AI wins or Artist wins or they join hands?
Note: These are the author’s own views, and this article is present on author’s other social media platforms as well.
The following excerpts are taken as it is from my recent publication [1]. These are my views, to read more refer to the publication given at the end of the article.
“With the advancements in AI comes the problem of ownership. AI initially was used by artists to help artists, songwriters, scriptwriters, and movie makers but now it has taken over all these domains. Who taught AI all this? The answer is humans. AI-based software was trained on hundreds and thousands and more of human-created art, photographs, chats and texts. But when AI software creates something new, say a new image file, it may be created using thousands of man-made items. This means the credit for new images made by AI to some extent lies in the hands of humans who made the base image, and who made AI learn painting or singing, as the case may be.”
“The solution to this can be understood as follows. There are traditional artists and AI and digital arts-based artists. Let us understand all this with the help of restricting art to painters; similar analogy would apply to other artists, be they scriptwriters or musicians, to mention a few.”
Solutions
“The AI and Robotics based arts are trained on thousands and more of human-made artworks, photographs, scripts, etc. These training data is used to make newer artwork. But it is not always clear how to find the original makers of artwork from AI-generated art. Sometimes the contribution is just to make a colored ball in the new AI art and many times it is the whole face that is used and maybe processed with a makeup filter. The solution lies in how much of art was taken from original training data, and how much was learned as a teacher-learner relationship.”
The solution can be legally formulated as follows:
“1. The AI artwork has more than 80% of similarity with the original art in training data. Then the original artist and the new AI artist can get into some negotiations on sharing the profit or barring the sale of the new artwork, as the base artist wants. The original artist can buy the work the digital artist made, based on hours spent by the digital artist on editing.
2. In case of less than 80% of similarity, the original artist can claim a share of the profit on selling the artwork and cannot stop the digital artist from selling and purchasing the artwork.
3. In case the original artist wants to work together with a digital-AI artist, they can share the profits and the collaboration can lead to new heights in creating arts never seen before. Such solutions may make the marketplace for arts ownership a harmonious place to work in.”
Your suggestions are invited, to reach to more such solutions in other areas of AI which need in-depth analysis of cultural professions and for preservation of traditional kinds of artworks.
References:
[1] Yadav N. Ethics of Artificial Intelligence and Robotics: Key Issues and Modern Ways to Solve Them. Journal of Digital Technologies and Law. 2023;1(4):955–972. https://doi.org/10.21202/jdtl.2023.41. EDN: mdiefv