[[{“value”:”As many of you know, I grew up reading (on knowledge) Hayek, Michael Polanyi, Ludwig Lachmann, Mario Rizzo, and others in that tradition. For these Austrian and Austrian-related thinkers, knowledge is about how different parts of a system fit together, rather than being a homegeneous metric easily expressed on a linear scale. There is no
The post Austrian economics and AI scaling appeared first on Marginal REVOLUTION.”}]]
As many of you know, I grew up reading (on knowledge) Hayek, Michael Polanyi, Ludwig Lachmann, Mario Rizzo, and others in that tradition. For these Austrian and Austrian-related thinkers, knowledge is about how different parts of a system fit together, rather than being a homegeneous metric easily expressed on a linear scale. There is no legible way to assess the smarts of any single unit in the system, taken on its own. Furthermore, there are many “walls,” meaning knowledge is bumpy and lumpy under the best of circumstances. It thus makes little sense to assert that an entity is “3x smarter” than before. In my early 20s I received a second “dose” of related ideas through complexity theory and non-linear dynamics, some of those frameworks having Hayekian roots.
When people came along and made various predictions about AI following “scaling laws,” I was never extremely impressed. I did not feel I had the technical background to contradict them, I just was never sure they were measuring the social import of that knowledge in a meaningful way.
That is one (not the only) reason I have never been much persuaded by either the AI doomsters nor the AI utopians. Both seemed to me misguided rationalists, operating with a fundamentally pre-Hayekian understanding of knowledge. Furthermore, Ludwig Lachmann frequently told me that capital was a structure based on relationships of complementarity, mirroring the Hayekian knowledge insight in capital theory.
I find Matt Clifford’s observation “There is no AI-shaped hole in most organizations” to be a very useful starting point for analysis.
I am also much influenced by the history of artistic and scientific revolutions. Consider the Florentine artistic Renaissance, or say the blossoming of Germanic classical music in the 18th century. There were thick markets of rivalrous creators, sophisticated audiences, new technologies to work with, a diversity of funding sources, and strong beliefs that something very important was at stake, among other preconditions. Do we find similar preconditions active in AI worlds today? I would argue yes, but of course that could be contested. In any case, it is another and very different way of trying to understand the likely future pace of AI progress. “Does this feel like the environment that produced the Beatles and Bob Dylan?” “The Scot tinkerers of the Industrial Revolution?” “The German Romantics?”
Now in the last two days we have seen various media accounts (Bloomberg), some citing AI experts, claiming that scaling has slowed down or is no longer working. Put aside whether these claims are correct. I remain bullish on AI progress, because the AI world is showing so many signs of significant ferment. Ask yourself for instance — is it attracting the best minds and most ambitious people? Just as the postulation of AI scaling never so much excited me, neither does talk of its possible diminution much discourage me.
It is still a question of whether and at what pace we can find or create “AI-shaped holes” in organizations, or with individuals. And that is up to us.
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Economics, Philosophy, Uncategorized, Web/Tech
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