AI relies on tokens, explicitly or implicitly, and each token carries with it meaning that might be imperceptible to the user. By giving users the ability to see the tokens that are informing the output, they can discovery new creative paths and hone their input.
Only a few platforms make use of this as an interface pattern. Notably Midjourney's /describe function reveals the tokens and implied prompt behind an image. This can be applied to images that the generator produced, or human-created files. Using the variations pattern, Midjourney reveals 4 different interpretations of the image, and makes it easy for the user to reproduce each option to evaluate how closely it can reproduce the original tone, subject, and context.
This can produce some entertaining results, like learning "Joni Mitchell" was an influence for an abstract image. This also serves to ensure cleanliness in our images from copyright or copycatting. Midjourney explicitly calls out any artists whose work could be interpreted as an influence: both revealing the ethical flaws in its training data while helping users re-constitute their prompts to avoid that unintentional reference.
Alternatively, when interacting directly with an AI, you can simply ask it to share the tokens it relied on. This is not a technique layman users will be familiar with however, so it's unreliable as a solution. Furthermore, unless you are using the open input to communicate with the AI, there is no mechanism to ask for its intent. This leaves the user blind.
Finally, tokens can be transparently shared in a gallery or in the details of a generated file. Audio generators like Udio include the top tokens in the description of songs in their examples gallery. This can help users search for relevant audio files, and help them gather clues for how to prompt for similar sounds. Other generators include the tokens in the meta data of the file itself.
