The underlying driver of this shift is hard to grapple with. It doesn’t derive from what these models produce, but what they produce from: vast streams of creative writing, photographs, and drawings shared online. The authors of these works find themselves grappling with the reality that they have co-created a massive corpus of training data for the very AI platforms that would undermine their professions. To many, it feels as if their creative fruits have been harvested and blended by an algorithmic juicing machine without warning or consent. Where labor power is strong, such as screenwriters and actors, strikes by creative professionals are centering these concerns. But this isn’t an option for independent, small-scale creatives who depend on the Internet to find clients and community.

Salvaggio, E. (2023, August 25). A New Contract for Artists in the Age of Generative AI. Tech Policy Press. https://techpolicy.press/a-new-contract-for-artists-in-the-age-of-generative-ai/

We shouldn’t be distracted by the claim that AI systems are somehow unknowable or too complex to understand. The relationship is simple: without human expression and creativity, these models wouldn’t exist. To protect the essence of open communication online, we should strive to make sharing feel safe and consensual. When that consent is violated, accountability ought to be placed where it belongs: at the level of the humans developing and deploying these systems. In the end, this framework will affirm the data and copyrights of artists, and create better conditions for training new AI systems on consensually shared data.