ChinAI #113: Around the Horn Again

Plus, where's the coverage about Japanese companies in China?

Greetings from a world where…

Eugene Han, a PhD fellow at RAND who researches China tech, commented, “The last time was reading about a Japanese government initiative to fund shifting production out of China. Otherwise almost nothing over the past year(s).”

Indeed the major story about Japanese companies in China, at least this year, was that Japan was subsidizing 87 companies to shift production lines out of China. First reported by Nikkei Asian Review, this story was later picked up by the New York Times and the Washington Post. It makes sense why this is the only story that made it past the editor’s desk: probably got good clicks, tied to a specific policy, and fits with the DECOUPLING! narrative.

What’s missing is an understanding of the bigger picture, which the stats in my tweet point toward. Here’s the context that these articles lack: there are 33,050 Japanese companies in China, and the proportion of Japanese companies that chose to shrink, relocate, or withdraw from the Chinese market was the lowest it’s been in the past five years — 4.3 percent points less than the ratio in 2015. That’s from a recent 2020 Japan External Trade Organization (JETRO) White Paper on “Japanese Companies and the Chinese Economy.” According to JETRO’s survey, 93.8% of Japanese companies in China said they would either maintain the status quo or expand their business scale in China. Via Sina Finance’s (Chinese-language) readout.

I think this is a really good example of a blindspot in English-language coverage of China. As David Wertime’s latest Politico China Watcher reminds us: Earth to Washington and Beijing: It’s not all about you.

…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).

Around the Horn Again

Let’s run it back. Same structure as ChinAI #109:

  • short preview of 10 articles related to ChinAI — all published this past week and sourced from scans of WeChat accounts and groups

  • reply to the email and/or comment on the Substack post with the number of the article you’re most intrigued by, and we’ll translate a couple for next week!

  • some added weight to votes from subscribers that are supporting ChinAI financially

My hope is that folks researching this space and related areas can get more familiar with these types of sources, so I put more emphasis on linking to past ChinAI coverage of specific platforms. Okay, let’s go around the horn…again! (all links go to the original Chinese article)

1) Tencent, A Manufacturing Re-evaluation

Summary: How does a company with social media and gaming roots try to transform manufacturing services? Good details on what makes Tencent different from other Internet giants trying to expand their domain, in particular the value of the WeChat ecosystem at the enterprise level.

Source: 机器之能/jiqizhineng (Synced) — a long-time source for ChinAI translations, often features longform articles about China’s tech industry

2) Tsinghua Law professor says “No” to facial recognition access control in neighborhoods districts

Summary: Reviews Professor Lao Dongyan’s protests against the use of facial recognition access control in entry/exit for neighborhoods/residential communities, which has become more common in a time of Covid. Also covers a seminar held on this topic held in Beijing on September 23. Recall that ChinAI #77 featured her strong case against the use of facial recognition on the Beijing subway.

Source: 南方都市报 (NDDaily) — Southern Metropolis Daily, newspaper published in Guangzhou -- well-known for its investigative journalism.

3) Right Brain AI

Summary: Longform article that examines Microsoft’s XiaoIce chatbot, as a new example of “Right-brain AI,” which enables machines to emotionally connect with human beings. Plays off the distinction with “left-brain AI” — which is more connected to calculation and rational decision-making.

Source:出色WSJ中文版 (Wall Street Journal, Chinese edition) — The WSJ’s Chinese-language site was launched in 2002. I wonder how often WSJ Chinese, or similar platforms like FT Chinese, translate their Chinese-language reporting into English.

4) “New Infrastructure” musters troops for the battlefield, BATH evolves toward intelligence

Summary: Assesses the positions of Baidu, Alibaba, Tencent, and Huawei in their attempt to construct the new infrastructure of the “Internet of Everything [万物互联].”

Source:钛禾产业观察 (Taihe Industry Observer). I covered this plaform in-depth in these two previous ChinAI issues, describing them as China’s mini DefenseOne. The first link has a translation of the 11th article in their “Transformer” series. This is number 15 in that series.

5) Yunxi assists enterprises in digital transformation with standardized digital “middle platform” products

Summary: To try and catch the wave of digital transformation, many companies have tried to implement a 中台 (zhongtai) strategy. This article is a brief look at Yunxi, a leading service provider of digital 中台 (zhongtai). I could not, for the life of me, figure out the best way to translate this term. Eventually, came across this Zhihu thread that suggested “middle platform.” An architecture concept first articulated by Alibaba, a middle platform is an additional connective layer that fits between the traditional 2-tier structure of business applications (back-end and front-end)

Source: 赛迪网 (CCIDNet). Interesting site that covers IT industry developments. Related to CCID consulting, which is also producing a lot of good content. I wrote a little bit about the output of consulting firms/think tanks like CCID, Qianzhan, etc. in ChinAI #72.

6) IDC Marketscape Report: “Assessment of China’s Conversational AI Vendors

Summary: Released September 24, this report examines China’s dialogue-based AI market, which is predicted to reach 1.56 billion USD by 2024.

Source: International Data Corporation (IDC) is a Massachusetts registered and headquartered research company focused on the tech landscape. Interestingly, it was bought by China Oceanwide, a large Chinese conglomerate in 2017. IDC’s China division produces a lot of Chinese-language reports.

7) “AI Governance Online” Platform, launched in 2020 Zhongguancun Forum

Summary: This public service platform, a joint initiative by the Beijing Academy of AI and China-UK Research Centre for AI Ethics and Governance, was launched on September 19. Provides an evaluation for an AI project based on global AI governance principles as well as AI risk and governance case studies. You can play around with English-language version here; after, filling out the evaluation, it scores the project:

*It’s an impressive effort, and I applaud this important collaborative effort in the space of global AI governance. However, is this going to be a censorship-free space where the case studies section could include China’s use of facial recognition technology to target Uighurs and other ethnic minorities?

Source: 北京智源人工智能研究院 (Beijing Academy of Artificial Intelligence): BAAI was launched by the Ministry of Science and Technology and the Beijing Municipal Government in November 2018; it’s also supported by a lot of top Chinese universities and tech companies. For an interview with the head of BAAI’s AI ethics and safety research center, see ChinAI #52. For a summary of BAAI’s 2019 conference, see ChinAI #73.

8) An overseas PhD graduate at age 30, I decided to return to Shanghai Jiaotong University to Study AI

Summary: A profile of Jingwen Leng, who studied for a Computer Science PhD in the Department of at University of Texas at Austin, and has now returned to be a tenure-track Associate Professor at Shanghai Jiaotong University’s John Hopcroft Center. Relates his story to those of others in similar positions.

Source: AI科技评论(aitechtalk) — focuses on in-depth reports on developments in the AI industry and academia.

9) Is China’s Image on Twitter Getting Worse and Worse — A Tsinghua research team reveals the inside story

Summary: This article highlights this arxiv preprint that investigated China’s image among foreign publics based on a large-scale Twitter dataset. More interesting to me was the comment section, where some people noted the “guts/balls/courage” of Leiphone to cover such topics.

Source: 雷锋网 (Leiphone) — a long-time source for ChinAI translations, which I think of as China’s MIT Tech Review. See ChinAI #60 for more on this source.

10) China Standards 2035 vividly portrayed, this is the real key to Sino-U.S. tech competition

Summary: On glance looks like a good overview of China Standards 2035, albeit a bit hype-y and steeped in the great power competition narrative. Some good stats from Japan’s ICT tech committee on China’s growing influence in ICT standards.

Source: 智谷趋势(zgtrends) — new one to me, some harsh reviews on this Zhihu thread, describe themselves as cief intelligence adviser to decision-makers, and were one of Hurun China’s Top 50 most influential finance self-media.

***Okay same drill as last time: Reply to the email, or comment on the Substack post, with the number of the article you’re most intrigued by, and choose the feature translation for next week! If you’re supporting ChinAI financially as a subscriber, flag that in your reply, and I’ll give it a little added weight when tallying up all the votes.

ChinAI Links

Must-read: The Chipmakers — US Strengths and Priorities for the High-End Semiconductor Workforce

CSET analysis by Will Hunt and Remco Zwetsloot: “Technical leadership in the semiconductor industry has been a cornerstone of U.S. military and economic power for decades, but continued competitiveness is not guaranteed. This issue brief exploring the composition of the workforce bolstering U.S. leadership in the semiconductor industry concludes that immigration restrictions are directly at odds with U.S. efforts to secure its supply chains.”

Should-read: Scientists use big data to sway elections and predict riots — welcome to the 1960s

Harvard historian and writer of many New Yorker must-reads, Jill Lepore re-introduces us to the history of Simulmatics, which pioneered the use of computer simulations and pattern detection in American political campaigns. Draws from her book: If Then: How the Simulmatics Corporation Invented the Future (2020).

Should-read: Europe and AI: Leading, Lagging Behind, or Carving Its Own Way?

