ChinAI #211: The Toughest Campus Recruitment Season Ever?
Job seekers confront AI interviews and other hurdles
Greetings from a world where…
getting Babel, a book by R.F. Kuang, on inter-library loan for *academic* reasons = a good weekend
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Feature Translation: The Endless Job Hunt
One privilege of having a platform like ChinAI is that when journalists start a new beat covering China tech, they will sometimes ask me what types of stories I wish would get more ink. My answer is always very simple: human-interest stories.
Wikipedia tells us:
“In journalism, a human-interest story is a feature story that discusses people or pets in an emotional way. It presents people and their problems, concerns, or achievements in a way that brings about interest, sympathy or motivation in the reader or viewer. Human-interest stories are a type of soft news.”
I’ve never taken a journalism class in my life, but I think human-interest stories can be the hardest-hitting news about China’s AI landscape. What if we covered this topic “by presenting people and their problems, concerns, or achievements in a way that brings about interest, sympathy or motivation in the reader or viewer.” Bonus points if we can do this without framing the story as an exercise in U.S.-China technological dick-measuring!
Context: This week’s feature translation does just that. It comes from Renwu (人物) magazine, which previously published an investigative report in September 2020 on the algorithmic pressures faced by delivery workers (ChinAI’s full translation in this Google Doc). That article served as a tipping point for public pressure on Chinese regulations on algorithms, passed in March 2022.
This Renwu piece reports on an extremely difficult autumn job-seeking season, in which the number of college graduates in China exceeded 10 million for the first time. The story takes us into the mindset of students as they undergo this endless job hunt — complete with AI interviews and other hilarious and absurd moments.
Yu Xin is a master’s graduate of Wuhan University in biomedicine:
In that video interview, no real person appeared throughout the whole process, and the so-called “interviewer” was just a virtual female image in the video. The AI image told her the exam rules, and read out the exam questions with a mechanical voice. After 30 seconds of thinking time, the video recording started. Yu Xin had to put her head in the frame circled on the screen. The ambient light could not be too bright or too dark, and her head could not be raised higher or lower than a certain level. “My whole person just stayed in these bounds, talking to a machine, which did not respond after I talked.” Recalling that interview, Yu Xin squeezed out a few words, "Shocked, uncomfortable, stammering.”
To deal with these oddities, job-seekers consulted the “mianjing”[面经] — interview experiences posted on online bulletin boards:
Xu Yi, a Shanghai male, also experienced more than 80 AI interviews in this year's job hunting season. Sometimes he can face four or five interviews a day, each for 45 minutes. At the beginning, like Yu Xin, he told about his own growth experience with great sincerity, but later, he found that what the AI wanted to investigate was not these issues. He learned from the "Mianjing" on the Internet that this AI examiner can analyze the interviewer's personality, emotions, motivation and other psychological states from his facial expressions, movements and voice. “And it can also analyze the probability of job-hopping.”
The difficulty of this campus recruitment season is magnified because there are not just more job-seekers but also less positions:
The person in charge of Sun Yat-sen University’s Employment Guidance Center found that there were significantly fewer companies that came to make presentations this fall. “As of November 7, there were only 112, down 20% from the same period last year.”
According to Cui Chao, who runs campus recruitment for a large tech company:
After half a season of fall recruitment had passed, there were already 80,000 resumes in his resume library. In the previous year, for the campus recruitment of fresh graduates in 2022, the sum of fall recruitment and spring recruitment combined received no more than 50,000 resumes.
Before even getting to the AI interview stage, students often had to complete preliminary written test questions, which took over an hour for each position:
Yu Xin felt like she was soaking in a pond, with her feet unable to touch the ground, waiting for a company to salvage her from the water at any moment. The prerequisite for being “salvaged” is that you have to “swim in” first. Doing endless test questions is like her struggling to swim, and every time the test questions are submitted, she "continues to go back to the pool to soak.”
First half of FULL TRANSLATION: The Endless Job Hunt
ChinAI Links (Four to Forward)
Must-read: 2022’s Best Investigative Stories about China and Taiwan
Joey Qi, editor of Global Investigative Journalism Network in Chinese, lists some of the best investigative reporting relating to China and Taiwan from this past year. The CommonWealth Magazine report on “Made in China” Security Products in Taiwan was particularly interesting.
Should-read: Competition and cooperation in artificial intelligence standard setting: Explaining emergent patterns
In Review of Policy Research, Nora von Ingersleben, Doctoral Research Fellow at Technical University of Munich (TUM), explores patterns in AI standard-setting. This journal article traces some important trends of cooperation on AI technical standards in transnational standard-setting organizations like the ISO and IEC, which are more insulated from political agendas. She writes, “Several of my interviewees maintained that standard setting in expert mode was easier…When I asked a high-ranking representative of a large multinational manufacturing company during our interview whether he foresaw global cooperation on AI standards, he said: ‘As soon as you get out of the political discussion and get into the discussion about techniques and engineers are [talking about] the practical aspects that can actually be standards, I see very good collaboration and I believe this [technical standard setting] is where it is happening.’”
Should-read: How Literary Translation Can Shift the Tides of Power
Jen Wei Ting, a Singaporean writer and translator, reflects on the currents that shape what gets translated: “At a recent translation conference in Singapore in September, I listened to children’s book translator Helen Wang speak of the high demand for translated children’s books in China. Chinese parents, especially educated professionals, believe imported children’s books, especially those from the West, teach ‘greater self-confidence and ambition.’ Even with children’s literature, translation is a one-way street: in the U.S., translated children’s literature is almost non-existent. Most translated children’s books are works from Western Europe.”
Should-read: The private sector advances in China: The evolving ownership structures of the largest companies in the Xi Jinping era
This Peterson Institute for International Economics working paper, by Tianlei Huang and Nicolas Véron, assesses structural changes in China’s corporate landscape. They conclude: “As for market value of the largest listed firms, the private sector’s share in the top 100 listed Chinese companies was only 8 percent at end-2010 but crossed the 50 percent threshold in 2020 and retreated slightly in 2021 to 48 percent, following that year’s regulatory crackdown on several private-sector-dominated industries. These findings do not support a narrative of broad-based rollback in recent years of previous private-sector expansion.”
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 an Assistant Professor of Political Science at George Washington University.
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