ChinAI #124: China Standards 2035 — Coming Soon
A national standard framework for new generation AI
|Jeffrey Ding||Dec 21, 2020||2|
Greetings from a world where…
Third-tier newsletters cover product innovations, second-tier newsletters cover process innovations, first-tier newsletters cover technology standards.
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Feature Translation: China Standards 2035 ready to come out, this is the real key to Sino-U.S. tech competition
Last week, we covered localized substitution in Chinese software, which included a table, titled “Domestic and foreign ecosystem alliances in chips + operating systems” from Huaxi Securities Research Institute. Thanks to Kristy Loke for stepping up and translating it in full — now on page 5-6 of the full translation from last week.
Context: This week, we circle back to a previous Around the Horn pick that some readers had expressed interest in, from 智谷趋势 (zgtrend), which was the source of the feature translation on China’s North-South gap from a couple weeks back.
Article expresses the standard narrative about China Standards 2035, which goes like this:
First, China has lacked the “right to speak”/”discursive power” in writing the rules of the technological roads. Hence, China pays the second most in intellectual property royalties, which leads to a large deficit in trade in services. In the past, when China tried to challenge American-dominated standards with its own — most notably, the WAPI standard for wireless — Chinese experts were denied visas by the U.S. to attend key meetings. That’s not completely true, but that’s the version in the article. Here’s more context on what actually happened in the WAPI case back in 2004. Also, there’s more to technical standards-setting than zero-sum competition between great powers. In a commentary for NBR, I analyzed how China, the United States, and other countries are balancing priorities in their pursuit of technical standardization in data governance and artificial intelligence
Second, new technological revolutions provide an opportunity for China to lead in the formulation of new systems of standards. AI is key to this, so that’s why in mid-August, the Standardization Administration of China and other five departments jointly issued the "Guide to the Building of a National Standard Framework for New Generation Artificial Intelligence.”
Some nice, substantive indicators for China’s efforts to increase influence in digital standards-setting:
In recent years, the annual growth rate of China's submissions to the ISO and IEC (two leading int’l technical standards bodies) has reached about 20%. In 2019, China submitted a total of 238 proposals for ISO and IEC international standards, of which 150 were submitted to ISO, 77 were submitted to IEC, and 11 were submitted to the Joint ISO/IEC Information Technology Committee (JTC1) — this is the body where one of the most important AI standards bodies is housed (SC 42)
China has submitted 830 technical documents related to wire communication (有线通信 — how do you translate this?!) to the ITU, ranking first in the world, surpassing the total of the following three countries, South Korea, the United States, and Japan.
It’s important to keep all this in comparative context. When measured by national representatives at the chair or vice-chair positions at ISO and IEC technical committees, China’s influence has greatly increased but remains below that of other countries like the U.S. and Germany. As the article notes, these are very rough proxies for influence — at the end of the day, the best tech does carry a lot of weight even if it doesn’t always win, so the quality of technological standards is most important. The figures below support these two points — data from the Japanese Industrial Standards Committee.
One last thought for those who like meta-analysis. It’s notable how much international (esp. U.S.) coverage of China Standards 2035 has shaped this zgtrend article.
The opening quote cites Frank Rose, a senior researcher at Brookings, on the importance of standards for U.S.-China tech competition — which is essentially the frame of the article. It also quotes U.S. Attorney General Barr’s speech at a CSIS conference, Naomi Wilson’s excellent de-hyping of China Standards 2035 on the CFR blog, and many other international outlets like Foreign Affairs.
In fact, the only two Chinese voices quoted are Yan Xuetong, a prominent Tsinghua professor, and Dai Hong, director of the State Administration of China (SAC)’s Industrial Standards Second Department. Interestingly, I think I tracked down the Dai Hong quote in Dr. Ray Bowen II’s testimony (p. 21) before the U.S.-China Economic and Security Review Commission from earlier this year in March.
Why should we care? I think this fits in with a broader trend I’ve noticed in scanning through Chinese tech coverage every week. Many of the writers and platforms are very plugged in with what’s happening in the English-language landscape (e.g. articles that largely translate influential Twitter threads).
More in FULL TRANSLATION: China Standards 2035 ready to come out, this is the real key to Sino-U.S. tech competition
ChinAI Links (Four to Forward)
Very envious of this article by Jordan Branch in International Organization. It demonstrates the use of language — specifically, “cyberspace” as a “domain” for military operations — has expanded the military’s role in cybersecurity and bolstered support for the creation of a U.S. Cyber Command. Foundational metaphors matter.
Should-read: In AI ethics, “bad” isn’t good enough
Amanda Askell writes, “Lately I've been thinking about AI ethics and the norms we should want the field to adopt. It's fairly common for AI ethicists to focus on harmful consequences of AI systems. While this is useful, we shouldn't conflate arguments that AI systems have harmful consequences with arguments about what we should do. Arguments about what should do have to consider far more factors than arguments focused solely on harmful consequences.”
Should-read: Mapping U.S. Multinationals’ Global AI R&D Activity
New CSET analysis: Many factors influence where U.S. tech multinational corporations decide to conduct their global artificial intelligence research and development (R&D). Company AI labs are spread all over the world, especially in North America, Europe and Asia. But in contrast to AI labs, most company AI staff remain concentrated in the United States. Roxanne Heston and Remco Zwetsloot explain where these companies conduct AI R&D, why they select particular locations, and how they establish their presence there. The report is accompanied by a new open-source dataset of more than 60 AI R&D labs run by these companies worldwide.
Should-reread: ChinAI #120 Singles Day and the Making of Alibaba Cloud
I want to re-up this ChinAI issue from last month with some reactions from Cooper Pellaton, a student at Georgia Tech who’s worked at Alibaba. He’s an alumni of Alibaba’s DAMO Academy so he reached out after reading the issue. Thanks to Cooper for sharing his inside view on DingTalk, which is Alibaba’s “Slack-like” enterprise communications platform:
“Overall, I think DingTalk is really underrated but it’s definitely part of a larger toolchain at Ali. Things that worked successfully there which I haven’t seen anywhere else were integrated project management/time tracking/and version control system. Everything rolled into one means it’s a one stop shop for work (also easy request to other teams code/projects). Enterprise software is different in China and deserves to be studied in its own right.”
More details on DingTalk, which he calls a “great, but not so great” product:
Real-time translation. In beta while I was at DAMO, you can message with people in your native language and all the translation is done seamlessly. Nice because while there are very few foreigners at Ali, you occasionally need to refer to things in your native language.
Deep integrations. Features mini-apps like in Slack or WeChat. We could read AliMail, see package delivery, etc. all in chats.
No statuses or calendars. Because most meetings are made informally and no one uses emails, having a daily “calendar” or schedule is impossible. Meaning finding your coworker is always a puzzle.
Employee discovery is terrible. Very difficult to find your coworker when the contact cards are tiny and lack information - a bigger problem then you’d imagine.”
Thank you for reading and engaging.
These are Jeff Ding's (sometimes) weekly translations of Chinese-language musings on AI and related topics. Jeff is a PhD candidate in International Relations at the University of Oxford and a researcher at the Center for the Governance of AI at Oxford’s Future of Humanity Institute.
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Any suggestions or feedback? Let me know at firstname.lastname@example.org or on Twitter at @jjding99