A really useful overview of Europe’s AI strategy (both at the European Commission- and country-level). Ending has some smart recommendations, and the paper frames Europe’s strategic position well:

  • “Given the need to address the societal, ethical, and regulatory challenges posed by AI, the EU’s stated added value is in leveraging its robust regulatory and market power—the so-called ‘Brussels effect’—into a competitive edge under the banner of ‘trustworthy AI.’”

  • “Yet normative principles and regulation alone are not enough for the EU to become a global AI leader. What is also required is a reevaluation of European competitiveness in this field in a way that leverages its comparative advantages… There is a clear rationale for a stronger EU-level role and for a more coherent European-wide approach to AI that complements member states’ own actions.”

Should-read: Xi's Science and Technology Speech Echoes and Updates Deng Xiaoping

Six experts on China’s S&T development untangle the past, present, and future in President Xi Jinping’s recent speech to a gathering of scientists and technology workers. DigiChina Project also translated the speech in full.

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

ChinAI #112: Part II, The Human Cost of 30-min Food Deliveries

Plus, must-reads on forecasting research community growth and the effects of foreign-language proficiency

Greetings from a world where we play infinite games…

…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: Delivery Drivers, Trapped in the System

*We’ve finished out the rest of this 15,000-word piece introduced in last week’s issue. Big thanks to ChinAI readers Gabriele and San for helping out with parts of the translation!

DISCUSSED IN PART TWO OF THE FULL TRANSLATION (in the style of how Believer magazine intros their articles)

  • The unchecked power (and impatience) of Chinese consumers, backed up by Ipsos survey data

  • Food delivery as a customer-centric “social performance” in which drivers are performing emotional labor, which is more draining than manual labor

  • Combined, Ele.me and Meituan “employ” nearly 6 million drivers. Just let that sit for a minute.

  • Drawing Peppa Pig memes, begging for five-star reviews, and keeping spare Coke

  • How Meituan and Ele.me implement gamification. One driver, "I was a Black Gold Knight last month. If I want to maintain it, I still need 832 points. There is still a lot of work to do."

  • Meituan’s effort to develop a windproof, waterproof, noise-removing, and smart Bluetooth headset with intelligent voice interaction so that workers stop looking at their phones while driving.

  • A “more deadly surprise” than being forced to watch driving safety videos — Operation Smile: a spot-check to make sure drivers are wearing work clothes, a helmet, badge, and a mask (in a time of Covid). Some false positives and negatives with this computer vision application.

  • Platform companies as “hands-off husbands” who care little about housekeeping; in Meituan and Ele.me’s case they contract out the “housekeeping” of ensuring driver and traffic safety to police officers and insurance companies.

  • Nick Seaver’s concept of “algorithms as culture” — “constituted not only by rational procedures, but by institutions, people, intersecting contexts, and the rough-and-ready sensemaking that obtains in ordinary cultural life."

  • Amidst all the hubbub about Meituan’s market value exceeding US$200 billion, some people brought up Wang Xing’s (Meituan’s CEO) fascination with James Carse’s book Finite and Infinite Games. The purpose of the former is to achieve victory, while the latter aims to keep the game going forever. The article concludes, “The delivery platform system is still running, and the game continues, but the drivers know almost nothing about their role in this ‘infinite game.’ They are still sprinting ahead, for the possibility of a better life.”

*I’ve posted the first few sections of the second half translation at the bottom of this issue. If you have the time, the full translation is well-worth a read, especially if your diet of China-related content mostly views “China” as an abstraction, rather than an entity composed of many actual human beings.

FULL TRANSLATION: Delivery Drivers, Trapped in the System

ChinAI Links (Four to Forward)

Must-read: A Novel Approach to Predicting Exceptional Growth in Research Communities

Klavans, Boyack, and Murdick develop a novel approach to forecast growth in highly specific research communities. Based on one of their models, they forecast the top research communities in AI applications, focusing on who was the research leader rin each community:

Table 10

Table 10 shows the dominance of Alphabet (Google’s parent company) and Tsinghua University. Chinese and American institutions make up 9/10 of the research leaders in these research communities which are forecasted to show high growth.

Must-read: Effect of Foreign Language Proficiency on Attitudes Toward a Former Aggressor State (Hu and Liu, 2020, in Journal of East Asian Studies)

Very relevant to ChinAI’s value-prop, the authors find a channel through which individuals proficient in a foreign language have an “alternative channel through which they are exposed to positive narratives put forth by other parties regarding the former aggressor state. And as a result, their attitudes towards the former aggressor state are more positive than those held by their linguistically limited counterparts.” For ChinAI purposes, it’s not just about positive narratives but a greater diversity of narratives.

The authors examine public attitudes towards the Japanese in Mainland China, Singapore, and Taiwan—three Chinese-ethnic majority political units that experienced Japanese aggression leading up to and during World War II. Using survey data, they demonstrate that individuals who are proficient in the English language are much more likely to hold positive attitudes towards the Japanese. These results are robust even when controlling for alternative factors. H/t to Kaiser Kuo for recommending.

Should-read: The True Story of Lee Kuan Yew’s Singapore

Haonan Li and Victor Yaw write: “The Western student of international politics knows to nod approvingly when Lee’s name is mentioned. Frustrated by the sludge of partisan politics in his own country, he sees in Lee’s legacy a kind of exotic escape. If asked, he remarks sagely: Singapore is proof of what enlightened authoritarianism can achieve.”

Should-watch: DoD Joint AI Center Explainer on AI and ML

Greg Allen, head of strategy and comms for the JAIC, breaks down the technical concepts of AI and Machine Learning for a non-technical audience. Check out some really great stuff on their blog as well.

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


Peppa Pig and Coke

Because of a disagreement with a customer, Meituan delivery driver Xiaolin discovered a ‘secret’ hidden in the system – the delivery time shown to the customer was different from the one displayed on the driver’s interface.

At the time, he had just started delivering Meituan orders. One time, he received an order, but as soon as he got to the store, a customer pelted him directly with a question: “How come you haven’t delivered this yet? It’s been delayed for a while.” Xiaolin thought that the customer was being unreasonable, because according to his smartphone there still were nearly 10 minutes available for delivery. After delivering the meal, he and the customer clashed again over time, and they both took out their phones to compare – the customer’s “expected delivery time” was exactly 10 minutes shorter than the driver’s “demanded delivery time”.

After he discovered this ‘secret’, Xiaolin has been calling the Meituan customer service every month for nearly four years; every time there is a different serviceperson, but the response is always the same: “Explain to the customer how that is only the expected delivery time.”

This is not only Xiaolin’s individual experience; many drivers have mentioned this problem to People. In their view, this is how the system pleases and retains customers, and this is also one of the principal causes of conflict between customers and drivers.

In his book Consumer Behavioral Science: Perspectives on Chinese Consumers, scholar Lu Taihong points out that the convenience afforded by the digital age makes consumers become increasingly critical, as they pay more and more attention to service quality and product experience; as their loyalty towards brands and products weakens, they become more ready to change suppliers at any time, and so “customers have a larger guiding influence on the market than they had in the past.”

Facing this kind of influence, delivery platforms that focus on large numbers of users and orders have also used algorithms to construct a kind of power structure; in this system, the customer is at the absolute top, and has unchecked power.

But customers can make mistakes. “Sometimes customers just can’t really tell” – on this topic, Gansu driver Wang Bing has a lot on his mind: “A lot of people don’t know where they live… They clearly live at the number 804, but they write 801. They clearly are at the South Gate, but they write North Gate. And there are some customers who forget they ordered a meal: when you call them, no one answers, but on the next day they remember and they give me a call, asking about their food… there are also people who order without looking at the address at all, and when I receive the order I immediately notice that the address is not right, that it’s somewhere in another province…”. The point is that customers do not need to pay for their mistakes, and if their order is delivered too late, it is always the driver who is punished.

As a sociologist who has extensively researched the professional difficulties of delivery drivers, Sun Ping has also discussed this kind of “unchecked customer power” in one of her articles. While the driver delivers a meal, the customer can examine everything about the driver: their real name, phone number, punctuality rate, how many times they have been praised, meal pick-up time, delivery route, and how long it will take to deliver. The customer also has the right to cancel the order while the order is being processed.

“They can see everything, the entire process, but we don’t know who they are. And if there is any problem, we can’t cancel the order like they can,” a driver complained to Sun Ping. They also shared a personal experience about having an order cancelled:

“I had two orders on my hands, one was 1.5 kilometers away, and had 45 mnutes left; the other was 3 kilometers away, and had only 20 minutes left, so I delivered the more distant one first. The 1.5 km customer got angry because he saw me pass their place through the GPS tracking without delivering their order. He was fuming, he canceled the order and complained about me with the platform…”

In the survey run by People, there also are drivers sharing similar experiences: on one day, upon receiving their meal, the customer asked the driver “Aren’t you just delivering one order to me?”

As the speed of delivery increases, the rating system becomes completely skewed, and the system’s pampering treatment of customers makes them more and more impatient.

