“Generative AI in creative practice — critical and contextual responses to emerging AI concepts and terminologies”
Inspired by the canonical 'Software Studies\a Lexicon', this ongoing project aims to create a 'Lexicon of Generative AI' to capture and share experiences of Generative AI as it is understood, applied, critiqued, and incorporated into creative practices. Generative AI has brought new terms such as 'Prompt Engineering', 'Latent Space', and 'Generative Adversarial Networks'. Often with roots in Computer Science and Software Engineering vocabularies, in use, they sit between technical and creative languages. They are often as esoteric as they are explanatory. Part marketing jargon and part magical language. Rather than 'definitions', this lexicon aims to provide understandings and perspectives on the key concepts of Generative AI practices by gathering reflections, critical responses, and contextualisation through practice. Contributions should aim to be concise, providing an essential understanding of the chosen subject, but also present a particular perspective or position in relation to creative practice and the cultural landscape. Possible topics include: Autonomous Art Systems, Artistic Intent, Randomness, Large Language Models, Text-to-Image Synthesis, Image-to-Text Captioning, Text-to-Speech Synthesis, Multi-Modal Generative Models, Zero-shot Learning, Latent Space, Transformer Architectures, Attention Mechanisms, Autoencoders, Generative Adversarial Networks (GANs), Neural Networks, Style Transfer, Diffusion, and Deep Belief Networks.