Why Responsible AI Datasets?
The rapid development of large language models (LLMs) by major tech companies has led to a wave of copyright infringement lawsuits and regulatory scrutiny worldwide. The lack of transparency and compliance in dataset creation is at the heart of these issues.
Recent Lawsuits & Copyright News (2023–2025)
- Studio Ghibli vs. OpenAI (2025): Studio Ghibli filed a lawsuit against OpenAI for unauthorized use of its copyrighted films and scripts in LLM training datasets. This case highlights the ongoing risk of using copyrighted material without explicit permission.
- New York Times vs. OpenAI & Microsoft (2023): The New York Times sued OpenAI and Microsoft for copyright infringement, alleging their articles were used to train LLMs without consent or compensation.
- Authors Guild vs. OpenAI (2023): A class-action lawsuit by prominent authors (including George R.R. Martin and John Grisham) against OpenAI for using their books in training data without authorization.
- Getty Images vs. Stability AI (2023): Getty Images sued Stability AI for scraping and using millions of copyrighted images to train generative AI models.
- Universal Music Group, Sony, Warner vs. Anthropic (2024): Major music publishers filed suit against Anthropic for distributing copyrighted song lyrics via its Claude LLM.
- Comics Creators vs. Meta (2024): Comic book artists and publishers sued Meta for using their works in Llama model datasets without permission.
- Google & Mixtral (2024–2025): Both companies have faced legal threats and regulatory investigations in the EU and US for lack of dataset transparency and potential copyright violations.
Major Problems with Current LLM Datasets
- Lack of Consent: Most LLM datasets are built by scraping the web without explicit permission from content creators or rights holders.
- No Provenance Tracking: Datasets rarely document the source, license, or legal status of included data.
- Copyright Infringement: Use of copyrighted books, articles, images, and code without authorization is widespread.
- Non-Compliance with Global Laws: Datasets often fail to comply with the EU AI Act, GDPR, UK Copyright Law, US Copyright Law, and other international standards.
- Opaque Practices: Major providers do not disclose full dataset contents or allow independent audits.
- Ethical Risks: Inclusion of personal data, biased or harmful content, and lack of accountability.
Global Standards & Legal Requirements
- EU AI Act: Requires transparency, risk management, and lawful data sourcing for AI systems deployed in the EU.
- GDPR: Prohibits use of personal data without consent or legal basis.
- UK & US Copyright Law: Protects creative works from unauthorized reproduction and use, including in AI training.
- Other Jurisdictions: Many countries are introducing or updating laws to address AI and data rights.
Our Solution
The Responsible AI Dataset Initiative is committed to building datasets that are fully transparent, legally compliant, and respectful of creators’ rights. We track provenance, obtain permissions, and align with global standards—setting a new benchmark for ethical AI development.