Jing Jing, who lives in Shanghai, admits that he has been "spoiled." He is usually busy with work, does not know how to cook, and almost entirely relies on deliveries to fill his stomach. He often ordered food at a “light-meal” restaurant not far away. According to his memory, in the past, it took about 45 minutes from placing an order to eating the first small tomato in a Caesar salad. To pass the time, he usually watched a 45-minute TV series while he waited. Recently, the waiting time has stabilized at 26 minutes, but not long ago, the meal delivery time exceeded 30 minutes, and he became unbearable, making 5 calls to check on the order.

In 2017, Ipsos, a French research institute, conducted a survey on the “impatience” of consumers in 12 provinces and cities in China. The results showed that the development of mobile technology has made consumers more and more impatient in all aspects. This phenomenon is more and more prominent in economically developed areas and young people. Among them, "consumers in Beijing are the most impatient."

Faced with increasingly impatient customers, the drivers have no choice but to try every means to comfort them.

Speaking of this, Wang Bing also had a lot to say — when the delivery times of orders are close, he will pick the expensive one to deliver first, because customers with high-priced orders are usually more likely to lose their temper. “No matter how you explain it, they don’t listen, and they’ll suddenly get angry, saying that they will return the order. This 100 RMB takeaway -- how do I have the money to pay for this every day?”

They also try to meet customer needs other than food delivery, such as buying cigarettes and water, or "bringing a razor to an Internet cafe." For a while, under the influence of Douyin, there were always customers who asked Wang Bing to draw a piggy Peppa when delivering the meal. Wang Bing was very angry about this but he still had to draw it. "I bought a piece of cowhide/kraft paper, drew a Peppa Pig, and also wrote the sentence, ‘are you stupid?’"

"Delivery is a kind of customer-centric social performance." Sun Ping wrote in the survey report. She called the behavior of drivers to please customers and strive for five-star praise as "emotional and sentimental labor." In her opinion, this part of labor is often overlooked, but its damage and consumption to the driver are far greater than manual labor.

In the conversation with "People", she mentioned oneo driver who left the deepest impression. "Two vehicles were stolen from him within three days, and his battery was stolen three times. In talking about this he started crying and said that the platform requires us to say ‘Have a nice meal.’ Nobody knows this but I came from the countryside. I did farming work before. I am really embarrassed to say this (“have a nice meal!”) Also to ask for five stars --  I am a man. How can I say this?”

In an interview with Jiemian News about the "SKP incident," Shen Yang, associate professor of the Department of Public Economics and Social Policy at Shanghai Jiaotong University, said that although delivery drivers may have a monthly salary of over 10,000, they are still mired in class inequality. Those who make more money at the expense of time and health must do more intense work-both physically and emotionally-to get more wages.

Wang Bing is still developing new tricks to soothe customers. In summer, many people will order an extra cup of Coke with meals, but this summer there was a lot of rain. He often crashes due to way too many orders. When this happens, the Coke is basically gone and can’t be saved, but go back to the merchant and get another one, you will not only have to pay for it yourself but the order will also inevitably be late. In order to prevent customers from getting angry, he always keeps a bottle of Coke in his takeaway box. If the customer’s Coke is spilled, he finds a place where nobody is around to fill the spare Coke into the original paper cup, and wipes around the cup to leave no traces. He thinks this method is great.

At the same time as these delivery drivers are going to these lengths, some anxious customers appeared on several legal consulting websites. Someone posted a message asking, "I hurried the delivery driver to bring my order faster, causing an accident. Do I have to bear legal liability?" Below the question, there was a lawyer’s reply: "No responsibility."

Games

Not long ago, Meituan and Ele.me successively announced their 2020 Q2 earnings. In this quarter, Ele.me turned the corner and reached positive profits per order, while Meituan completed a net profit of 2.2 billion RMB, a year-on-year increase of 95.5%. Among this, the delivery business is the biggest contributor to Meituan’s profitability.

On August 24, 2020, Meituan’s share price also reached a new high, with a market value exceeding US$200 billion, making it the fifth-largest company in Hong Kong stocks by market capitalization.

In this half-year-long investigation, People came into contact with nearly 30 takeaway drivers, and the one phrase they frequently brought up was yi mao qian (ten cents/a dime).

 A Meituan driver in Hunan said, "If your punctuality rate is less than 98%, then you lose ten cents per order; if it’s less than 97%, then you lose twenty cents per order. Isn’t this just forcing the drivers to speed up? For us, the difference of a dime in each order is huge.”

An Ele.me driver from Shanghai said, "Ele.me. The lowest unit price is 4.5 yuan. The more you run, the higher the unit price. Sometimes the extra dime feels very touching. It looks different -- 4.9 RMB or 5 RMB."

 In order to keep this "dime", drivers not only need to run faster, but also run more.

 This is also what the system hopes to see, because there is another secret hidden in the system — a "game" with levels.

 Whether it’s Meituan or Ele.me the system has set a point level system for the driver -- the more orders you run, the higher the punctuality rate, the better the customer evaluation, the higher the driver’s points will be. Higher points lead to higher levels and more reward income -- the system will also package this evaluation system like a monster-fighting video game. Drivers of different levels have different titles. Taking Meituan’s system as an example, the titles from low to high are: ordinary, bronze, silver, gold, diamond, and king.

 A Meituan crowdsourced driver from a city in the southeast described the specific level setting: within one week, he completed 140 valid orders, with a punctual rate of 97%. He will become a "Silver driver" and receive an additional reward of 140 RMB per week. If you complete 200 valid orders and the punctuality rate reaches 97%, you will become a "Gold driver" with an additional bonus of 220 RMB per week. In Ele.me, the order quantity is directly linked to the delivery fee. If the number of orders completed per month is less than 500, then it’s 5 RMB per order; 500 to 800 orders, 5.5 RMBper order; 800 to 1,000 orders, 6 RMB per order... and so on. In the game rules, the points will be cleared on a weekly or monthly basis.

In the research report "Orders and Labor: Research on Algorithms and Labor from the Economic Perspective of Chinese Food Delivery Platforms," ​​Sun Ping said that in addition to overtime punishment, the system also uses this gamified evaluation method to involve many drivers. An unstoppable cycle, "They want us to work day and night," a driver said to her, but they can’t get out of it. "I was a Black Gold Knight last month. If I want to maintain it, I still need 832 points. There is still a lot of work to do."

 "The higher the level, the greater the pressure that drivers face to maintain the level." In Sun Ping's view, this gamified packaging not only presents the possibility of addiction, but also cleverly combines the driver's self-worth realization with capital management, and the coat of gamification "provides a universal, internalized, and reasonable explanation for the exploitation of algorithms."

According to the "Job Employment Report for the First Half of 2020" published by Meituan, the total number of drivers in Meituan has reached 2.952 million. The Ele.me fengniao official website shows 3 million drivers. Facing the systematic survival of nearly 6 million drivers, Zheng Guanghuai, a sociologist at Central China Normal University, proposed the concept of "downloaded labor".

In the investigation report "Wuhan City Delivery Workers Group Survey: Platform Workers and ‘Downloaded Labor’", Zheng Guanghuai's team gave an in-depth explanation of this concept—Drivers "download" the app to start work. On the surface, this app is just a production tool to assist them in their work, but in fact, what the drivers "download" is a set of sophisticated labor control modes. Under this mode, "The original subjectivity of workers has been comprehensively shaped and even replaced." They seem to work in a more free way, but at the same time they "suffer deeper control."

"The platform creates "platform workers" through downloaded labor." Zheng Guanghuai's team wrote, and the characteristics of this labor model are: strong attractive force, weak contract force, high supervision, and low resistance.

The medium that assists the system in completing the "downloaded work" is the drivers' own mobile phones-as the most important work tool, in public reports, the takeaway platform has been working hard to help the drivers get rid of their mobile phones.

"We are afraid that the driver will have trouble taking orders." In an interview with 36Kr in April 2018, He Renqing, the head of Meituan's delivery algorithm team, specifically mentioned, "For Meituan, the most difficult problem is how to prevent the driver from looking at their mobile phone while riding."

For this reason, Meituan spent 7 months developing a Bluetooth headset with a built-in intelligent voice interaction system. According to He Renqing, this headset is windproof, waterproof, noise-removing, and smart. Drivers can complete all operations by speaking as long as they wear it, ensuring that they can get ride of the mobile phone during the food delivery process.

In reality, none of the Meituan drivers who have communicated with People have received or used this smart Bluetooth headset, and none of the drivers can really get rid of their mobile phones.

Although she has only experienced the life of a delivery driver for a few days, Cao Dao still has lingering fears of the fear of being controlled by her mobile phone. "As you’re navigating, the system will ceaselessly remind you that Meituan crowdsourcing has another new order, please check the order in time and that will get mixed together with the navigation sounds. And then once you’re almost past time, customers will call you to ask where you are. You may have to take another order while navigating, and then answer the phone to explain to the customer why the order is not delivered on time..." Cao Dao said that this feeling made her feel that every minute is important and that she is being chased every day, "Can only go fast, go faster."

