Ed Newton-Rex, former VP of Audio at Stability AI, has launched ‘Fairly Trained,’ a non-profit certifying generative AI companies for ethical training data practices, aiming to address concerns over data scraping and copyright infringement. The initiative has already certified nine companies and introduced the ‘Licensed Model certification’ to ensure ethical use of training data.
Ed Newton-Rex, ex-VP of Audio at Stability AI, announces the launch of ‘Fairly Trained’
Ed Newton-Rex, former VP of Audio at Stability AI, has launched ‘Fairly Trained,’ a non-profit organization dedicated to certifying generative AI companies for fairer training data practices.
Why is Fairly Trained important?
The initiative aims to distinguish between companies that train their AI on unfairly scraped data and those that adopt a more ethical approach by licensing.
Practical Solutions and Value
The ‘Fairly Trained’ program introduces its first certification, the ‘Licensed Model certification.’ The goal is to highlight AI models that use training data ethically, ensuring no copyrighted work is used without a license. This applies to AI models in various fields like image and music generation.
Companies must thoroughly check the rights status of their training data, and detailed records of the training data used must be maintained. The application involves a detailed written submission and a review process, concluding with certification and annual reevaluation.
While this first certification does not address all concerns around generative AI training, such as the opt-in vs. opt-out debate, it’s a step forward. Newton-Rex acknowledges this and expresses hope for future certifications to address these nuances further.
It’s important to note that the program has already been well-received in the industry, with nine companies already certified, covering domains like image and music generation.
Testimonials
Dr. Yair Adato of BRIA AI commends the initiative, stating in a blog post, “We proudly support the Fairly Trained certification. This initiative counters the industry’s opacity in data procurement, ensuring companies meet rigorous ethical standards.”
Christopher Horton, SVP at Universal, said, “We welcome the launch of the Fairly Trained certification to help companies and creators identify responsible generative AI tools that were trained on lawfully and ethically obtained materials.”
Future Prospects
Despite his resignation at Stability AI, Newton-Rex expressed optimism about the potential for a harmonious relationship between generative AI and the creative industries, which has now been underscored by Fairly Trained.
Could this be the year of increased accountability for AI companies and more transparent data practices?
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