I don't do themed editions of the letter all that often, but when I do they're deliberate. This time, it just happened. Funny how that works ...

With that out of the way, let's get Monday started with these links:

Boarding China's Last Bus — An examination of why the Chinese overwhelmingly embrace AI. It's not (just) about shiny new technology but also about the country's ingrained attitude towards change.

From the article:

The signal for individuals was clear: You had better catch the “last bus” to seize the fleeting opportunity. If you fail, no one, even the state, will back you up. This mentality undergirded China’s development at the turn of the century and prevails today. Whether it involves market, education, industrial, or technological reforms, people in China are frenetic about new things because they are always seeking the trend to follow. In Xiang’s words, “every bus is the last bus.”

Illegible benefits — Carlo Cordasco examines the longer-term impact of, and the changes wrought by, the use of generative AI in various fields.

From the article:

When preliminary exploration is cheap, you spend less time grinding through arguments from first principles, a grinding that builds fluency that shows up in live exchange. Friends have pressed me on this, and they are right to worry. The shape of the disagreement is itself instructive, because the cost is immediately describable as a subtraction from a capacity I have been exercising for years, while the benefit was prospectively invisible and retrospectively obvious. I did not predict it, and I could not have named it in advance. The faster literature review and cleaner first drafts I had hoped for in 2023 turned out to be roughly as interesting as Thamus’s concession that writing would be a useful aide-mémoire.

How data collectives are helping communities fight Big Tech AI extraction — A look at how some groups and communities are trying to keep their information out of the clutches of Big Tech while still being able to use that data for their own purposes.

From the article:

Besides collectives, other frameworks in use include data trusts, where a trustee manages data on behalf of a group; data unions, which aggregate the data of individual members to negotiate collectively with buyers; data commons, such as Wikimedia and OpenStreetMap, which have different governance structures; and data donation schemes, such as the Personal Genome Project, where individuals contribute their data for public benefit.

How AI is changing language — Is AI having as great effect on writing and language as other technologies have had in recent memory? Or are large language models merely aping the agglomeration of works, produced by humans, on which they've been trained?

From the article:

The problem is that not only does AI train on human writing, but humans are stylistically influenced by AI, the interplay creating a kind of linguistic hall of mirrors. Short of an author admitting it, it's hard to say for certain whether an individual piece of writing is AI or not. That uncertainty is a recipe for paranoia.