Cite this as: Kansa, E.C. 2026 Archaeology in the AI Era: Demystifying powerful and problematic systems shaping the future of the past, Internet Archaeology 71. https://doi.org/10.11141/ia.71.15
This essay explores how Large Language Models (LLMs) and the generative "Artificial Intelligence" (AI) services they power impact archaeology's information ecosystem. Most of the discussion focuses on the dangers of escalating costs, commercial dependency, indeterminacy and reliability, and the potential for bias amplification. The essay highlights the need for structural reforms in archaeology's professional incentive systems, especially those systems that measure and reward publishing practices.
Corresponding author: Eric C. Kansa
[email protected]
Open Context
Figure 1: Blocked Requests to Wikipedia per Day (2023-2026)[11]. Original image by Chris Danis under a Creative Commons Attribution Share-alike license (https://web.archive.org/web/20260604234640/https://diff.wikimedia.org/2026/03/26/quo-vadis-crawlers-progress-and-whats-next-on-safeguarding-our-infrastructure/image-1919/)
Figure 2: Short-term Compute Savings from Bot Protections for Open Context (April to May 2025). The y-axis represents the percentage of CPU use for Open Context’s primary web server. More CPU use indicates higher processing loads, either in response to traffic, API use, or running complex queries. The arrow marks when Anubis, an open source bot firewall, started blocking some scraper traffic to Open Context.
Figure 3a: Microsoft Bing AI Search Summary on the "Age of the Sphinx" (Great Sphinx, Giza). The LLM-generated summary text in blue seems to suggest that two very different time frames for the construction of the Great Sphinx at Giza are both equivalently plausible.
Figure 3b: Google AI Search Summary on the "Age of the Sphinx" (Great Sphinx, Giza). The LLM-generated summary text suggests that two very different time frames for the construction of the Great Sphinx at Giza are "the subject of ongoing debate".
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