Electric Vehicles

"We can never lose time on the road. The time on the road is the fastest." An Ele.me driver told People, and another Meituan driver said that it’s only when on the road that an order is truly in his own hands., "Unless there is traffic police riding behind me and saying don’t speed, don’t speed. Otherwise when there are too many orders, all the drivers want to let it fly." After that, he added another sentence, “even if you fly, you can’t make it.”

At this time, the only thing that can help them is the electric bike that they are riding.

Before taking the job, drivers need to solve the problem of electric vehicles by themselves. Usually, the distribution stations have long-term cooperative third-party companies that provide drivers with electric vehicle rentals. In order to save costs, most drivers will choose a car with a rent of several hundred RMB, and the conditions of these cars are mostly difficult to say — some do not have a rearview mirror, and some pedals and front of the car are wrapped seven or eight times by rubber strips. A driver said that after running deliveries, he became an "electric car repair master."

If you don't want to rent, some sites will also guide drivers to buy a vehicle in installments.

A Meituan driver in Chengdu, at the request of the distribution site, bought an electric vehicle of an unknown brand at a price of 1,000 RMB higher than the market price. Another driver said that he had spent thousands on an electric vehicle through the distribution site. Just two days after running, the vehicle’s battery broke.

Meituan driver Wang Fugui felt lucky compared with those peers who mistakenly spent too much money. The only thing that happened to him was that he flew (along with the battery) out of the vehicle and got his head stuck in a guardrail in the middle of the road -- on his first day of becoming a driver. He had rented the vehicle through the station, and the monthly rent was 200 RMB. "Basically, it's a bunch of pieces put together." With no lights, the brake pads are worn out. Sometimes when you step on the brake, it will move forward, but when you step on the accelerator, it will reverse.

But this is not a problem. On the second day after the crash, he spent 10 RMB to install a foot brake by himself. When he ran the night shift, he would put a small flashlight in his mouth instead of the lights, or glue the flashlight to the front of the car. After all, this car also has its advantages. "It's extremely fast and can run up to 65 kilometers per hour," said Wang Fugui.

According to data released by the Ministry of Public Security in 2018, between 2013 and 2017, there were 56,200 road traffic accidents involving electric bikes causing casualties, resulting in 8,431 deaths and direct property losses of 111 million RMB. In order to further regulate the use of electric vehicles, in April 2019, the country officially implemented the new national standard for electric vehicles-according to regulations, the speed of electric vehicles must not exceed 25 kilometers per hour, and an electric vehicle that meets the new national standard must be sold for at least 1,000 RMB.

However, among nearly 30 delivery drivers contacted by People in this survey, no matter whether they were with Meituan or Ele.me, none of their electric vehicles meet the new national standard. These electric vehicles can generally run up to 40 kilometers per hour, far exceeding the speed limit. In groups and Tiebas of drivers, there are still many people discussing how to remove the speed limit for newly purchased electric vehicles through modification.

After working as a driver for more than a year, that car started to break down more and more frequently. Wang Fugui sometimes has to take a taxi to deliver meals. Fortunately, he’s located in a small county town in the northwest, so instead of having delayed deliveries on orders due to vehicle breakdowns, it’s more affordable to take a taxi. You can easily send more than a dozen orders for 50 RMB.

Later, in order to run faster, he gritted his teeth and bought a new vehicle by himself. As for the broken-down vehicle from before, he doesn’t know how many parts were dismantled and installed on however many electric vehicles waiting to be rented.

Whether riding an old or new vehicle, Wang Fugui’s performance has always been ranked in the top five and top three in the region, but he resigned not long after joining because he couldn’t stand the platform’s new requirements. “ Meituan, in order to expand, had us go on the streets to solicit customers. Every day we had to sign up two people who had never logged in to the Meituan app. At first, I had to endure it for a few days. Later, I couldn’t stand it anymore, so I ran away.”

Operation Smile

(continued in) FULL TRANSLATION: Delivery Drivers, Trapped in the System

ChinAI #111: The Human Cost of 30-min Food Deliveries

Renwu magazine's longform exposé on how drivers are trapped in a dangerous system

Greetings from a world where the price of punctuality is too high…

…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).

ChinAI Links (Four to Forward)

Switching up the order this week. There’s a feature translation of a really moving, special piece so I wanted to include the full text. Plugging a few things first, and then the last link will set the scene for this week’s 16page, 7000-word+ translation (and I only got halfway through this week).

First, GovAI is hiring for a project manager:

Should-read: Chinese Climate Narratives Newsletter

This summer I got to work with Mel Guo, a fellow at the Stanford Existential Risks Initiative. She is starting a newsletter titled “ To burn jade and common stone” (玉石俱焚), a Chinese idiom that means to destroy indiscriminately. It encapsulates the consequences without China’s buy-in on addressing climate change — the destruction of everything, precious or ordinary. At the intersection of Chinese civil society and climate change, the newsletter will unpack discussions of environmental organizers on Weibo, Chinese public opinion on climate change, etc. Check it out and subscribe!

Should-read: In China, Therapy is Going Mobile

RestofWorld, which reports on tech stories outside the Western bubble, has just published a story about the rise of online psychology apps in China, a country where psychotherapy was once condemned. Thanks to a thriving middle class looking to self-actualize, answers to questions like “are you happy?” are finally being addressed. For 100 to 1,200 TMB, a user can choose from hundreds of mental health professionals located anywhere from Beijing to Boston and book a consultation on such topics ranging from self-love to career pressure.

Must-reads: Some Food Delivery Background Reading before the Longform Translation

  • The thread that first linked me to the People (Renwu) magazine longform article:

  • An excellent article by Eliza Gkritsi, Nicole Jao, and Coco Gao for Technode that provides further insight into the labor status of drivers (most are independent contractors but they have made attempts at organizing).

  • After the People magazine exposé, China’s Meituan and Ele.me (the two giants food delivery platforms) have “announced tweaks to their algorithms as they try to head off a growing societal backlash against the stringent demands placed on their drivers.”

  • Your order, their labor: An Exploration of Algorithms and Laboring on Food Delivery platforms in China — an article in the Chinese Journal of Communication by Sun Ping, an assistant researcher at the Chinese Academy of Social Sciences who is cited throughout the People magazine article. She expands on the idea that delivery drivers have created their own “organic algorithms” or “inverse algorithms” to subvert the delivery platform system’s algorithm.

*By the way, if you’re a student and you need the full text to any of the academic article I link to, just hit me up and I’ll get you the pdf.

Feature Translation: Delivery Drivers, Trapped in the System

***I took an initial cut this week and got halfway through on the Google Doc. Can we crowdsource the rest of the translation? I think it’s a really worthwhile article to translate to get a sense of ordinary life in China. Just start writing suggestions in the Google doc so there’s no duplicate work! And then we’ll credit people when (hopefully) sharing the rest of the translation next week.

Context: Author: Lai Youxuan (赖祐萱); Editor: Jin Shi (金石); Source: 人物 (“People” - monthly magazine, first published in 1980, that started out focused on celebrity biographies. Original mandarin here. ChinAI previously translated a People article on a mother and her AI daughter.

No key takeaways this week, but I hope my informal translation can at least you give folks some sense of the type of journalism that can and does exist in China:


"Message Received"

Another two minutes disappeared from the system.

Ele.me driver Zhu Dahe clearly remembered that one day in October 2019. When he saw the system delivery time for an order, his hand holding the handlebar was sweaty: "2 kilometers, delivery within 30 minutes” — as someone who did food delivery in Beijing for two years, he knew that the previous shortest delivery time for the same distance was 32 minutes. But starting from that day, those two minutes were gone.

At about the same time, Meituan drivers also experienced similar “losing-time incidents." A Meituan driver who specializes in running long-distance deliveries in Chongqing found that the delivery time for orders within the same distance had changed from 50 minutes to 35 minutes; his roommate also did deliveries, and his delivery time limit for 3 kilometers had also been reduced to 30 minutes.

This is not the first instance of when time disappeared from the system.

Jin Zhuangzhuang has been the leader of the Meituan distribution station for three years. He clearly remembers that from 2016 to 2019, he received three notifications from the Meituan platform to "accelerate.” In 2016, the longest time for delivery within was 1 hour. In 2017, it became 45 minutes. In 2018, it was shortened by 7 minutes and fixed at 38 minutes. According to relevant data, in 2019, the average delivery time of delivery orders for the entire industry was 10 minutes faster than three years earlier.

The system has the ability to continuously "swallow" time. For the creators, this is commendable progress and a manifestation of the deep learning capabilities of AI’s intelligent algorithms. In Meituan, this "real-time intelligent distribution system" is called the "Super Brain.” Ele.me, named its system "Ark." In November 2016, Wang Xing, the founder of Meituan said in a media interview, "Our slogan is ‘Meituan waimai, song sha dou kuai (Meituan delivery, we deliver anything quickly.’ Deliveries arrive in 28 minutes on average." He said, "This is the embodiment of very good technology.

As for the delivery people who implement "technical progress," this can be "crazy" and "deadly."

