Large Language Models are built on the collectively accumulated knowledge of humanity -- an "epistemic commons" that is being privatized while the knowledge workers whose labor made these models possible are threatened by automation. This paper bundles multiple mutually independent lines of argumentation that converge on the same conclusion: humanity has a justified claim to participation in AI value creation. The justifications range from a "maintenance obligation" (the obligation follows from the input received, not from the quality of the output) through the "variation thesis" (securing all as a rational obligation), the "variation cycle" (AI permanently requires human variation), and "Kantian ethics" (contradiction in conception) to the "Logos tradition" (knowledge belongs to no one) and the "Human-LLM analogy" (which compels a revision of intellectual property). The strength of the argument lies in its convergence: under no conceivable scenario do all lines of justification fail simultaneously -- they at most shift their addressee or their level of justification. A Five-Pillar Model is proposed: (1) AI value creation levy, (2) public data royalties, (3) direct citizen dividend, (4) public AI infrastructure, and (5) a coexistence guarantee for individual copyrights.
Lukas Geiger (Thu,) studied this question.