Isabelle Levent

Because creativity  by definition  involves not only novelty but value, and because values are highly variable, it follows that many arguments about creativity are rooted in disagreements about value. 

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

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. 

Now none of this is meant to say that I think programmers, artists and engineers have no responsibilities when it comes to the outputs of machine learning models. In fact, I think we bear responsibility for everything these models do. (I never, for example, attribute authorship to a program or a model. If I publish the results of a text generator,

What’s difficult is to state our aesthetic values clearly enough to enable the program itself to make the evaluation at each generation.

A recurring theme in participant feedback was that the language model lacked taste and intentionality...In contrast, good writers are skilled not only in producing but also discerning good language. In other words, they have taste, the ability to decide why one sentence is interesting while another is not.