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UK Copyright and AI Text and Data Mining

UK copyright law has a specific text-and-data-mining exception for non-commercial research with lawful access, not a general commercial AI-training exception.

  • 3 perc olvasás
  • Utoljára frissítve
Ezen az oldalon3 perc olvasás
  1. Áttekintés
  2. Mély merülés
  3. Stratégiai hatás
  4. The Future of UK Copyright and AI Text and Data Mining
  5. Valós megvalósítás
  6. Kockázatok és védőkorlátok
  7. Végrehajtási ütemterv
  8. Folytassa a felfedezést
  9. Gyakran ismételt kérdések

Áttekintés

In March 2026 the government said a broad opt-out exception was no longer its preferred policy and proposed more evidence gathering rather than enacting that reform.

Mély merülés

Text and data mining (TDM) uses automated analysis to find patterns in text or data, and often requires copies. Section 29A of the Copyright, Designs and Patents Act 1988 permits copies for computational analysis where the sole purpose is non-commercial research and the researcher already has lawful access. Sufficient acknowledgement is required unless impractical. Contract terms preventing qualifying copies are unenforceable, while providers may take reasonable measures to protect network security or stability. This narrow exception is not a blanket route for commercial model training. If a TDM purpose is commercial, section 29A does not itself authorize the copying; permission or another applicable legal basis may be needed. It is also too broad to claim every commercial training use necessarily infringes: the work, acts, permissions, other exceptions and facts matter, and cross-border activity raises territorial questions. The government’s report of 18 March 2026 reviewed policy options from its 2024 consultation. It said opposition, evidence gaps and a changing market meant the broad copyright exception with opt-out was no longer its preferred way forward. Instead, government proposed gathering further evidence and considering alternative interventions. This report states policy direction; it did not enact a new TDM exception. Current analysis therefore starts with existing copyright law, permissions and case-specific legal questions while courts and parties resolve disputes. Organisations should avoid substituting policy announcements for enacted rules.

Stratégiai hatás

Kockázat és biztonság

A katasztrofális és a mindennapi mesterséges intelligencia okozta károk egyaránt attól függnek, hogy ki érti a kockázatokat, és ki tud cselekedni.

Tisztább döntések

A közéleti és szakmai műveltség határozza meg, hogy politikailag lehetséges-e az erős biztonsági politika.

Átvágva a felhajtáson

A világos magyarázatok csökkentik a hírverés, a laboratóriumi PR és a homályos etikai színház általi elkapását.

The Future of UK Copyright and AI Text and Data Mining

Government has shifted from its earlier consultation-stage support for a broad opt-out route toward further evidence gathering and alternative approaches. Timing and substance of future legislation remain uncertain. Licensing, court decisions and overseas policy may affect practice, so developers should maintain traceable datasets and revisit assessments. Review this position if Parliament enacts new rules; until then, keep section 29A, licensing and other exceptions distinct. Preserve dated copies of the report and licences relied upon. Monitor court decisions and enacted amendments, not announcements alone.

Valós megvalósítás

A university researcher with lawful access copies journal works for non-commercial computational analysis and acknowledges sources where required.

A business training a commercial model on protected works does not assume section 29A applies because the activity is called text mining.

A rights holder and developer agree a licence defining training, attribution, security and downstream use.

A team checks whether a work is public domain, licensed, or covered by another exception before copying it.

Kockázatok és védőkorlátok

  • Az egzisztenciális kockázat sci-fiként való kezelése, miközben a képesség összetett.

  • Zavaros felületi termékbiztonság a nagy autonómia melletti igazítással.

  • A nem angol nyelvű és nem szakértő közönségnek csak rossz minőségű forrásokat kell hagynia.

Végrehajtási ütemterv

  1. Különítse el a termékkárok, a visszaélések és az ellenőrzés elvesztésének/hibás beállításának kockázatait.

  2. Kérdezd meg, milyen bizonyítékok változtatnák meg az idővonalakról és a súlyosságról alkotott nézetedet.

  3. Részesítse előnyben az elsődleges forrásokat és a konkrét értékeléseket a marketinges állításokkal szemben.

  4. Határozzon meg egy cselekvési utat: karrier, politika, finanszírozás vagy készségek – nem csak a tudatosság.

Folytassa a felfedezést

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Gyakran ismételt kérdések

What is UK Copyright and AI Text and Data Mining?

UK copyright law has a specific text-and-data-mining exception for non-commercial research with lawful access, not a general commercial AI-training exception. In March 2026 the government said a broad opt-out exception was no longer its preferred policy and proposed more evidence gathering rather than enacting that reform.

What kind of TDM use does UK section 29A specifically permit?

Section 29A covers copies for non-commercial research when the user already has lawful access.

Does section 29A create a general exception for commercial AI training?

The exception exists, but its stated scope is non-commercial research.

What access condition applies to research TDM?

The exception does not grant a right to obtain the work; lawful access is required.

What did the March 2026 government report say about a broad opt-out exception?

The report moved away from that approach and proposed collecting more evidence.

Did the report itself create a new copyright exception?

A report describing proposals does not itself amend copyright legislation.