fascinating document:
First, the context:
China has been rolling out regulations on algorithms & AI for ~2 years, including a July regulation on generative AI.
I’ve spent the 1.5 years trying to answer two questions: 1. What is China doing on AI governance? 2. Who are the key players, and how do 🇨🇳 AI regulations actually get made?
China's AI regs will shape the technology’s trajectory in China & around 🌍.
They'll be “default settings” for their AI exports (LLMs in Indonesia, AVs everywhere). As 🇺🇸+🇨🇳 systems interact more we need to understand each system's safeguards.
Bonus: we can learn sth. (2/10)
If we can understand how China sets AI regs, maybe we can predict what's next. To do that I used a fun methodology: Reverse Engineering.
We took specific requirements/terminology in the regs & traced them back to their roots in Party docs, academic papers, public pressure (3/10)
I strongly recommend reading this intro to generative AI regulation from @AlexCEngler.
I'm going to share a couple highlights + thoughts below, and would love to hear from others on this. Mini-🧵 brookings.edu/blog/techtank/…
Impt section on AI value chain, and the different capabilities + responsibilities of upstream vs downstream developers. This is complicated & will crop up in more and more AI regulatory issues.
Trends in "watermarking" AI-generated content got me thinking:
1. Seems like a good topic for technical standards bodies, w/ effectiveness depending on how widely models proliferate 2. Watermarks = more sophisticated version of 🇨🇳 requirement that AIGC have "conspicuous label"