Isabelle Levent

"The data we licensed from Shutterstock was critical to the training of DALL-E,” said Sam Altman, OpenAI’s CEO. “We’re excited for Shutterstock to offer DALL-E images to its customers as one of the first deployments through our API, and we look forward to future collaborations as artificial intelligence becomes an integral part of artists’

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.

If it was possible to deduce how much of an influence each individual image has on the final outcome (and the owner of each image was known and labelled, which I currently doubt happens), would it be simple to compensate people then?

Much of the discussion this year is about text-to-image, but I believe this is a temporary stage; these things are going to continue evolving very quickly.

Imagine an art-lover at an exhibition entitled ‘Dots 2008’. He speaks to two artists, each displaying a painting. In both cases, the art-lover cannot see past the seemingly random arrangement of dots of paint. He mentions this to the first artist, who says: “Oh, no, they’re not randomly placed. Each dot represents a friend of mine. The colour of

The Lab’s mission is also to develop a critical literacy that can help cultural institutions approach AI technologies as advanced and multilayered media. While reliant on the highly specialised theoretical work needed to untangle issues such as ‘distributed authorship’ (Ascott 2005; Zeilinger 2021) involved in artistic research, the Lab does not

There’s another edge case as well; in theory, with the same prompts and the random seed that’s used for generating the images, you could end up with someone else generating the same, or a very similar, image as what you created.