The economic data seems to depend on one’s point of view. I’m no economist and I certainly can’t prove to you that AI is having an economic impact. Its use grows quickly though: Statistics on AI market size
It’s also important, I think, to distinguish between AI capabilities and AI use. The AI-2027 text argues that a selected few AI capabilities matter most, namely those related to software and AI engineering. These will drive the recursive improvements. Changes to other parts of the industry are downstream of that. Both our viewpoints seem to be consistent with this model: I see rapidly increasing capabilities in software, and you see that other fields have not been so affected yet.
I’ll finish with yet another anecdote, because it happened just yesterday. I was on a mountain hike with my nephew (11 years). He proudly told me that they had a difficult math task in school, and “I was one of the few that could solve it without ChatGPT”.
It’s an anecdote, of course. At the same time, effects of AI seem to be large in education, and changes in education probably lead to changes in the industry.
The economic data seems to depend on one’s point of view. I’m no economist and I certainly can’t prove to you that AI is having an economic impact. Its use grows quickly though: Statistics on AI market size
This is confusing two different concepts. Revenue generated by AI companies or by AI products and services is a different concept than AI’s ability to automate human labour or augment the productivity of human workers. By analogy, video games (another category of software) generate a lot of revenue, but automate no human labour and don’t augment the productivity of human workers.
LLMs haven’t automated any human jobs and the only scientific study I’ve seen on the topic found that LLMs slightly reduced worker productivity. (Mentioned in a footnote to the post I linked above.)
It found that consultants with AI access outperformed consultants without AI access, on most dimensions that were measured. Ethan has since participated in several other studies on the industry adoption of AI.
The economic data seems to depend on one’s point of view. I’m no economist and I certainly can’t prove to you that AI is having an economic impact. Its use grows quickly though: Statistics on AI market size
It’s also important, I think, to distinguish between AI capabilities and AI use. The AI-2027 text argues that a selected few AI capabilities matter most, namely those related to software and AI engineering. These will drive the recursive improvements. Changes to other parts of the industry are downstream of that. Both our viewpoints seem to be consistent with this model: I see rapidly increasing capabilities in software, and you see that other fields have not been so affected yet.
I’ll finish with yet another anecdote, because it happened just yesterday. I was on a mountain hike with my nephew (11 years). He proudly told me that they had a difficult math task in school, and “I was one of the few that could solve it without ChatGPT”.
It’s an anecdote, of course. At the same time, effects of AI seem to be large in education, and changes in education probably lead to changes in the industry.
This is confusing two different concepts. Revenue generated by AI companies or by AI products and services is a different concept than AI’s ability to automate human labour or augment the productivity of human workers. By analogy, video games (another category of software) generate a lot of revenue, but automate no human labour and don’t augment the productivity of human workers.
LLMs haven’t automated any human jobs and the only scientific study I’ve seen on the topic found that LLMs slightly reduced worker productivity. (Mentioned in a footnote to the post I linked above.)
If you’re interested in studies that evaluate the impact of LLMs on productivity, I can recommend the blog of Ethan Mollick. For example this post from September 2023: https://www.oneusefulthing.org/p/centaurs-and-cyborgs-on-the-jagged
It found that consultants with AI access outperformed consultants without AI access, on most dimensions that were measured. Ethan has since participated in several other studies on the industry adoption of AI.