Adobe is buying videos for $3 per minute to build AI model

Adobe’s Strategy and Legal Positioning

• Many see Adobe’s paid, licensed-data approach as a deliberate contrast to “scrape everything” tactics from other AI companies.
• Supporters say this reassures risk‑averse enterprise customers who fear copyright liability and want a clean provenance story.
• Critics argue Adobe is betting that courts will eventually penalize large‑scale unlicensed scraping, thus giving Adobe and similar rights‑holders a defensible moat.
• Some question whether long‑term licenses over persona/likeness should even be signable, raising possible future constraints (e.g., time-limited or revocable rights), though others see that as an overreach.

Copyright, Fair Use, and Training Data

• Debate over whether using content for training is more like humans learning from existing works (often seen as fair use) or like copying without permission.
• Comparisons made to: streaming vs downloading, ripping DRM’d content, libraries, classroom use, memes, and derivative characters in comics.
• One side argues law and policy should prevent big content conglomerates from monopolizing training data.
• Others think some form of licensing/compensation is inevitable, but worry it still may leave most creators underpaid, as with music streaming.

Compensation: Is $3/Minute Fair?

• Some view $3/min as attractive “found money,” especially for low‑effort footage or unused material.
• Others point out that high‑quality or animated content can take hours per minute to produce, reducing the effective rate to near exploitative levels.
• Because the deal is reportedly non‑exclusive, some see it as incremental revenue; others still object to selling training rights so cheaply.
• Concern that Adobe is selectively attracting creators willing to sell cheap, which might bias model output quality.

Creator Impact and Future of Work

• Worries that AI trained on creators’ work will undercut their own future income, effectively paying once to be replaced.
• Counterargument: technology has always displaced some jobs while creating others, and society still runs at low unemployment, albeit with many “bullshit jobs.”
• Existential concerns raised about AI/robotic automation, UBI, and who ultimately captures the value.

Open vs Corporate AI and Regulatory Capture

• Some argue open models trained on unlicensed data are crucial to prevent AI being locked behind corporate paywalls.
• Others note current open models are mostly downstream of big-company spending and may be threatened if licensing becomes mandatory.
• Fears expressed about “data laundering” (using synthetic data to obscure original unlicensed sources) and future lobbying to restrict open-source or small‑scale model training.