Timothy Lee: The last year has been a lot of cognitive dissonance for me. Inside the AI world, there’s non-stop talk about the unprecedented pace of AI improvement. But when I look at the broader economy, I struggle to find examples of transformative change I can write about.
Electricity wasn’t in wide industrial usage until 1910s, despite technology being very promising from the start. The reason was differenct infrastructure necessary for steam-powered and electric factories.
I think the same with LLMs: you need specific wrapping and/or experience to make them productive, this wrappings are hard to scale, so most of surplus is going to dissipate into consumer surplus + rise of income of productive workers.
The simplest (in conceptual sense) way to integrate AI in economy is to make it self-integrating, i.e. instead of having humans thinking which input AI need to get and where output will be directed, you should have AI agent which decides for itself.
Electricity wasn’t in wide industrial usage until 1910s, despite technology being very promising from the start. The reason was differenct infrastructure necessary for steam-powered and electric factories.
I think the same with LLMs: you need specific wrapping and/or experience to make them productive, this wrappings are hard to scale, so most of surplus is going to dissipate into consumer surplus + rise of income of productive workers.
The simplest (in conceptual sense) way to integrate AI in economy is to make it self-integrating, i.e. instead of having humans thinking which input AI need to get and where output will be directed, you should have AI agent which decides for itself.