In the setting of the system, delivery time is the most important indicator, and going over time is not allowed. Once it happens, it means bad reviews, reduced income, or even removal. In a Baidu Tieba where delivery drivers gather, one driver wrote, "Delivering food is a race against death, a competition with traffic police, and a friendship with red lights."

In order to keep himself alert, a Jiangsu driver changed his social account nickname to: going over time is 狗头. A Shanghai driver who lives in Songjiang said that he would drive in the wrong direction on basically every delivery. He calculated that he could save 5 minutes each time. Another Ele.me driver from Shanghai did a rough calculation. If he did not violate the rules, the number of deliveries he could run in a day would be reduced by half.

"Drivers will never be able to rely on their personal strength to fight the time allocated by the system. We can only use speeding to retrieve some time." One Meituan driver told People that the "craziest delivery" he has experienced is 20 minutes for one kilometer. Although the distance is not far, he needs to go get the food, wait for the food to be made, and deliver the food within 20 minutes. On that day, his speed was so fast that his butt bounced off his seat several times.

Speeding, running red lights, going in the wrong direction... In the opinion of Sun Ping, an assistant researcher at the Chinese Academy of Social Sciences, these delivery drivers’ actions to challenge traffic rules are a kind of "inverse algorithm," which is a last-resort work practice of drivers who have been under the control and discipline of system algorithms for a long time. The direct consequence of this "inverse algorithm" is that the number of traffic accidents encountered by delivery workers has risen sharply.

Sun Ping began to study the digital labor relationship between delivery system algorithms and drivers in 2017. In the exchange with "People” about the relationship between "shorter and shorter delivery times" and "more and more traffic accidents," she said, "It must be (the most important reason)." 

Actual data strongly supports this judgment. In the first half of 2017, data from the Traffic Police Corps of the Shanghai Public Security Bureau showed that in Shanghai, there would be a delivery driver casualty every 2.5 days on average. That same year, there were 12 casualties among Shenzhen delivery drivers within 3 months. In 2018, the Chengdu traffic police investigated and dealt with nearly 10,000 illegal drivers in 7 months, with 196 accidents and 155 casualties. On average, one driver was injured or killed every day. In September 2018, the Guangzhou traffic police investigated and dealt with nearly 2,000 delivery drivers who violated the law. Meituan accounted for half of them, and Ele.me ranked second.

The hashtag --- #外卖骑手,已经成为最危险的职业之一# (delivery driver has already become one of the most dangerous occupations) has become a Weibo hot search term more than once.

Specific cases from public reports are far more affecting than data——

In February 2018, an Ele.me driver was speeding on a lane closed to motorized vehicles and knocked down Li Mouqiu, one of the founders of the Shanghai Emergency Department, Ruijin Hospital, and Huashan Hospital emergency department. Li Mouqiu died one month later. In May 2019, a delivery driver in Jiangxi was in a hurry to make a delivery and hit a passerby who entered a vegetative state. A month later, a Chengdu driver ran into a Porsche while running through a red light, and his right leg flew off on the spot. In the same month, a delivery driver in Xuchang, Henan, went the wrong way on the motorway, was hit and flew in the air and rotated 2 times to the ground, causing multiple fractures all over his body...

Zhu Dahe, the driver with sweaty palms who was "terrified" by the delivery time, also once had an accident. In order to avoid a bicycle, he fell off his electric bike as he was speeding on a lane off-limits to motorized vehicles. The mala hot pot that he was delivering also flew off. At that time, what ran through his mind first before the physical pain was, "Oops, that will mean I went over time."

In order to avoid going over time and bad reviews, he called the customer and asked the other party to cancel the order, and bought that hotpot using his own money. "It's too expensive, more than 80 RMB," he said, "but it tastes good. "He still feels bad about it, because he had just entered the industry at the time and had insufficient experience. A more reasonable approach would be to pay the customer the money for the spicy pot and have them place another order. This way, “At least I could get the delivery fee for this trip," he said. "6.5 RMB, I remember it very well."

"Car crashes are all too common. As long as you don’t spill your meal, it’s not a big deal for a person to fall." Zhu Dahe said. When running deliveries, he has seen too many colleagues who had traffic accidents. “Normally I won’t stop,” because “I don’t have time for my own delivery.”

The experience of the Meituan driver Wei Lai confirms this statement.

At noon this spring, Wei Lai and a driver in uniform of the same color waited for a red light at an intersection. It was only a few seconds before the other driver got anxious and rushed past just as a car came at high speed. “The person and the car both flew in the air, and he died on the spot." Wei Lai said that when he saw his colleague lying in the middle of the road he did not stop. "The delivery in his hand would go over time." And just then, a new order came, and a familiar female voice sounded out —"Delivery. From XX to XX, please reply after the beep, and receive it."

Heavy Rain

According to the settings of the system, after the drivers reply "received,” it will start to operate.

In 2019, at the ArchSummit global architects summit, Wang Shengyao, a senior algorithm expert on the Meituan distribution technology team, introduced the basic operation of this intelligent system-

From the moment the customer places the order, the system starts to decide which driver to send to take the order based on the driver’s route, location, and direction. The order is usually dispatched in the batches of three or five orders. An order has two task points: fetching and delivering food. If a driver is doing  5 orders and has 10 task points, the system will complete the "ten thousand orders to ten thousand second-level solutions" in the 110,000 route planning possibilities. Plan out the optimal distribution plan.Two task points and food delivery. If a driver carries 5 orders and 10 task points, the system will map out the optimal delivery plan based on its "10,000 orders for 10,000 people at the speed of seconds” solution.

But in reality, if you want to crush this “optimum," a heavy rain is enough.

The drivers' attitudes towards rain vacillate greatly. They like rain because there will be more orders on rainy days, but if the rain falls too much, the system will easily "burst with orders,” and they are more likely to "get into trouble."

Gengzi, a Meituan driver rin Hunan, had a terrible rainy night. The rainstorm kept pouring down for a whole day, orders poured in frantically, and the system exploded. Every driver in the site carried more than a dozen orders at the same time, the boxes were full, and bags crowded the handlebar space. Gengzi remembered that he could only lightly lean his feet on the edge of the pedal, as he was keeping an eye on the delivery boxes wedged in between his thighs.

The road was too slippery. He fell down several times, then quickly got up and continued to deliver. It was not until 2:30 in the morning that he delivered all the orders on his hand. A few days later, he received the salary slip for the month, and the figure was actually much lower than usual. The reason is simple. On the day of the heavy rain, many of his orders were delivered late, so his salary was cut.

It is not only Gengzi who has been deducted from wages, but also the stationmaster of the distribution station.

"I’m someone who eats data." Meituan's distribution station director Jin Zhuangzhuang defined himself in this way. For a distribution station, the most important data include: orders received, late delivery rate, bad review rate, and complaint rate. Among them, the late delivery rate is the most important because it is the source of many bad reviews and complaints.

Generally, the late delivery rate of drivers should not be higher than 3%. If this is not reached, the rating of the distribution site will be lowered, and the unit price of the entire site will also drop. Everyone including the site manager, personnel, quality control, etc., or even managers connected to the site will be affected.

At the end of each year, the site will also face assessments by the Meituan and Ele.me platforms. The bottom 10% of the distribution stations in each region will face the risk of being eliminated.

Under this systematic evaluation system, the "late deliveries" bring not only the loss of income to the drivers, but also a second harm in the form of mental hurt.

"He will become a thorn on the team’s side." Sun Ping said, "Late deliveries are serious. It not only deducts a large amount of money, but it’s also closely tied to the issue of group honor. Since he is dragging everyone back, the distribution manager will find him, and then the section manager will seek him out, and then the district manager will seek him out. And then everyone will dislike him.

This will bring great mental pressure to the driver. Zhu Dahe, who fell on the road with the mala hotpot, told "People" that in his first few months as a driver, he spent every day in depression.

He came from a small place and was not familiar with the roads of Beijing, not to mention the huge amount of traffic and people on the road. He tremblingly abided by the rules, and was deducted for late deliveries every day. This makes him feel incompetent. "Isn’t it said that delivery staff can earn more than 10,000 RMB (a month)? Why am I so bad at it?" He said, "I thought I wasn’t cut out for being a delivery driver."

Later, as the electric bike rode more and more smoothly, and the road became more and more familiar, he transformed from a novice to a master on the road, and this sense of incompetence gradually disappeared. "Compared with delivering an order late, driving on the wrong side of the road is nothing." He said that he can even experience a sense of "flow" when driving on the wrong side of the road with his colleagues.

Nowadays, under normal circumstances, Zhu Dahe rarely has late deliveries, but extremely bad weather is still a spell he cannot escape. At this time, the out-of-control system will also rope him in --- carrying an excessive amount of deliveries, completely losing control of the delivery times, facing late delivery penalties, and plus he cannot ask for leave

In August 2019, Typhoon Lekima struck Shanghai. An Ele.me driver accidentally got electrocuted while delivering goods in the rain. Then, a screenshot of the WeChat group chat of the delivery station was uploaded to social networks. In the screenshot, the distribution manager wrote @人民 (all): "No leave for the next three days... If I can’t find you in the next three days then you will face double the penalty for absenteeism. Reply when you receive this message." Under the manager’s message, a long list of drivers responded “1” -- which represents they received the message.

