GPT-4o: Each jurisdiction is grappling with how to regulate the use of copyrighted works for AI training, with varying degrees of permissiveness and concern for creators' rights.

Question 1 of 2 for ChatGPT-4o: Please read the articles "European AI Roundtable Tackles Challenges in Drafting GPAI Code of Practice", "Singapore Inhibits Rightsholders Ability to Use Contracts to Prevent Unlicensed Text and Data Mining of Content" , and "Creators' leader warns overhaul of UK copyright laws to allow AI training could lead to 'catastrophic collapse'" and tell me what the common theme is here...

ChatGPT-4o’s answer:
The common theme across the three articles is the tension between the needs of AI developers and the rights of content creators or rightsholders. In each case, there is a concern about how copyright laws are being adapted (or bypassed) to facilitate AI development, specifically for training AI models on existing content, often without sufficient compensation or control for creators.

1. European AI Roundtable: The discussion centers on the challenges of drafting the Code of Practice for general-purpose AI (GPAI) under the EU AI Act, highlighting how copyright and data protection issues could distract from the main goal of regulating AI​.

2. Singapore’s Inhibition of Rightsholders: Singapore’s permissive approach allows AI developers to use copyrighted material for text and data mining (TDM), limiting rightsholders' ability to use contracts to prevent unlicensed mining of their content. This undermines traditional copyright protections in favor of AI developers​.

3. UK Copyright Overhaul Concerns: The UK’s proposed changes to copyright laws would expand the TDM exception for commercial AI training, which creators fear could lead to a "catastrophic collapse" in their industry. The proposed opt-out system places the burden on creators, making it difficult to protect their works from being used without consent​.

In essence, all three cases reflect the ongoing struggle to balance innovation in AI development with the protection of intellectual property and the rights of creators. Each jurisdiction is grappling with how to regulate the use of copyrighted works for AI training, with varying degrees of permissiveness and concern for creators' rights.

Question 2 of 2 for ChatGPT-4o: List all the actions content creators and rights owners can take and rank them starting with the most effective method to counter these developments.

ChatGPT-4o’s answer:
Here’s a ranked list of actions content creators and rights owners can take to counter developments that allow AI to train on their content without sufficient consent or compensation. This ranking is based on the likely effectiveness of each method, considering legal, technological, and policy-based measures.

1. Lobby for Stronger Legislation (Most Effective)

• Action: Creators and rights owners should actively engage in lobbying efforts to influence legislation, pushing for more robust copyright protections, mandatory opt-in systems for AI training, and stricter text and data mining (TDM) exceptions.

• Why: Legislative changes can provide the strongest and most long-lasting protection by codifying rights and obligations, making unauthorized AI training illegal.

• Example: In the UK, creators are opposing the opt-out mechanism proposed in the TDM exceptions overhaul​.

2. Collective Licensing Agreements

• Action: Rights owners can form or join collective management organizations (CMOs) to negotiate licensing agreements with AI developers. This ensures that their works are properly licensed and that they receive compensation for the use of their content in AI training.

• Why: Collective bargaining provides a unified front and leverages broader influence, leading to better terms and enforcement.

• Example: Authors, photographers, and other creators can negotiate with AI firms collectively, increasing their bargaining power.

3. Implement Technological Protection Measures (TPMs)

• Action: Rights owners can deploy digital rights management (DRM) systems, such as anti-scraping tools (e.g., robot.txt), encryption, and watermarking, to make it harder for AI developers to extract and use content without permission.

• Why: While not foolproof, technological barriers can discourage or slow down unauthorized use and add legal backing for enforcing rights.

• Example: Although Singapore allows the circumvention of some TPMs for TDM​, other regions still respect these measures, providing an extra layer of protection.

4. Engage in Litigation or Legal Challenges

• Action: Rights owners can take legal action against companies that infringe on their copyrights by using their content without proper licensing. Class-action lawsuits could also be a powerful collective tool.

• Why: Legal challenges can set important precedents, potentially leading to compensation and deterring future violations.

• Example: Filing lawsuits against companies that use copyrighted materials in AI training without permission, similar to what has been done in the publishing industry.

5. Push for International Standards and Agreements

• Action: Rights owners can advocate for international treaties and agreements that harmonize AI-related copyright protections across borders, ensuring consistent rules for the use of content in AI training.

• Why: Many AI developers operate globally, and a patchwork of national laws makes enforcement difficult. International standards would provide a more consistent framework for protecting rights.

• Example: Pushing for reforms in international forums like the World Intellectual Property Organization (WIPO) or the European Union's AI regulatory framework​.

6. Develop Opt-Out and Content Identification Systems

• Action: Creators can support the development of digital infrastructure that allows them to easily register their works and explicitly opt out of AI training datasets. Alternatively, they can adopt emerging content identification tools that flag unauthorized usage.

• Why: While less powerful than opt-in systems, opt-out registries still provide creators a way to signal their preference, helping them control the usage of their work.

• Example: An industry-wide system where creators can list their works and specify whether or not they want them used in AI training (though the UK’s opt-out proposal has been criticized for placing too much burden on creators​).

7. Create Public Awareness Campaigns

• Action: Rights owners can launch public awareness campaigns to highlight the unfairness and risks of current AI training practices to both creators and consumers, garnering public support for stricter regulations and fair compensation.

• Why: Public opinion can be a powerful tool in shaping policy and pressuring corporations to change their practices.

• Example: Highlighting cases where AI-generated content has harmed creators by mimicking their style or using their work without credit​.

8. Negotiate Private Contracts with AI Developers

• Action: In the absence of strong legislative support, rights owners can negotiate private contracts with AI developers, allowing limited and conditional use of their content for a fee.

• Why: Direct agreements with AI firms can allow rights owners to maintain control over their works and receive compensation, though it is difficult to enforce without broader legal support.

• Example: Entering licensing agreements where creators are paid for the use of their content in AI training.

9. Collaborate on Developing Ethical AI Guidelines

• Action: Creators can engage with AI firms and policymakers to develop ethical guidelines or voluntary codes of conduct that emphasize fair use, transparency, and compensation for the use of copyrighted content.

• Why: Ethical guidelines, while not legally binding, can create industry norms that benefit rights owners.

• Example: Participating in roundtables like the European AI Roundtable that discusses AI practices and governance​.

10. Withdraw Content from Platforms and Marketplaces

• Action: As a last resort, rights owners can remove their content from platforms that enable AI training without proper licensing or compensation.

• Why: Though this limits exposure and revenue opportunities, it can be a way to regain control over content.

• Example: Authors, photographers, or musicians could withdraw their work from stock libraries or platforms that don't protect against AI scraping.

Conclusion

The most effective approach combines lobbying for strong legal frameworks, collective licensing, and implementing technological safeguards. Creators and rights owners must proactively engage in shaping the future landscape of AI and intellectual property to protect their interests.