Isabelle Levent

Many methods for creating these models don't (and to be honest can't) attach the name, website and other details of every image and piece of text used to a create a new image in the metadata to every step of the process.

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.

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. 

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

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

In particular, anthropomorphizing the AI system mitigates the responsibility to the artist, while bolstering the responsibility of the technologist. Critically, this suggests that the responsibility that will be allocated to individuals in the creation of AI art will be dependent on the choice of language and framing used to discuss it

For a computer to make a subtle combinational joke, never mind to assess its tastefulness, would require, first, a data-base with a richness comparable to ours, and, second, methods of link-making (and link-evaluating) comparable in subtlety with ours. 

the reconfiguration of culture as a domain of not just human-made meanings but also machinic calculation