For the past few years, China has been rolling out a Black Mirror / Harry Potter-esque social rating policy known as the Social Credit System (SCS). Far from just a credit score in the financial sense, an SCS score can determine whether a person can buy business class tickets on trains (or take the train at all) or have access to flights. Apps are rumored to exist that would tell users whether they are standing near someone with a debt listed in the system, so … they can walk away I guess.

This is a massive undertaking, and researchers are finally starting to collect good data on the system’s operation, such as a MERICS report looking at the implementation of this complex system, which involves companies and all levels of the Chinese government. Westerners have also increasingly explored the generally positive reception of the system by Chinese citizens, which would seem at odds with typical desires for privacy.

Yet, one of the biggest and most obvious open questions is what exactly will get you rewarded or punished by the SCS? Now, we are finally starting to get answers.

In a new paper that will be presented this week at the ACM FAT* Conference on algorithmic transparency, a group of researchers investigated how positive and negative points were assessed by downloading a large corpus of hundreds of thousands of entries from the Beijing SCS website and analyzing it with content analysis machine learning tools.

They found that Beijing was remarkably clear about what will get you punished, but vague about what will get you positive points. For instance, the vast majority of the blacklist was made up by people who had failed to pay their debts, or who had committed a traffic violation. Meanwhile, the people on the redlist (the positive list) were there because they were, say, great volunteers, but with no criteria on how to get that status or why they were listed at all.

“It’s very difficult to pinpoint the exact degree of transparency,” of SCS said Severin Engelmann, one of the lead researchers based at the Technical University of Munich. Far from being just an experimental startup, SCS is already quite advanced. “Blacklisting and redlisting are already in place, and they clearly indicate what behavior is bad … but not what behavior is actually good,” he said.

Even more interesting, there are more companies on the blacklist and redlist than there are individuals within the Beijing corpus, indicating that while the government is certainly concerned about citizens, it’s bringing its social control mechanism onto companies perhaps more aggressively.

Jens Grossklags, another of the researchers, noted that this level of transparency — while inconsistent — was unusual in the West. “It is really fascinating from a data science perspective to see how much information is being made available not just to individuals but to the general public,” he said. He noted that public shaming has been common with the Chinese system, while Western consumers have a hard time accessing their own scores let alone the scores of others.

The study is one of the first to look at the actual implementation of SCS and reverse engineer its algorithm, and the researchers are potentially following up by investigating regional variations and further changes to the system.

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Share your feedback on your startup’s attorney

My colleague Eric Eldon and I are reaching out to startup founders and execs about their experiences with their attorneys. Our goal is to identify the leading lights of the industry and help spark discussions around best practices. If you have an attorney you thought did a fantastic job for your startup, let us know using this short Google Forms survey and also spread the word. We will share the results and more in the coming weeks.

Stray Thoughts (aka, what I am reading)

Short summaries and analysis of important news stories

Hustling to nothing

Erin Griffith has a great piece on the increasing pervasiveness of hustle culture. This is part of a long-running debate in Silicon Valley between the work-your-ass-off crowd and the productivity-peaks-at-35-hours crowd. The answer in my mind is that we should see work in phases — running at 100 MPH all the time is most definitely not sustainable, but neither frankly is working a very stable number of hours per week. The vagaries of life and work mean that we need to surge and recede our efforts as dictated, and always track our own health.

Nvidia’s troubles continue

We’ve talked a lot about Nvidia over the past few months (Part 1, Part 2, Part 3). Well, the bad news train just continues. As my colleague Romain Dillet reports, Nvidia is cutting its revenue outlook, and now the stock is falling again (another 14% as I write this). It cites lowered demand particularly from China, which is experiencing a major slowdown in its economy.

Can Chinese startups subsidize customers forever?

The Financial Times asks an important question about the “China model” of startups: should founders heavily subsidize customers in order to buy market share and fight competitors? They point to bike sharing startup Ofo’s collapse, although I would point to the expensive rise of Luckin Coffee as perhaps the latest example. It’s a lesson that Munchery’s investors also have had to learn: at the end of the day, those unit economics better turn positive if a company is to survive.

What’s next

• More work on societal resilience

This newsletter is written with the assistance of Arman Tabatabai from New York

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