ChinAI #167: Progressive AI Policy
Why China's AI talent base must include migrant workers
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Feature Translation: More urgent than master’s and PhD graduates entering factories is the “reskilling” of migrant workers
Context: Migrant workers, who have moved from rural areas to join the urban workforce, make up about 1/3 of China’s working population. This week’s 文化纵横 (Beijing Cultural Review) article, by Wei Chen, a professor at Nanjing University, and Hui Xu, a PhD student at the University of Jena, examines the re-skilling of migrant workers as China’s manufacturing sector confronts digital transformation and automation. While formulating high-end industrial policies and investing in technologically advanced machinery is important (and attracts most of the headlines), Chen and Xu argue that China must also “implement progressive public policies,” which include improving the quality of vocational education for migrant workers — a key channel for social mobility.
Key Takeaways:
Automation, intelligentization, and manufacturing skill adjustments
There’s an urgent need to address a “skills shortage.” Senior welders, maintenance electricians, and industrial robot system operators are all featured in catalogues of occupation shortages published by local governments. See ChinAI #78 on the shortage of 20 million technicians for automating manufacturing.
“Replacing human workers with industrial robots” (机器换人) could widen the income gap between low-skilled and high-skilled workers, so China needs to develop a more inclusive national skills formation system. The risk of “technological unemployment” is higher for migrant workers.
Possible solutions? Past studies show that increasing the number of years of education, apprenticeship experience, and participation in skill training can improve the employability of migrant workers.
One channel is via company-sponsored trainings. The authors surveyed 111 workers in the industrial robot sector who had participated in skills training. About 94% of respondents believed that their technical and operational capabilities improved after participating, and nearly 80% of respondents believed that these trainings enhanced their employability.
Still, company-sponsored trainings suffer from issues such as lack of scientific standards for training content, uneven teaching levels, and insufficient credibility in skill certificates.
Thus, government has a role to play. That looks like setting up national vocational skills standards for jobs like industrial robot system operator, reforming higher vocational education systems, and holding skills competitions to certify personnel in skills like “basic programming and maintenance of industrial robots.”
It’s not just about more technical knowledge and better jobs. It’s about the social status and benefits that come with skills training.
Because migrant workers often don’t have a local (urban) household registration in the place where they work, they have limited access to social benefits. Obtaining professional certifications could help them accumulate points to get local household registration status.
Here’s an example from Foshan, a city in Guangdong. In 2019, Foshan awarded special VIP cards to winners of skill competitions in various occupations like electricians, welders, fitters, etc. Skilled workers with this card enjoy better government services, favorable treatment on school admissions for their kids, and benefits in apartment applications.
Read the FULL TRANSLATION: The Upward Ladder: Social Mobility of New Skilled Workers in a Period of Economic Transition
ChinAI Links (Four to Forward)
Should-apply: GovAI Summer and Winter Fellowships
Summer and Winter Fellowships provide an opportunity for early-career individuals to spend three months in Oxford working on an AI governance research project, learning about the field, and making connections with other researchers and practitioners.
Should-listen: Yang Gao on Sample-efficient AI
Yang Gao, an assistant professor at Tsinghua University, talks about his co-authored paper introducing EfficientZero: “a reinforcement learning system that learned to play Atari games at the human-level after just two hours of in-game experience.” In this interview with Jeremie Harris of towards data science, he also talks about long-term AI timelines and AI safety conversations in China.
Should-read: Perspective | Discovering Dr. Wu
Should-read: Informal Strike Organization in South China
Professor Chen, one of the authors of this week’s article, has also published work in China Review on how grassroots labor activism in the Pearl River Delta. “By examining how workers build the representative mechanism that, in practice, acts as an informal strike organization, this article illustrates an alternative pattern of organization in strikes that bypasses trade unions and discusses its influences on emerging Chinese labor activism.”
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 postdoctoral fellow at Stanford's Center for International Security and Cooperation, sponsored by Stanford's Institute for Human-Centered Artificial Intelligence.
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