Ed Newton-Rex says generative AI has an ethics problem. He ought to know, because he used to be part of the fast-growing industry. Newton-Rex was TikTok’s head AI designer and then an executive at Stability AI until he quit in disgust in November over the company’s stance on collecting training data.
After his high-profile departure, Newton-Rex threw himself into conversation after conversation about what building AI ethically would look like in practice. “It struck me that there are a lot of people who want to use generative AI models that treat creators fairly,” he says. “If you can give them better decisionmaking tools, that’s helpful.”
Now Newton-Rex has launched a new nonprofit, Fairly Trained, to give people exactly that type of decisionmaking tool. It offers a certification program to identify AI companies that license their training data. The AI industry now has its own version of those “fair trade” certification labels you see on coffee.
To earn Fairly Trained’s certification label, which it calls L Certification, a company must prove that its training data was either explicitly licensed for training purposes, in the public domain, offered under an appropriate open license, or already belonged to the company.
So far, nine companies have received the certification, including image generator Bria AI, which trains exclusively on data licensed from sources like Getty Images, and music generation platform LifeScore Music, which licenses work from all the major record labels. Several others are close to completing their certification. The nonprofit charges a fee of $500 to $6,000, depending on the size of the applicant’s business.
OpenAI— the world’s leading generative AI company—recently argued that it is impossible to create generative AI services like ChatGPT without using unlicensed data. Newton-Rex and the first companies to get Fairly Certified’s stamp of approval disagree. “We already think of it as a mandatory thing to do,” Bria CEO Yair Adato says of licensing data. He compares AI models built on unlicensed data to Napster and the Pirate Bay, and his own company to Spotify. “It’s really easy for us to be compliant,” says Lifescore Music’s cofounder Tom Gruber, who is also an adviser to Fairly Certified. “The music business really cares about provenance and rights.”
Newton-Rex says it has support from trade groups like the Association of American Publishers and the Association of Independent Music Publishers, as well as companies like Universal Music Group. But the movement to overturn the AI industry’s standard approach of scraping training data at will is still very much in its infancy. And Fairly Trained is a one-man operation. Not that Newton-Rex minds; he still has a startup founder’s mindset. “I believe in shipping things early,” he says.
The nonprofit is also not the only one trying to standardize the idea of labeling AI products with information about their ingredients. Former Warner Music Group executive Howie Singer, who now studies how technology is changing the music industry, sees similarities between Fairly Trained and the Content Authenticity Initiative, a project spearheaded by Adobe to help people track the authenticity of images. “This is a good step,” he says of Newton-Rex’s project.
