I think the biggest thing is taking the time to figure out your value prop: how can you combine your background and skills to contribute to a gap in the existing news ecosystem and blogosphere?
- Jeffrey Ding, ChinAI
Jeffrey started ChinAI as an email to friends and colleagues interested in translations of Chinese writings on artificial intelligence.
When he felt his “side hustle” pulling him away from his 9-5 work as a PhD student and aspiring academic/researcher, Jeffrey had to rely on word-of-mouth for growth and help from contributors.
Read on for more on Jeffrey’s experience and insights for creators working on side hustles of their own:
On his #1 piece of advice for creators: I think the biggest thing is taking the time to figure out your value prop: how can you combine your background and skills to contribute to a gap in the existing news ecosystem and blogosphere?
On his decision to not charge subscribers: ChinAI is more of a side-project for me, I decided to keep it free for all, essentially supported by donations via paid subscriptions. I do some little incentives for paid subscribers like giving their votes more weight when it comes to picking a translation for the next week.
On the time demands of a newsletter: I wish it was something I thought more systematically about at launch because there were some weeks where the newsletter took over my life.
One topic I'm drawn to are AI applications that are not as visible or consumer-facing as the ones you often hear and read about (think: machine quality inspection and machine translation as opposed to facial recognition).
I call it Unsexy AI.
For example, one of my favorite ChinAI issues was this translation of a longform article about China's efforts to improve manufacturing lines for knives, peelers, and other cutting tools. The piece covered how Chinese factories are attempting to employ machine vision to detect defects in the production line, so as to improve manufacturing efficiency.
I think this aspect of China's AI development is really important because it will drive productivity growth, which is central to so much of the Chinese government's broader strategic goals (sustained economic growth, performance legitimacy and regime stability, military capabilities, etc.)
New York Times and Wall Street Journal are good go-tos for generalists on tech. Wired and MIT tech review provide more tech-specific coverage.
Financial Times and Reuters (not US based) are also good.
To be honest, I've been lucky in that much of my growth has been passive (e.g., word-of-mouth from others, being invited to speak on podcasts and join things like this Creator AMA, so it's definitely been a fortunate network effect for me).
I used to post Twitter thread summaries of the newsletter and tag people who's work I recommended in each issue but stopped doing that a while ago.
I started the newsletter as a "side-hustle," and I've tried to bracket it off from my 9-5 work (as a PhD student and aspiring academic/researcher)
I wish it was something I thought more systematically about at launch because there were some weeks where the newsletter took over my life.
Now, I try to only work on it for 6 hours max on the weekends, and I also have pulled in a lot of contributors who help out with translations and analysis, whom I compensate as independent contractors.
After 3+ years I have a good process down.
First, I spend about an hour scanning Chinese WeChat accounts, media platforms, and groups that cover China's AI scene to pick out an article/white paper/report/blog that takes an angle that's not been well-covered in English-language media. So the prop bet is with every issue you are getting information you wouldn't get anywhere else unless you could read Mandarin.
Then, I spend a couple hours translating and annotating that text in a Google doc that is open to comments. Next, I distill the translation down into key takeaways and provide context about the source, which goes in the text of the Substack.
Finally, I provide links to 4 English-language reports on China's AI scene that serve as my reading recommendations for the week.
One way I like to conceptualize the AI ethics discussion is a red light-yellow light-green light system.
Red=off limits/censored topics (e.g. use of facial recognition to discriminate against ethnic minorities like the Uyghurs).
Yellow=some room for critique of govt surveillance like Dongyan Lao’s complaints about Beijing metro facial recognition but still murky area.
Green = very robust discussions about AI and privacy, AI safety, and even risks associated with superintelligence or strong AI.
It’s funny, ChinAI is essentially an amalgamation of two of my favorite newsletters.
One is Sinocism by Bill Bishop who is the OG of China-focused newsletters.
The second is ImportAI by Jack Clark who does a great job translating technical AI research trends to commoners like me.
Combine the two and you get ChinAI in some ways.
One thing I remind myself is that a lot of the depressing/disturbing news is not unique to covering this topic.
That is, AI augments and exacerbates existing bad things in society, but it also provides an opportunity for redress and new paradigms.
I predict more regulations. See, for example, the data security law and CAC regulations on deepfakes.
DigiChina project has good coverage of these issues.
I would say US media consistently overestimate China's actual AI capabilities.
I cover others in my year #1 review post.
One distribution change was I switched from Mailchimp to Substack because I reached Mailchimp's 2000 list for free service.
Yes, I've been making money from the newsletter for about two years. About a year and a half into doing the newsletter, I made it so people could also be paid subscribers even though everyone would have access to the same content (allowing people to "tip" me via substack even though they wouldn't get exclusive content, similar to The Guardian or Wikipedia).
As for content change, I started out providing more encyclopedic content but have started feeling more comfortable expressing adding my own voice and hot takes.
I think the biggest thing is taking the time to figure out your value prop: how can you combine your background and skills to contribute to a gap in the existing news ecosystem and blogosphere.
I think there's also a lot of value in creating a newsletter not designed to grow a huge audience.
A lot of times ChinAI is helpful for me as just a public notetaking device, where it helps build accountability and discipline for me to keep up to date with what's happening on this particular topic.
For me, [a] challenge was balancing the newsletter with working full-time on my dissertation.
It was more fun to do the newsletter and you get that short-term high of getting something out there every week.
So I had to get to a balance where I was also putting in the needed work on the longer-term projects.
One thing to flag at the start is that I chose a different path than many other newsletter writers who go paid.
Substack, for example, recommends that you should do 1 free post a week and X number of paid posts exclusive to paying subscribers. https://on.substack.com/p/your-guide-to-going-paid
If I were optimizing for making the most money off of ChinAI, I should probably follow their advice.
But since ChinAI is more of a side-project for me, I decided to keep it free for all, essentially supported by donations via paid subscriptions.
I do some little incentives for paid subscribers like giving their votes more weight when it comes to picking a translation for the next week. See the "Around the Horn" issues in my archive. But otherwise there's no difference in how I manage the relationship between free readers and paid subscribers.
I haven't thought enough about this question to give a comprehensive answer, but let me give two examples.
One interesting example of dual misperception is the issue of who was the first to develop a national AI strategy. On the Chinese side, I've translated texts that say the U.S. was the first to do so with the set of three white papers on AI published by the Obama administration in 2016. Funnily enough, in US circles, China's 2017 AI plan was perceived as a China being the first to develop a national AI strategy.
Another misunderstanding I think is that there's a technonationalist stream of Chinese media that perceives everything the US is doing in AI as trying to contain China's development, whereas I see the US as having a more multifaceted approach which is shaped by many actors that don't see the competition as zero-sum.