Artificial Intelligence and Etruscan Archaeology
Maurizio Forte, Felipe Infante de Castro · 2025
Abstract Generative artificial intelligence (AI), a subset of AI focused on creating original content, has transitioned from science fiction to daily reality, impacting diverse fields from education to software development. This chapter explores the emergence and implications of generative AI, beginning with OpenAI’s DALL-E, a pioneering model that generates images from textual descriptions using a large dataset of image–text pairs. The launch of Stable Diffusion by Stability AI marked a significant milestone, making advanced generative AI accessible to a broader audience by running on consumer-grade computers and being open-source. Generative AI’s applications in archaeology are nascent yet promising, with early experiments in reconstructing Etruscan tumuli and creating environmental and architectural visualizations. These applications illustrate the potential of AI to enhance archaeological interpretation by generating realistic and contextually accurate images from curated datasets and paleoenvironmental data. Despite its transformative potential, generative AI faces challenges such as the quality and representation of input data and the need for domain-specific training to produce accurate outputs. The chapter concludes by reflecting on the future of AI in archaeology and beyond, emphasizing the need for interdisciplinary collaboration and continuous innovation. Generative AI not only offers new tools for visualizing the past but also invites us to reconsider our understanding of history and reality in a hyperrealistic, multiverse framework. As AI technology evolves, it promises to revolutionize how we interpret, visualize, and engage with complex datasets, opening new frontiers in research and creativity.