AI Copyright Debate: The Core Lies in Licensing Mechanisms and Value Distribution
Recent debates over using copyrighted data for AI training center on establishing licensing mechanisms and distributing surplus value. Industrial-scale pre-training shouldn't be simply viewed as fair use; the industry urgently needs scalable licensing solutions, and copyright systems will eventually reach a new balance.
Confirmed
- Refuting the "Value Transfer" argument: @dhadfieldmenell believes that summarizing unauthorized training as mere "value transfer" is misleading, implying creators originally held massive wealth and power. A more accurate analogy is "undiscovered oil"—AI developers actually discovered and created new value at great cost, yet refuse to share the surplus returns.
- Pre-training is not fair use: The author explicitly opposes classifying industrial-scale pre-training directly under "fair use." Since AI companies have already shown a willingness to pay for data, a market for training licenses clearly exists. Taking data without authorization inevitably disrupts this market.
- Need for scalable licensing: AI companies cannot negotiate one-off licenses with individual creators, and rights holders must accept some friction in collecting fees. The current challenge isn't that "licensing is unsolvable," but rather that the industry hasn't seriously tackled it. With creativity, scalable licensing is entirely achievable.
Why It Matters
- Data value will be reassessed: This conflict will eventually drive the copyright and IP systems to a new equilibrium. Throughout this process, data production and curation will become increasingly valuable, and intellectual property will remain a crucial component of the modern world.
- Both sides must compromise: The US intellectual property system originally emphasized public interest, and the framers of the Constitution didn't inherently side with copyright holders. Therefore, rights holders need to make new concessions for the AI era, while tech companies can no longer treat "fair use" as a default liability shield.
2026-07-28 ~ 2026-07-28 · 9 related posts
Primary sources
- AI copyright is a licensing problem, not an existential-risk problem — dhadfieldmenell ·
- AI Data Dispute: Wealth Transfer or Untapped Oil on Creator Land? — dhadfieldmenell ·
- A copyright-and-AI thread argues licensing at scale will require concessions from both sides — dhadfieldmenell ·
- The AI licensing problem is hard, but not impossible, the author says — dhadfieldmenell · 2026-07-28
- [source] A copyright-and-AI thread argues licensing at scale will require concessions from both sides — dhadfieldmenell · 2026-07-28
- Rights holders will need scalable ways to collect training royalties — dhadfieldmenell · 2026-07-28
- Industrial-scale pretraining should not be treated as fair use, the author argues — dhadfieldmenell · 2026-07-28
- [source] AI copyright is a licensing problem, not an existential-risk problem — dhadfieldmenell · 2026-07-28
- AI and copyright may end up in a new equilibrium where data curators gain value — dhadfieldmenell · 2026-07-28
- Copyright debate over AI training turns into a fight over value creation — dhadfieldmenell · 2026-07-28
- A copyright debate says unlicensed AI training is value creation, not value transfer — dhadfieldmenell · 2026-07-28
- [source] AI Data Dispute: Wealth Transfer or Untapped Oil on Creator Land? — dhadfieldmenell · 2026-07-28