Isabelle Levent
@isabellelevent
@isabellelevent
on metaphors for LLMs
The Lab’s primary focus is on the ways in which artists and designers are adopting, adapting and remaking AI processes, building their own datasets and reaching into the ‘grey box’ of AI technologies.
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.
I think that the language model’s failure to dismiss the class results from a slightly different cause than my student’s failure to dismiss the class with the same utterance. While the student’s failure arises from their lack of authority, the model’s failure results from the fact that it functions more like a citation of language rathe
... See moreLike oil and land, data are a common that is commodified by private actors for profits. The commons being commodified is our essence as humans: our interactions with society at large.
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,
... See moreIf I have an idea for a novel, but the computer writes most of it, is it still my story? This question will not be answered with numbers about how many words I or the computer wrote. It’s going to be answered culturally; it’s going to be a feeling we have about where authenticity or truth really lies.
They will shade our constant submissions to the vast digital commons, intentional or consensual or mandatory, with the knowledge that every selfie or fragment of text is destined to become a piece of general-purpose training data for the attempted automation of everything. They will be used on people in extremely creative ways, with and without the
... See moreAcademically, 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.