ChinAI #119: Digital Intelligentization in China's SMEs
Results from surveys of 1000 small, medium, and micro businesses in China
Greetings from a world where…
renewal is afoot
…As always, the searchable archive of all past issues is here. Please please subscribe here to support ChinAI under a Guardian/Wikipedia-style tipping model (everyone gets the same content but those who can pay support access for all AND compensation for awesome ChinAI contributors).
Feature Translation: Market Research Report on Digital Intelligentization Solutions for China’s Small and Medium Enterprises
Context: Drawing from research on nearly 1000 small, medium, and micro businesses, Synced’s think tank has published a new report on digital intelligentization in China. This week’s translation consists of the summary slidedeck (the ones with a comment mark out the ones I looked at more in-depth).
Key Takeaways:
Slide 4: an overview of national-level policies related to SME digitization and digital intelligentization, which dates back to 2015
Slide 6-7 gives sectoral breakdown of China’s SMEs: top 3 industry designations for SMEs are wholesale and retail (30%), manufacturing, and business services; for micro-enterprises operated by self-employed individuals, the top three are wholesale and retail (50.6%), accommodation and dining, and transportation and logistics
Slide 10 on the big picture of digital intelligentization among SMEs: the total number of SMEs that are initiating digital intelligentization projects is only about 10 million, less than one-tenth of the total number of SMEs.
Slide 11: 67.74% of surveyed SMEs have increased their investment in digital intelligentization projects to varying degrees this year compared to 2019.
Slide 18: Nearly half of the surveyed SMEs agree that they lack technical experts related to digital intelligentization projects; other major barriers include: large deviations between the project quote and (the company’s) budget, unclear application scenarios, and poor data foundations.
Slide 25: Sometimes I fall prey to this model of Chinese tech giants as the primary engines of China’s entire digitization process. But, per a survey of 428 digital intelligentization solution providers, SMEs accounted for 76%, and start-up companies accounted for 48.77% (note: these are two different typologies of characterizing companies, so that’s why the combined figures exceed 100%).
Slide 28-29: Lists of top companies in different verticals of digital intelligentization, including: comprehensive, business administration, dining and accommodations, transportation, construction, etc.
FULL(ish) Translation: Market Research Report on Digital Intelligentization Solutions for China’s Small and Medium Enterprises
ChinAI (Four to Forward)
Should-read: Canaries in Technology Mines — Warning Signs of Transformative Progress in AI
Zoe Cremer, a Research Scholar at FHI, and Jess Whittlestone, a Senior Research Fellow at Leverhulme Centre for the Future of Intelligence, introduce a methodology for identifying early warning signs of transformative progress in AI, to aid anticipatory governance and research prioritization. This paper won the Best Paper Award at the 1st International Workshop on Evaluating Progress in Artificial Intelligence.
Should-read: The State of AI Ethics Report
This Montreal AI Ethics Institute (MAIEI) report provides a very useful update on developments in the field of AI ethics. As Danit Gal, a technology advisor at the United Nations, writes, “MAIEI’s reports lower the AI ethics literacy threshold. Their deep-dives, summaries, and analyses serve as an accessible and engaging means to interact with this field and its exciting and consequential developments.”
Should-read: The Untold Tech Revolution Sweeping through Rural China
From the NYT review of Xiaowei Wang’s book Blockchain Chicken Farm about tech in China’s countryside:
Consider the boom in the production of pork, a hot commodity among China’s increasingly prosperous diners. To increase the yield of pork farms, Alibaba trained a new artificial intelligence, “ET Agricultural Brain,” on vast amounts of data from pork operations, the better to predict how to increase yield. (They set up entire “digital towns” where young rural workers sit all day long clicking on pictures of pigs, labeling them as sick or healthy, to feed the A.I.’s smarts.) In the short run, the A.I. does indeed help optimize soaring pork production. It’s a win for diners, for pork producers and for government, which yearns for China to achieve “food security.” (“The food bowl of the Chinese people must always remain firmly in their own hands,” as Xi Jinping, general secretary of the Chinese Communist Party, has said.)
But nature does not always respond so obediently. One key strategy that emerges from all this high-efficiency pork farming? Feeding the animals “industrial pig swill,” a goulash that, cannibalistically, includes ground-up pig parts. And this, in turn, creates dangerous new vectors for disease, spreading the dreaded African swine fever so badly that by 2019 it tore through China and destroyed nearly one-quarter of the world’s pigs.
Should-read: Most of America’s “Most Promising” AI Startups Have Immigrant Founders
Tina Huang, Zachary Arnold, and Remco. Zwetsloot in a CSET data brief:
“Half of Silicon Valley’s startups have at least one foreign-born founder, and immigrants are twice as likely as native-born Americans to start new businesses. To understand how immigration shapes AI entrepreneurship in particular in the United States, Huang, Arnold and Zwetsloot analyze the 2019 AI 50, Forbes’s list of the “most promising” U.S.-based AI startups. They find that 66 percent of these startups had at least one immigrant founder. The authors write that policymakers should consider lifting some current immigration restrictions and creating new pathways for entrepreneurs.”
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.
Check out the archive of all past issues here & please subscribe here to support ChinAI under a Guardian/Wikipedia-style tipping model (everyone gets the same content but those who can pay for a subscription will support access for all).
Any suggestions or feedback? Let me know at chinainewsletter@gmail.com or on Twitter at @jjding99