Artificial intelligence is reshaping the contemporary world. Trickling deeper into archaeology and history, these technological changes will influence how the past is written about and visualized. Through the evaluation of text and images generated using AI, this article considers the systemic biases present in reconstructed archaeological scenes. We draw on advances in computer science, running large-scale, computational analyses to evaluate patterns in content. We present a case study examining Neanderthal behavior, juxtaposing published archaeological knowledge with images and text made using AI. Our study reveals a low correspondence between scientific literature and artificially intelligent material, which reflects dated knowledge and cultural anachronisms. Used to identify patterns in (mis)representations of the past, the methodology can be applied to understand the distance between scholarly knowledge and any domain of content generated using AI, across any archaeological time depth and beyond the discipline.