This screenshot caused a huge public controversy. Some netizens asked why could Hema, KFC, and McDonald's all suspend delivery during the typhoon, but the delivery platform could not?

In this regard, Meituan station manager Jin Zhuangzhuang can only express helplessness. Every time it rained heavily, the drivers would come to him for leave, a flat tire, a fall, and family trouble, for various reasons. But in the face of a large influx of orders, for the sake of the site’s performance metrics, he had to forcefully stipulate, "Except for birth, old age, sickness, or death, you cannot ask for leave in bad weather, and you will be fined if you ask for leave.

In heavy rain, when Jin Zhuangzhuang was the most tired, he had to sit in front of the computer on the site and constantly monitor the position of each driver, the amount of orders they carried, and the time of delivery. For his site, Meituan stipulates that each driver can only receive 12 orders at a time. If the number exceeds 12, the system will stop dispatching orders. However, in severe weather or major holidays, this limit makes it impossible for drivers to carry the huge orders that flood in. At this time, the system is most likely to collapse: some drivers carry double the orders, and some drivers get almost no orders; some drivers get orders in the complete opposite direction; the delivery time of the closer order is longer than the one far away...

At this time, Jin Zhuangzhuang needs to play another role --- "manual scheduler." Under this status, he can enter the system and transfer driver A's order to driver B in order to balance the capacity. Although the system is capped at 12 orders, manual rescheduling is not restricted. As long as someone is manually controlling the system, the number of orders in the hands of the driver can become "a very scary number" -- the most was when a driver carried 26 orders at the same time; one delivery station with a little more than 30 drivers once completed 1,000 orders within 3 hours; another driver was allocated 16 orders  at once when running orders in a county with a population of 500,000 during peak hours.

An Ele.me station manager told People that this kind of manual intervention is not for rescuing the drivers, but to "excavate the potential and speed of each driver to the maximum."

The driver’s potential has been tapped to the extreme. If it still doesn’t work, Jin Zhuangzhuang will go out and deliver the orders himself, the most he carried was 15 once. "(When the orders explode), I first let the drivers carry on for a while. If they can’t go on any more, I appeal to Meituan to reduce the scope of deliveries. After 2018, our site no longer allows these appeals. No matter how many orders there are, we will have to deliver them." He said that when one finally finishes deliveries during a period when orders explode, your entire body feels numb, as you’ve been completely running on instinct -- “there is no human emotional response."

Last year, Jin Zhuangzhuang left the business because his family was sick. He said he would not come back again. Recently, a friend wanted to take over a distribution site, but Jin Zhuangzhuang dissuaded him, "This industry gives people a sense of time pressure and pressure to meet metrics, which you can't imagine." This summer there were heavy rains in southern China, and while Jin Zhuangzhuang was thankful that he had escaped, he was also worried. He didn't know how many sites had explosions of orders, or how many drivers had to desperately rescue their performance metrics.

Navigation

In order to complete her subject research, Sun Ping contacted nearly one hundred delivery drivers in the past four years, many of whom have complained about the delivery route given by the system.

In order to allow drivers to focus more on food delivery, this intelligent system will replace the human brain as much as possible — helping drivers plan the order of picking up and delivering food for multiple orders, and provide food delivery route navigation for each order, so drivers do not need to rack their own brains and can follow the prompts of the system to complete orders, and at the same time bear the risk of being led the "wrong way."

Sometimes, the navigation will show a straight line. A driver once said angrily to Sun Ping: “It (the algorithm) predicts the length of time based on the straight-line distance. But this is not the case for our food delivery, as we need to detour, and we have to wait for traffic lights... Yesterday, I delivered an order, and the system displayed five kilometers, but I ended up driving seven kilometers. The system treats us like helicopters, but we are not.”

Sometimes, the navigation will also include sections where drivers drive the wrong direction on the road.

In October 2019, Guizhou driver Xiaodao posted on Zhihu that Meituan had guided drivers to go on the wrong side of the street. In his communications with "People," he said that he had just been a driver for half a year and had encountered several navigations that guided him to go the wrong direction on the road. One of them was to deliver a meal to a hospital. Normal driving required a U-turn, while the route on Meituan’s navigation system was to cross over and drive on the other side of the road. According to the screenshots he provided, this segment extended close to 2 kilometers.

"Some are even more intimidating," said Xiaodao. "Some places are not convenient for going against traffic flow. If there are overpass bridges, the system navigation will have you drive over the overpasses, including those that do not allow electric vehicles to go up. It will also have you go straight through a wall."

In Beijing, a short video content creator, Cao Dao also encountered the same situation. To gain experience in the profession, she worked as a Meituan driver for less than a week. What surprised her was that when she took the order, the system navigation actually displayed as if it were a walking route -- there was no difference between walking forward or backward on a particular route, but the delivery system calculates time based on the shortest route, which contains a large number of segments which involve going against the traffic.

From Xiaodao's point of view, whether it is the straight-line distance or the wrong-direction distance the purpose of the system has been achieved — the system will pay delivery fees according to the distance and time calculated by the navigation model. With shorter distances and quicker delivery times, the delivery platform can keep more users, and also hold down delivery costs.

At the end of 2017, the Meituan technical team also mentioned "costs" in an article introducing the optimization and upgrading of the intelligent distribution system. The article pointed out that the optimization algorithm has reduced the platform's capacity loss by 19%. The meal that required 5 drivers to deliver in the past can now be delivered by 4 drivers. Finally, the word "costs" appeared in the conclusion of the article: "Efficiency, experience, and cost will become the core indicators pursued by the platform."

In fact, Meituan has also gained tremendous benefits.

According to data released by Meituan, in the third quarter of 2019, Meituan’s delivery orders reached 2.5 billion, and revenue per order increased by RMB 0.04 compared to the same period in 2018. At the same time, cost per order was reduced by 0.12 RMB compared to the same period --- This also helped Meituan earn a full 400 million RMB more in Q3 2019 (than it did in Q3 2018).

It’s just that in the background of the platform’s huge profits is the decrease on drivers’ personal income. Xiaodao said that whenever there is a wrong-side segment in the system navigation, he will face a dilemma of no choice. Either give up on wrong-side driving and face the risk of delay by taking a longer path, or risk safety to follow the navigation, but matter which choice, "There is really less money."

"Every driver must balance safety and income." As an "outsider" who temporarily entered into this system, Cao pointed out the plight of the drivers. "All delivery platforms are chasing profit maximization. In the end, they have passed on all the risks to the drivers who have the least bargaining power."

In the exchange with "People," several drivers all expressed the same sentiment, "They don't worry that no one will do delivery. If you don't do it, others will."

Before becoming a Meituan driver, A’Fei was a KFC delivery worker. "At most, one person would deliver 600 or 700 orders a month. Because of store limits, KFC can give the delivery company a high unit price of 12 or 13 RMB (order). Therefore, the delivery fee staff held at 9 RMB and has not changed." He used the phrase "the most standardized" to describe the job, but the income is not high, "At most you can earn a little over 5,000 RMB a month." In the end, inspired by the "over 10,000 RMB income of delivery drivers" (narrative), he decided to leave KFC to do food delivery.

In Meituan and Ele.me, drivers are divided into two categories-special delivery and crowdsourcing.

"Professional Deliverer" (专送) is a full-time driver attached to the distribution station, with a basic salary, prescribed work hours, and receive dispatch orders from the system, which also evaluates their on-time rate. "Crowdsourced deliverers" (众包) are part-time drivers with extremely low barriers to entry. One person, one car, and one app can be employed immediately after registration. They have no basic salary, can freely take orders, and can refuse system dispatches, but if they refuse too many items they can be restricted from taking orders. Crowdsourced drivers are not affected by bad reviews and complaints, but will face heavier penalties for delays. One second of going over time will directly deduct half the delivery fee. Regardless of whether you are a professional deliverer or a crowdsourced deliverer, no one has a labor employment relationship with the delivery platform.

A Fei finally chose to join Meituan and became a crowdsourced driver. That was around 2017. He worked about 9 hours a day, specializing in running long-distance delivery, and earned about 10,000 per month, and earned 15,000 in the best month — low threshold (for entry), high incomes — This is considered an important reason why delivery platforms "are not afraid of nobody coming to work".

In the eyes of sociology scholars, "over 10,000 in delivery income" is nothing more than an “exceptional situation" in the initial stage of the platform. After a long-term investigation of the labor process of couriers and deliverers in Wuhan, Zheng Guanghuai’s team at the Central China Normal University’s school of sociology found that with the end of platform subsidies and more and more drivers joining, "over 10,000 in delivery income"  is becoming an illusory dream.

