Synthetic Books
This work addresses the challenge of relating to AI-aided written language in art contexts, but it is incremental as it builds on existing AI technologies without major breakthroughs.
The paper tackles the problem of contextualizing AI-generated publications by introducing the concept of 'synthetic books' created using autoregressive language models like GPT-2 and GPT-3, and discusses their value and artistic quality through case studies.
The article explores new ways of written language aided by AI technologies, like GPT-2 and GPT-3. The question that is stated in the paper is not about whether these novel technologies will eventually replace authored books, but how to relate to and contextualize such publications and what kind of new tools, processes, and ideas are behind them. For that purpose, a new concept of synthetic books is introduced in the article. It stands for the publications created by deploying AI technology, more precisely autoregressive language models that are able to generate human-like text. Supported by the case studies, the value and reasoning of the synthetic books are discussed. The paper emphasizes that artistic quality is an issue when it comes to AI-generated content. The article introduces projects that demonstrate an interactive input by an artist and/or audience combined with the deep-learning-based language models. In the end, the paper focuses on understanding the neural aesthetics of written language in the art context.