Is the Free Ride Over? — Wikipedia Demands AI Companies to "Cease Unauthorized Use" and "Fair Compensation"

1. What Happened: Wikipedia's "Red Line"

• Core of the Request:

  1. Stop Scraping (the act of massively retrieving web pages with robots),

  2. Transition to Paid API (Wikimedia Enterprise),

  3. Proper Credit to Contributors (Attribution).
     The foundation aims to institutionalize **"responsible access" and "fair compensation"** based on the current reliance of AI companies on Wikipedia. Wikimedia Foundation
     
     

• Awareness of the Issue:
  The proliferation of summary displays and direct answers by generative AI has resulted in a decrease in human page views, potentially reducing donation opportunities and community participation. The foundation is concerned about sustainability, considering the increased server load. Media outlets have also reported the policy shift from **"scraping to paid API"**. Chosun Ilbo+2Techzine Global+2
  
  

• Official Basis:
  The primary source is the Wikimedia Foundation's blog post "In the AI era, Wikipedia has never been more valuable". It positions the Enterprise API as a "responsible access method suitable for scale to support the nonprofit mission." Wikimedia Foundation

2. Why Now: Wikipedia as "Public Infrastructure" in the AI Era

• AI Performance Relies on Wikipedia
  Research and media reports indicate that excluding Wikipedia from training data results in reduced accuracy, diversity, and verifiability. Wikipedia is a knowledge base refined by **"neutrality, verifiability, and citation principles" upheld by hundreds of thousands of volunteer editors, serving as a quality benchmark for AI. . eWeek
  
  

• Open and Free Are Different
  Open licenses like CC BY-SA allow use under conditions (attribution, share-alike, etc.). However, massive and continuous commercial reuse and excessive technical load on sites are reasonably adjusted through API or license agreements. The foundation stands to protect the sustainability of **"free knowledge", not denying the continuation of free unlimited access, but visualizing the balance between scale and responsibility**. Wikimedia Foundation
  
  

• This Year's Preparations
  By April 2025, data set provision with Kaggle will offer efficient access means for researchers and small developers. The foundation has been strengthening **"legitimate, efficient, machine-readable"** routes other than scraping. The Verge

3. What Specifically Is Being Requested?—Operational Level Analysis

1. Switching Access Methods

   • Repeated Full-Page Scraping → Enterprise API
     The API provides update differences and structured information, enhancing server load reduction, availability assurance, and auditability. Wikimedia Foundation
     
     

2. Thorough Attribution

   • Clearly indicate the contributions of Wikipedia and its contributor community in generated content, search results, summaries, etc.. This directly relates to transparency and verifiability. Wikimedia Foundation
     
     

3. Financial Support

   • Support infrastructure and community continuously through paid licenses and donations. Address the asymmetry of reduced traffic and increased load. Wikimedia Foundation

4. Impact Analysis: AI Companies, Platforms, Users

• AI Companies

  • Cost Structure: While API costs and implementation costs for attribution increase, stable supply, differential distribution, and schema assurance reduce operational costs and legal risks. Tech in Asia

  • Legal and Reputation: Unauthorized use issues have already surged. Reddit is in litigation over unauthorized scraping, and disputes and settlements with publishers and media continue. Aligning with Wikipedia's cooperative approach also aids in reputation management. AP News+1
    
    

• Platforms (Search, SNS, News)

  • Compliance Requirements: Platforms need to prepare UI for attribution display in AI summaries and answers. How to redesign link referrals is a major issue, especially for larger platforms. Wikimedia Foundation
    
    

• End Users

  • Quality and Verification: When sources are clearly indicated, verifiability improves. With pathways to edit history and notes, users can engage with the process of fact discovery. GIGAZINE

5. Japan vs. Overseas: Differences in Perception of Systems, Business Practices, and "Publicness"

• Overseas (Centered on US and Europe)

  • Generalization of Large-Scale Licenses: Media companies are polarized between litigation or comprehensive contracts. Wikipedia, being nonprofit, proposes paid API + attribution from the perspective of sustainability × public goods. Innovetopia

  • Transparency Orientation: Emphasizing the importance of clearly indicating data sources, machine-readable supply routes, and auditability. The provision with Kaggle is part of this initiative. The Verge
    
    

• Japan

  • The Misunderstanding Barrier of "Open = Free": Understanding of CC licenses in educational and media settings is still developing. There is a tendency to overlook citation and share-alike conditions, leading to ambiguity in the distinction of large-scale commercial reuse.

  • Practical Implications: Japanese AI and major domestic platforms should incorporate UI/UX for attribution and API transition costs early on. Public relations should focus on explaining the international consensus of **"responsible access"** rather than "free to paid." itmedia.co.jp

6. Common Misunderstandings and Correct Understanding

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