Generative AI for Art

AI-generated artwork wins the top prize in a U.S. art competition! Jason Allen's "Théâtre D'opéra Spatial" or 'Space Opera Theater' won the top prize at the Colorado State Fair's fine art competition in the "digital arts/digitally-manipulated photography" category. While the category allowed digital art, this issue has ignited fierce debate on A.I. generated content. We have all been accustomed to chatbots talking to us in natural language or text editors used in blogs. Creativity is the hallmark of human evolution! The ability to create art is one of the defining characteristics of evolution. The past generation of automation technologies went after repetitive manual tasks and wasn't seen as much of a threat. Generative A.I. technologies promise higher-level cognitive task capabilities such as writing, coding, video, and art. So naturally, this will usher in industrial revolution scale debates on the balance of using A.I. vs human economic value add. The other dimension that is also playing out is copyright. There are at least three parties involved in making A.I. art. The millions of images and their authors, the model's technology provider, and the user who generated the art. In August, a U.S. appeals court affirmed that an artificial intelligence system could not be an inventor under United States patent law, noting that the inventor must be a natural person. Authors of licenses such as CreativeML Open RAIL-M claim no rights on user-generated outputs. Though the product created by the engine is not patentable, it is unique. How unique can derivative work be, and can it be considered innovative? That is the maturity curve that generative A.I. has to scale. After all, we humans learn from instruction, infer from different sources and then reflect those in our innovation! While this journey evolves, here are interesting open source libraries that will help you generate art using A.I.