What happens to jobs, productivity, inequality, and economic policy as AI transforms the way we work? Anthropic Chief Economist @PeterMcCrory and economist @JasonFurman took to the JFK Jr. Forum stage to explore these questions and more. https://ken.sc/forum0923-live

A few (personal) thoughts on reading empirical AI papers on the economy. Economists have gotten used to reading papers with super clean identification, arguing about the validity of an instrument, making sure parallel trend assumptions are satisfied. This is what gets you into a top journal, and it is *very* important research (no question here). But it also takes years and sometimes decades to get these types of papers right---people often don't find a good instrument to answer a specific causal question decades after the natural experiment. We will eventually have this type of research for AI as well, and it is absolutely necessary. But right we also need signals *right now*, even if they are noisier than what we are used to. We need papers where we can trust that researchers did their best methodologically, while at the same time acknowledging that the space is moving way too fast to wait for perfect identification. This will allow us to accumulate enough signals, coming at the same question using different angles, for example, to say "yes, X is likely happening in the economy". The AI exposure and early career hiring papers are a good example of this. There is no silver bullet paper with super clean identification. But at this point we have several independent teams reaching the same general conclusion, enough where we can say "there seems to be a slow down in AI-exposed, early career hiring."

We’re sharing how GLM-5.3 helped build and optimize the inference infrastructure serving GLM-5.3-Flash. The system went from its first successful run to production readiness in less than two weeks, with end-to-end throughput tripling relative to the initial baseline. The key was dense feedback: local correctness tests, execution traces, microbenchmarks, and end-to-end measurements that enabled targeted hypothesis testing rather than reliance on aggregate performance metrics alone. https://z.ai/blog/glm-built-its-inference-infrastructure

I've had the most wonderful time working on this project for the last few months. This was (equally) co-led w/ @JMateosGarcia , @alexolegimas and a fantastic team.

Anthropic's economic scenario analysis is interesting. But this is not something you can ignore, this is the most important consideration! "the model cannot generate the negative feedback in which disruption depresses demand and amplifies its own labor-market consequences"

New from us: Anthropic just published scenarios for AI’s possible economic impacts, which range from minimal, to explosive GDP growth of 15% by 2030 as knowledge-worker unemployment hits 18%. I sat down with their co-founder Jack Clark to pick his brains on how they’re thinking about all of this.

New post on the blog, featuring the excellent @ben_moll There’s been tons of discourse on how AI will contribute to economic growth, with many people closest to the technology predicting double digit increases. Are these forecasts likely? Probably not. The blog goes through the economics for why exploding improvements in capabilities (which technologists have been largely right about) may not translate to explosive growth. Ben’s thread covers this in detail, but gist is that: 1) there is nothing in economic growth models that prevents AI from leading to explosive growth but 2) this trajectory relies on a series of assumptions that are unlikely to hold in the real world. For example, one assumptions is likely to be violated because of a pretty counterintuitive feature of structural change: the sectors that become automated become smaller parts of the economy (because they’re cheaper, people become richer, and spending moves to non-automated parts of the economy). This, plus other features of the economy, is what will likely cause the trend of huge increases in capabilities coupled with “only” 4-5% growth (which is huge, btw) to continue. Here is the link: https://aleximas.substack.com/p/will-ai-soon-lead-to-double-digit Looking forward to hearing thoughts/feedback!