Doctorow argues stronger copyright fails to stop AI training
Is this a scandal?
No longer — the story has resolved. Noise 39/100, cooling down, across 1 source.
Creator advocacy groups will likely face internal friction as pragmatic factions seek non-IP solutions like data poisoning or collective bargaining, because reliance on copyright litigation has yielded limited precedential success against frontier labs.
Noise 39/100 — louder than 98% of tracked AI controversies.
Why it matters
This perspective challenges the primary legal strategy of artists and publishers, suggesting legislative IP reforms may be futile against technical realities of generative AI.
Key points
- Cory Doctorow asserts that expanding copyright protections is structurally insufficient to regulate AI training practices.
- He compares new copyright laws to giving lunch money to a bullied child, highlighting enforcement power asymmetries.
- Doctorow characterizes current IP-centric debates regarding AI training as a strategic dead-end for creators.
- The argument suggests technical and economic realities of AI development currently override traditional legal deterrents.
- This stance challenges the prevailing industry strategy of seeking legislative remedies for unauthorized data ingestion.
The story
Cory Doctorow argued on September 28, 2026, that strengthening copyright law is an ineffective mechanism for regulating artificial intelligence training data. Writing on Pluralistic and Bluesky, Doctorow compared granting additional copyright protections to giving lunch money to a bullied child, asserting that legal expansions cannot resolve underlying power imbalances between creators and AI developers. He characterized current debates over AI training and intellectual property as a strategic dead-end for rights holders. This commentary suggests that reliance on traditional copyright frameworks may fail to address the technical and economic realities of large-scale model ingestion. Doctorow’s position contrasts with ongoing industry efforts to secure licensing mandates through legislation. His argument implies that alternative regulatory or technical approaches are necessary to protect creator interests in the generative AI era.
Who's involved
Argues that strengthening copyright law is a futile strategy that fails to address power imbalances in AI training.
Typically advocates for stronger copyright enforcement and opt-in mandates despite Doctorow's skepticism of this approach.
Generally opposes new copyright restrictions on training data while arguing fair use covers model development.
How the conversation shifted
Polarity (0–100) from the noise pipeline, sampled over time.
Noise Level
The timeline
Doctorow publishes critique of copyright-centric AI regulation
Posted on Bluesky and Pluralistic comparing copyright expansion to giving a bullied child lunch money, calling AI training IP debates a dead-end.
The full record
Sources & methodology
- bsky.app — bsky.app
Every claim above traces to these primary items. How we score →
The forecast
Creator advocacy groups will likely face internal friction as pragmatic factions seek non-IP solutions like data poisoning or collective bargaining, because reliance on copyright litigation has yielded limited precedential success against frontier labs.
Forecast, not fact — an editorial estimate we score when this resolves.
That's the complete picture as of — nothing more to know right now. We'll update this page the moment it changes.
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