I'm surprised that the Author has missed a very important corollary to the diffusion of "genius theft" that they are bringing up.
And that is the diffusion of the beneficiaries. Maybe they think that OpenAI and Anthropic are actually worth, like a trillion dollars each and can therefore have value extracted from them. I'm not so convinced.
What if there aren't frontier labs spending billions on training a model. What if, instead, open source is at least mostly competitive with the top models. And if the models are open source (or weights, whatever you want to call it) the people benefiting are actually just rando people or startup founders.
What are you going to do if you want to extract this value from this diffuse set of beneficiaries? Put an arbitrary tax on anyone living on San Francisco or something??
The reality is that the author is trying to put the genie back into the bottle. All technological progress has winners and losers. It has people who are even benefiting from the rest of society and making personal gain based on that.
But, at the end of the day, doing accounting math on how much an individual benefited from a specific common good as vague as societal knowledge is impractical. And yet technological progress benefits all of society in a wholistic sense.
Additionally, the author focuses so much on the extraction of a public good, I am surprised that they failed to address that these labs are creating a public good as well. Who's to say that this "theft" is larger than the production of public goods that these labs give to the public in the first place.
I mean, my life has been massively improved by the fact that I have access to these models. And I'm not convinced that I have produce enough myself to outweigh this benefit that they are giving to me, so I consider it to be a fair trade.
> these labs are creating a public good as well.
https://en.wikipedia.org/wiki/Public_good
> In economics, a public good (also referred to as a social good or collective good)[1] is a commodity, product or service that is both non-excludable and non-rivalrous and which is typically provided by a government and paid for through taxation.
I can see that we are already excluding people from using models, whether it's China[1] or use in other harnesses[2] so its use can't be considered "non-excludable" or "non-rivalrous". It is also neither provided by the government nor funded through taxation.
I guess one change could be made to force LLM companies to release their (N-1)th model publicly and document architecture and system requirements, which would shift this to make these products actually public goods, however.
[1] https://x.com/AnthropicAI/status/2025997928242811253
[2] https://www.mindstudio.ai/blog/anthropic-openclaw-ban-oauth-...
Author here - thanks for reading and thoughtfully replying
I’d personally love a world where open weights compete with proprietary ones, but I don’t believe it solves the core concentration issue. In that scenario most value still flows to capital holders, it’s just hardware holders not model weight holders.
I emphatically do not want to put the genie back in the bottle nor do I believe it’s possible. Technology has never been restrained for long (export controls on cryptography textbooks in the 90’s comes to mind here)
I also have already personally benefited a great deal from LLMs. I actually frame the entire essay series from this perspective in my prelude essay here: https://www.wysr.xyz/p/a-consigliere-on-every-desk-and-in
However, I believe we may disagree on the definition of a public good. If you’re referring to the free tiers of private models, then I’d argue that unless there is some legal framework passed that forces the frontier labs to offer that to everybody, it’s a customer acquisition cost laundered as a public good. It could disappear at any time and probably will as cutting edge model margins are reduced via competition.
In general, I believe the best AI policy balances allowing for maximum competitive market dynamics while hedging existential economic disruption risk for the general population.
I’ll go into this deeper over the next few essays. Appreciate the feedback