AI and Archaeology: Why a Historically Accurate Film Remains Impossible

The trigger: an AI film about the Odyssey

The starting point of the analysis is a recent controversy. Entrepreneur Elon Musk criticised the adaptation of Homer's Odyssey by director Christopher Nolan, faulting its diverse casting and lack of historical accuracy. He then claimed he wanted to show that artificial intelligence could produce a faithful Homeric work at low cost.

His tool, Grok Imagine, published the first seven minutes of such a film on October 23. According to the article, reprinted from The Conversation, the issue is less the artistic quality of the result than the very promise of historical accuracy, which, in the authors' view, fails before the first shot.

A fragmentary archaeological record

Archaeology works from fragmentary traces of the past: only a tiny part of the remains survives in the ground, and only a fraction of that is excavated. The authors take the example of Troy: the deposits contain spindle whorls and loom weights, but no fabric. Textiles have disappeared, although every inhabitant would have worn them.

Anything that cannot be recovered directly must therefore be interpreted through hypotheses of varying strength, with uncertainties and competing interpretations. A generative AI, designed to produce a complete image, would fill these gaps with elements borrowed from other media, such as cinema, video games or painting.

Plausible is not accurate

The central risk lies in plausibility. Additions produced by an AI can seem convincing, even authentic to some viewers. Yet, as the authors stress, "convincing" is not synonymous with "accurate", and archaeology works in the gap between the two.

Homer's poem is itself a fragile witness: composed centuries after the collapse of the palaces it describes, it blends Mycenaean memories with the worldview of the Iron Age. Odysseus, Helen or Circe are not figures that archaeology can confirm. A model trained on these traces would inherit our gaps as much as our knowledge.

AI is useful if it shows its uncertainties

The researchers do not reject AI outright. A system cross-referencing excavation reports and object databases could reveal patterns no specialist would perceive alone, such as the spread of ceramic styles. But this would be a pattern present in the data, not an image of the past.

In their view, an AI truly suited to archaeology should display its uncertainty as clearly as its confidence: presenting several reconstructions when the evidence allows, limiting itself to fragments when only fragments survive, and flagging what is documented, inferred or merely plausible. This approach aligns with the principles of the London Charter (2009) and the Seville Principles (2011) on the virtual restitution of heritage.

Choosing which world to reconstruct

Reconstructing the past also requires choices. Troy covers phases separated by several centuries, and the Mycenaean palaces differed from Hittite cities: there is no single "Bronze Age". The traces may support the existence of a conflict at Troy, but cannot establish Homer's war as a single event.

An AI model nonetheless selects one version of Troy without ever signalling that choice. The film will probably be forgotten within days, but the method matters. For the authors, the most faithful reconstruction would not be the most assertive one, but the one that shows where the gaps lie.