Ben Recht over at his Substack arg min:
I’ve been wanting to write a summary of the Cultural AI conference I attended at NYU last week, but I’ve been struggling to succinctly capture my thoughts. That’s indicative of the depth and complexity of how AI meets culture, and the different perspectives and disciplines might not lend themselves to a tidy summary. As I often do when trying to wrap my head around complex things, I will stop worrying and just blog through it.
The talk that serves as my hub in the complex network of cultural AI is Cosma Shalizi’s “Aware of All Internet Traditions: Large Language Models as Information Retrieval and Synthesis.” That language models simultaneously retrieve information and synthesize new content isn’t controversial. Nor is the fact that this synthesis is formulaic. The current synthesis is next-token prediction trained on all written information, whose output is warped by some selective post-training. By design, language models mechanistically reproduce the recurring regularities in their training data. That training data consists of all the text files on the internet and what is easily available in printed books. Hence, the regularities are the tropes, stereotypes, templates, conventions, and genres of language and code.
The formulaic generation of discourse looks like discourse in ways we could never have imagined. But with hindsight, we shouldn’t be surprised. Human culture is very formulaic! There are long-standing formulas for oral tradition, for generating small talk, or for generating scientific papers. As Cosma put it, in the single sentence that summarizes the entire Cultural AI conference:
Following a tradition means not having to think for oneself.
More here. (Cosma Shalizi’s slides here.)
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