I don't understand how knowledge, either public or private, could get damaged.

Though the income of the individuals and businesses that rely on the expertise of the knowledge would be damaged. Is that what you meant?

Edit: At this stage, the revenue made by the AI labs is almost entirely spent on the formation of fixed capital and opex. The demand is mobilizing physical resources with money. Atoms are relocated and reconfigured into compute racks. But eventually, the created productivity will perhaps make supply-elastic goods extremely cheap and abundant, while the supply-inelastic goods will be worth even more relative to the elastic ones.

After all, money is simply a token for the transmission of physical resources. It doesn't create stuff out of thin air. When new stuff is created, it just makes money cheaper, so that the banks can respond with more money to counteract it. More stuff -> deflation -> more money creation allowed to undo the deflation.

But the "exchange rates" between different goods and services will diverge. That's also why I don't think a direct money transfer like UBI would fix the problem, when it doesn't change the divergence of relative economic values of different goods. Let's say, extremely cheap software and entertainment, but unaffordable healthcare and housing. More money for everyone doesn't make limited resources available. So, what I am leaning into is some sort of Georgist policy. That could hopefully mitigate the price divergence, assuming that AI cannot make every commodity equally abundant.

Well, lots of ways. One is some degree of model collapse, as the slop-enshittified Internet itself is ingested as training data--despite the AI companies' best efforts to prevent this, they won't be altogether successful.

But the more consequential one may be that few are motivated to contribute more training data to make Dario or Sam richer. This is already playing out in open source. People write open-source so humans can use it, in that human way that humans do, not to make Dario richer because his models will emit statistically convoluted copies of that open-source. What is my incentive to open-source something that I could commercialise today, compared to what it was before the LLM age?

(Many will say there's not much point in commercialising it, either, but to the extent that software still has commercial value, the appeal of the alternative path has greatly diminished.)