Isabelle Levent

Our intuitive moral understanding of actors and transgressions may be at odds with the inherent complexity of AI systems.

Second, we should create a legal regime that can make our data’s collective value something we can bargain over as a group.

Academically, this is a collision of everything from computer science and art history to media studies to disruptive innovation to labor economics, and no one of these disciplines seems sufficient to cover the topic. 

However, we often found that it was the unexpected differences between the prompt and the generated image’s interpretation of it that yielded new insight for and excitement from participants.

As more artists gain access to AI and take up the tools, artists will have a whole new look — both how they look making art and how their art develops.

We find that models learn just as fast with many prompts that are intentionally irrelevant or even pathologically misleading as they do with instructively “good” prompts. Further, such patterns hold even for models as large as 175 billion parameters (Brown et al., 2020) as well as the recently proposed instruction-tuned models which are trained on