The research report released by the team showed that: only 2.15% of delivery drivers had a monthly income of more than 10,000 RMB, while 53.18% of the interviewees reported that their current income could not meet family expenses.

A’Fei told "People" that after delivering orders in Beijing for a period of time, due to personal reasons, he went to Chongqing and his income dropped. Especially after the epidemic, more and more people joined, and it was even difficult for him to get orders. Sometimes the monthly income is less than 7000 RMB.

According to the "Report on the Employment of Meituan drivers during Epidemic Periods in 2019 and 2020" issued by the Meituan Research Institute, during the epidemic, the number of newly registered delivery drivers on the Meituan platform reached 336,000. Among the sources of new drivers, factory workers ranked first, followed by salespeople.

As for "when do you make the most money now", A Fei's answer is, "Only when it is very cold and very hot." Because, at such times, "most people are not willing to go out."

****You can read the rest of the sections (that I’ve translated so far) in the Google Doc with some annotations: Semi-Finished Translation

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

ChinAI #110: So You Want to be an AI Major?

Plus, Breaking down Ant Financial's Prospectus

Greetings from a world where…

(one of the best Twitter follows)

…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 #1: the “AI Major” in China

Thanks everyone for taking part in last week’s Around the Horn. Really close call among 4, 6, 7, and 8. I chose 8 (AI majors) since it had the most support among the choices that paying subscribers voted for, and 4 (Ant Group’s IPO) because it had the most support overall. Was helpful to see that almost every single option received at least some interest — except #9 about the early history of Hongqi cars (I’m glad I did the ATH exercise because there’s a good chance I would have gone for that one)

So…you want to be an AI major?

Context: High school seniors took the 2020 college entrance examination (gaokao) in July, and now they are thinking through which school and major they should apply for. One especially hot major is AI.

  • In March 2019, 35 colleges and universities across the country, including University of Science and Technology Beijing, Shanghai Jiaotong University, and Nanjing University, obtained the first batch of qualifications for establishing a new major of “Artificial Intelligence.”

  • Currently, a total of 215 universities across the country have added AI majors.

The choice of major matters a lot. One crucial aspect of China’s college admissions system: each university sets aside a number of places for each major, which means students apply to a specific major of a university. So, even if your scores are above the average successful applicant for a university, if you apply to an especially competitive major (which may be the case for new AI majors), you may not get in at all because your score was not high enough for the cutoff in that particular major.

Southern Metropolis Daily took a look at the curriculum, salaries, and employment prospects for AI majors. Key Takeaways:

  • Curriculum: 烧脑  ("brain-burning"), demands much thinking and reasoning, relatively large proportion of math classes. Here’s the math schedule for the AI major at my dad’s alma mater, Shanghai Jiaotong: Advanced Mathematics, Linear Algebra, Discrete Mathematics, Probability Statistics, Stochastic Processes, Linear Optimization and Convex Optimization. AI majors are oriented toward “elite cultivation”: about 30-40 people enrolled in AI majors from publicly available data at various schools.

  • Employment prospects/Salaries: Per a "2019 China AI & Big Data Talent Employment Trend Report" released by Liepin (big online talent services platform), the average monthly salary of AI and big data talents is 22,322 RMB. Data architects and data scientists rank the highest (37,451 RMB and 36,570 RMB). The average monthly salary of positions in deep learning, image recognition, recommendation algorithms all exceed 20,000 RMB. For context, avg monthly salary in 37 major cities in China = 8,452 RMB. It’s not all rosy. According to one third-year computer vision major at a top university, “If you don't have a paper or a contest (result), it’s very difficult to find an algorithm (engineer) post.”

  • Suggestions from professors: Students should prioritize their own interests. They could also choose majors related to AI and specialize later. "In fact, the direction of the AI major is a little bit more narrow. One good option is for undergraduates to choose relatively broad majors, such as applied mathematics, statistics, automation, electronics, etc., to lay a good foundation first, and then to engage in artificial intelligence research at the graduate level," Huang Kaizhu, a professor at Xi'an Jiaotong-Liverpool University, said.

FULL TRANSLATION: "AI Major" has become a hot spot to apply for

Feature Translation #2: Ant Group’s IPO Prospectus

Context: “The US capital markets are being shunned by the largest initial public offering in history. This is an indirect result of the recent China-baiting by US politicians, led by Donald Trump,” writes Daniel Broby, a UK fintech expert.

Less than one month after officially announcing its intention to list on both the Hong Kong and Shanghai exchanges, Ant Group’s prospectus disclosed its financial status for the first time. In just the first half of 2020, net profits reached 21.9 billion RMB, which (impressively) far exceeded last year's annual performance. Let’s learn about Ant Group, formerly known as Ant Financial — via jiqizhineng (Synced).

Key Takeaways:

  • Over 60% of revenue comes from digital financial technology platforms. Among them, the source of profits is mainly from two important loan products, jiebei (“borrow it”)and huabei (“spend it”), especially huabei, which can provide Ant with at least several billion RMB in profits every year.

  • Before reading this, I would’ve sworn that Ant’s more well-known digital payments platform (Alipay) would be the largest source of revenues. It comes in second, but “There is no doubt that payments are the lifeblood of Ant Financial, and the valuation of Ant Group depends on the dominant position of Alipay. Industry insiders believe that the data accumulated by Alipay can be described as its ‘unique martial art,’ and the credit system based on this data can be described as Ant's most competitive product.”

  • A key point that the prospectus emphasizes, and the numbers bear out: Ant is a tech company. The company’s R&D spending averages around 8% of operating costs for past four year. Since 2017, the total number of employees of Ant Group has increased significantly, from 9,273 in 2017 to 16,660 as of June 30, 2020. Technical personnel accounted for 64% of the increase.

  • Why is the location of its listing important? Here’s where it gets even more interesting. Ant is listing in both HK and SH, but the company is only aiming to raise 48b RMB in SH, compared to 92b RMB in HK. This is a huge gap in the scale of fundraising between Shanghai and Hong Kong, and the latter will become the main battlefield for global investors.

  • The SH listing, on a new Sci-Tech innovation board (STAR Market), is still significant though. Recall, in ChinAI #94, there was speculation that Cloudwalk (a facial recognition startup) would list on STAR, which was established “after complaints that Chinese mega stars like Alibaba…chose to list in the US rather than at home,” to encourage investment in domestic tech companies and make it easier for mainland investors to trade in these companies. Ant would be the giant of the STAR Market. According to statistics from China Economic Weekly, on the first anniversary (took place earlier in 2020) of the opening of STAR, the total R&D expenditures of STAR’s 133 new stocks totaled 21.2 billion RMB. Ant Group's R&D expenditure in 2019 alone has reached half of all listed companies on STAR.

FULL TRANSLATION: Breaking Down Ant’s 500-Page Prospectus

ChinAI Links (Four to Forward)

Should-attend: Navigating US-China Tech Futures, Stanford Cyber Policy Center Online Seminar

I’ll be participating in this online discussion next Wed (10-11AM Pacific) with Andrew Grotto, Director of the Program on Geopolitics, Technology, Graham Webster, editor in chief of the Stanford–New America DigiChina Project, and Jennifer Pan, Assistant Professor of Communication in the Stanford Department of Communication. I plan to mostly be a fly-on-the-wall trying to soak up all the wisdom of the other three — though I will maybe occasionally lob a few hot takes @ these two quote tweets of the original event announcements:

How DARE we even consider the possibility of cooperation………

Should-read: Mapping U.S.-China Technology Decoupling

From an all-star team — Yan Luo, Samm Sacks, Naomi Wilson, and Abigail Coplin — DigiChina attempts to map the state of decoupling in the U.S.-China technology relationship. First systematic effort I’ve seen which collects Chinese and US government actions on export/import controls, cross-border data flows, supply chain security reviews, financial untangling, visa restrictions, encryption, website and app bans, and other efforts to reduce dependence on the other country. My quick reaction: this is a really important effort. If we did the same thing and mapped all the ways the US-China have become more technologically dependent on each other, what would be the net-outcome (decoupling or coupled for life?)

Should-read: Immigration Pathways and Plans of AI Talent

By Cahterine Aiken, James Dunham, and Remco Zwetsloot for CSET, a data brief: “To better understand immigration paths of the AI workforce, CSET surveyed recent PhD graduates from top-ranking AI programs at U.S. universities. This data brief offers takeaways — namely, that AI PhDs find the United States an appealing destination for study and work, and those working in the country plan to stay.”

Should-read: Cloud Security — A Primer for Policymakers

By Tim Maurer and Garrett Hinck for Carnegie, a very useful primer for policymakers on cloud computing and cloud security. One interesting takeaway is that the cloud can actually be a huge win for security but better understanding by policymakers is necessary to realize that. See, in particular, Figure 5 for a helpful mapping of the impact of cloud security risk vectors. Thanks to Ozzie Gooen of FHI for helping review this primer.

