Browsing by Author "Tzerpou, Endoxia"

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    GenAI-Based Reconstruction of Prehistoric Remains
    (The Eurographics Association, 2025) Barceló, Juan A.; Tzerpou, Endoxia; Campana, Stefano; Ferdani, Daniele; Graf, Holger; Guidi, Gabriele; Hegarty, Zackary; Pescarin, Sofia; Remondino, Fabio
    Generative artificial intelligence (GenAI) has emerged as a powerful tool in various fields, including archaeology. However, its application in reconstructing prehistoric archaeology presents unique challenges and limitations that warrant careful consid-eration. Realizing the potential of Generative Artificial Intelligence to archaeological reconstruction requires a nuanced ap-proach that acknowledges and addresses the inherent limitations of AI in this context. The "black box" nature of some AI algorithms can make it difficult to understand how reconstructions are generated. This lack of transparency poses challenges for scientific reproducibility and peer review in archaeological research. By adopting a theoretical framework that combines technological innovation with rigorous archaeological methodology and ethical considerations, we can work towards more accurate, inclusive, and responsible reconstructions of prehistoric societies. This framework not only addresses the current limitations of AI in prehistoric archaeology but also sets the stage for future research directions. As AI technology continues to evolve, ongoing critical evaluation and adaptation of these approaches will be essential to ensure that generative AI becomes a valuable tool in expanding our knowledge of prehistoric human societies while respecting the complexity and cultural sensi-tivity of archaeological interpretation.