There have been a lot of technologies that were going to be the next big thing, but in the last analysis could not pull their weight economically. AI may find its spot on that illustrious list. From Charles Hugh Smith at oftwominds.com:
In the real-world, the costs are all we know for sure and profits remain elusive and contingent.
No one knows how the flood of AI products will play out, but we do know it’s unleashed a corporate frenzy to “get our own AI up and running.” Corporate fads are one of the least discussed but most obvious dynamics in the economy. Corporations follow fads as avidly as any other heedless consumer, rushing headlong into whatever everyone else is doing.
Globalization is a recent example. Back in the early 2000s, I sat next to corporate employees on flights to China and other Asian destinations who described the travails and costly disasters created by their employers’ mad rush to move production overseas: quality control cratered, proprietary technologies were stolen and quickly copied, costs soared rather than declined, and so on.
So let’s talk about costs of AI rather than just the benefits. Like many other heavily-hyped technologies, Large Language Model (LLM) AI is presented as stand-alone and “free.” But it’s actually not stand-alone or free: it requires an army of humans toiling away to make it functional: “We Are Grunt Workers”: The Lowly Humans Helping Run ChatGPT Make Just $15 Per Hour (Zero Hedge).
“We are grunt workers, but there would be no AI language systems without it. You can design all the neural networks you want, you can get all the researchers involved you want, but without labelers, you have no ChatGPT. You have nothing.”
The tasks performed by this hidden army of human workers is euphemistically sanitized by corporate-speak as data enrichment work.