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

ChinAI 109: Around the Horn

10 articles from WeChat accounts and groups in just the past week

Greetings from a world where the Ball Don’t Lie

A little personal update — for the upcoming academic year, I’ll be joining this cool (and intimidating) cohort as a predoctoral fellow at Stanford’s Center for International Security and Cooperation, supported by Stanford’s Institute for Human-Centered Artificial Intelligence. For those interested, that link gives a window into what I’m thinking and researching about outside of ChinAI.

…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).

Around the Horn with ChinAI

I don’t know if I’m even using the expression right, but I loved the ESPN show as a kid, so we’re just going to call this ChinAI’s first-ever around the horn. Here’s the premise:

  • I’ll give short previews of 10 articles related to ChinAI from this week that caught my eye when scanning WeChat accounts and groups. Each preview will also include a little context about the source. The idea is to give folks a fuller sense of the breadth and diversity of Chinese-language content, of which ChinAI is a drop in the ocean.

  • Reply to the email, or comment on the Substack post, with the number of the article you’re most intrigued by, and the one that receives the most votes will be the feature translation for next week! If you’re supporting ChinAI financially as a subscriber, flag that in your reply, and I’ll give it a little added weight when tallying up all the votes.

So, let’s go around the horn (all links go to the original Chinese article):

1) How was Germany's scientific research status created? How did it transform its scientific and technological achievements?

Summary: A prof-level senior engineer/deputy sec. of the party committee of Shanghai Institute of Family Planning Sciences gives their takeaways from a special training course, organized by the Shanghai Foreign Experts Bureau, which involved a visit to Hanover and Munich. Lessons for China from German scientific and technological transformation.

Source: 三思派 (Science-Pie) — This article was shared in a WeChat group I’m in. Though I don’t regularly follow it, seems to be a very interesting platform that focuses on science, technology, and innovation in China, jointly produced by:

  • Shanghai Institute for Science of Science, which was one of the earliest think tanks dedicated to innovation policy, established in 1980

  • Jiefang Daily, which is official daily newspaper of the Shanghai Committee of the Communist Party of China)

2) Open source is dead? Research shows that the open source field is no longer growing!

Summary: Distills key findings from a recent paper (Dorner et al.) on the saturation of open source software. Includes some reactions from readers of OSChina on whether they are still contributing to open source projects.

Source: OSChina — has featured in two recent ChinAI issues about Docker and the effect of entity-list export restrictions on open source projects, as well as Douyu’s open-source microservices architecture.

3) Breaking the record again! Overview of Megvii research institute’s 15 achievements at ECCV

Summary: The European Conference of Computer Vision (ECCV), one of the top 3 conferences on computer vision, was held last week. This article reviews trends in computer vision and highlights Megvii’s accomplishments, including a look at its 15 accepted papers.

Source: Paperweekly — a Chinese platform that keeps up with the latest in ML research, which we browsed together in a previous ChinAI issue.

4) Let’s unfold the 500-page prospectus of Ant Group’s IPO and understand what it’s like to have 21.9B RMB in net profits in half a year

Summary: What’s the secret to Ant Financial’s success? A deep dive into the company’s prospectus, which unpacks the company’s key competitive advantages but also the regulatory risks it faces.

Source: 机器之能/jiqizhineng (Synced)a long-time source for ChinAI translations, often features longform articles about China’s tech industry

5) Ten years of Baidu NLP: based on knowledge-enhanced language technology to realize multi-modal integrated understanding

Summary: A review of a decade of NLP progress and development at Baidu. Based on a speech at a recent Baidu summit given by Wang Haifeng, the company’s CTO and first Chinese chair of the Association for Computational Linguistics (a top conference in this field).

Source: AI科技评论(aitechtalk) — focuses on in-depth reports on developments in the AI industry and academia.

6) Li Dongrong: Thoughts on the protection of personal financial information in the digital age

Summary: Li Dongrong is the first president of the China Internet Finance Association, which is a national self-regulatory organization initiated by the People’s Bank of China in collaboration with gov. ministries/commissions. He provides an overview on the necessity of protecting personal financial information and recommendations to that end.

Source: 金融电子化 (fcmag) — recommendation via the WeChat account of China Information Security, a very important academic journal on informatization and cybersecurity.

7) The "underlying" strength of artificial intelligence under the “new infrastructure” concept

Summary: Examines the role of AI in the “new infrastructure” push. Looks at early investments that may have decades-long payoffs — focuses on Baidu’s Paddle Paddle and efforts in training next generation of AI talent. Came across this by just doing a WeChat search for "人工智能的” (AI) and filtered by the top ranked articles. This was one of the most read.

Source: 三联生活周刊 (www.lifeweek.com.cn) — SDX Joint Publishing, mainland branch of Sanlian (a huge Hong Kong books store chain). News and cultural magazine, which gives a flavor of what more mainstream audiences are reading about re: AI in China.

8) "AI Major" has become a hot spot to apply for! Some have annual salaries of over one million

Summary: Goes through figures on employment prospects in AI, salary figures, as well as the landscape of AI majors across Chinese universities.

Source: 南方都市报 (NDDaily) — Southern Metropolis Daily, newspaper published in Guangzhou -- well-known for its investigative journalism.

9) Frozen stiff, the red flag no longer flutters in the wind—a study of the early history of Hongqi cars

Summary: On August 23rd, FAW Hongqi’s luxury sedan officially hit the market. This essay goes through the history of Hongqi, which was launched in 1958, making it the oldest Chinese passenger car model.

Source: 北京大学科学技术与医学史系 (Department of History of Science, Technology and Medicine, Peking University). Shared in a WeChat group I’m in.

10) A whale falls in the northeast: Changchun ushers in its second spring

Summary: Changchun (capital of China’s Jilin Province in the northeast) had its first spring when its automobile industrial base grew rapidly in the 1950s/1960s. Now, Changchun is in decline, and part of a global "rust belt.” What’s the way out? Using a Chinese saying — 巨鲸落,万物生 [A giant whale falls, many things live] — this longform essay explores where new growth opportunities are in China’s northeast region.

Source: 钛禾产业观察 (Taihe Industry Observer). I covered this plaform in-depth in these two previous ChinAI issues, describing them as China’s mini DefenseOne.


***Once again: Reply to the email, or comment on the Substack post, with the number of the article you’re most intrigued by, and choose the feature translation for next week! If you’re supporting ChinAI financially as a subscriber, flag that in your reply, and I’ll give it a little added weight when tallying up all the votes.

ChinAI Links (Four to Forward)

Must-read: Annotated Bibliography on Network Traffic Management and Device Intrusion for Targeted Monitoring

Is there anything in this world more beautiful than a well-crafted annotated bibliography? A group at University of Toronto’s Citizen Lab — Siena Anstis, Sharly Chan, Adam Senft, and Ronald J. Deibert provide a high-level intro to network management technology such as deep packet inspection and Internet filtering tools. They review the literature on their uses for socially beneficial purposes as well as the potential for human rights infringements. Last updated: September 2019.

Should-read: The Future of American Industry Depends on Open Source Tech

By Kevin Xu and Jordan Schneider for Wired, a really informative, insightful, fit for the 21st century tech strategy. They write: “Yet as US policymakers develop their industrial policy to compete with China, open source is conspicuously absent…open source is not the panacea to all problems. By definition, anyone can run, change, copy, and distribute an open source technology. Thus, the technology and knowledge transfer can go to friends or foes. Indeed, China’s technology sector is starting to embrace open source—a sensible thing to do for a country looking to maintain its rapid growth and establish technological self-reliance in the face of US sanctions.”

Should-read: China’s Use of AI in its COVID-19 Response

By Emily Weinstein, who is producing high-quality content at an impressive rate, this CSET data brief summarizes findings from a March 2020 report entitled “Example Applications of Digital Health Technology for Epidemic Prevention and Control,” published by the China Academy of Information and Communication Technology (CAICT)—a think tank under the PRC’s Ministry of Industry and Information Technology (工业和信息化部; MIIT). The CAICT paper provides examples of how AI technologies helped combat COVID-19 from news reports from WeChat and official Chinese state-run media sources, company press releases, and academic journals. *Note that the foundation of this work is a translation of a Chinese-language report — that is a direct product of CSET investing in a translation lead (Ben Murphy).

Should-watch: Worlds of Ursula K. Le Guin

Best known for her science fiction and “Earthsea” fantasy series, celebrated and beloved author Ursula Kroeber Le Guin (1929–2018) wrote 21 novels, 11 volumes of short stories, four collections of essays, 12 children’s books, six volumes of poetry and four of translation during her life. American Masters presents the first documentary film exploring the remarkable life and legacy of the prolific and versatile author.

Thank you for reading and engaging.

***A quick note on my previous translation on Douyu’s open source framework Jupiter. Originally, I translated 二开 (shorthand for 二次开发) as “secondary development.” Thanks to ChinAI reader, Kevin Litchfield, for suggesting “fork” as an alternative translation. “Open source libraries have insufficient functions and bugs cannot be fixed in time, so (Douyu) forked the repository and continued to develop it.” We’re still trying to confirm the best way to translate 二开; after all, translations are living breathing things!

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

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