The author makes an error while explaining Jevons’ Paradox. They say “the cheaper and faster we got at producing coal, the more coal we ended up using”. But that’s not paradoxical at all. That’s basic supply and demand curve from economics 101. It’s exactly what you’d expect.
Whereas if you take the extraordinarily difficult step of opening Wikipedia (https://en.wikipedia.org/wiki/Jevons_paradox), you understand the real paradox. Jevons observed that when steam engines get more efficient and individually use less coal, we end up deploying many more steam engines in many new industries and use cases, increasing coal consumption overall.
This seems like a basic oversight, maybe this guy hasn’t heard of Wikipedia. On the other hand, I think he wants to push the narrative that AI is seeing enormous productivity gains. He does this by using price per token, which has fallen. Very similar to Jevons supposedly observing “coal production”. But the author is struggling to point to new industries and use cases that were opened up by AI, like when we deployed steam engines back in the 1860s. So he misstates Jevons paradox, removes the paradoxical part, and makes it seem like his thesis makes sense.
Jevons’ Paradox could still apply here! I’m not saying it doesn’t. But we just haven’t seen the examples quite yet. A good example would be an observed surge in demand custom built software as software engineers become more efficient. But lower token costs ain’t it.
Whereas if you take the extraordinarily difficult step of opening Wikipedia (https://en.wikipedia.org/wiki/Jevons_paradox), you understand the real paradox. Jevons observed that when steam engines get more efficient and individually use less coal, we end up deploying many more steam engines in many new industries and use cases, increasing coal consumption overall.
This seems like a basic oversight, maybe this guy hasn’t heard of Wikipedia. On the other hand, I think he wants to push the narrative that AI is seeing enormous productivity gains. He does this by using price per token, which has fallen. Very similar to Jevons supposedly observing “coal production”. But the author is struggling to point to new industries and use cases that were opened up by AI, like when we deployed steam engines back in the 1860s. So he misstates Jevons paradox, removes the paradoxical part, and makes it seem like his thesis makes sense.
Jevons’ Paradox could still apply here! I’m not saying it doesn’t. But we just haven’t seen the examples quite yet. A good example would be an observed surge in demand custom built software as software engineers become more efficient. But lower token costs ain’t it.