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Generative Systems

/ˈdʒɛnərətɪv ˈsɪstəmz/ From Complexity Theory (1980s) and Computer Science. Code that grows.
Definition Digital artifacts that are not static files, but dynamic processes. A Generative System uses algorithms (often procedural generation or AI) to create content on the fly. For the Archaeobytologist, these are deeply problematic because they have no "final state." You cannot archive a river; you can only take a picture of it.

The Unstable Artifact

Traditional preservation relies on the "fixity" of the object. A book does not change its text when you close it. A Generative System does. Examples include:

Preserving the Probability

How do we archive a system that changes every time you look at it? We replace "Object Preservation" with "Logic Preservation."

Field Notes

The Minecraft "Seed": Minecraft players share "world seeds"—alphanumeric strings that tell the game's terrain generator exactly how to build a specific world. This is a form of compressed geography. Passing a seed to a friend is like handing them the DNA of a continent.
Generative Archaeology: Some researchers use generative AI to "fill in the blanks" of physical ruins, training models on existing pottery shards to predict the shape of missing ones. This creates a "Probabilistic Past"—a history that is statistically likely but factually unproven.

Ephemera

A major challenge with Generative AI (LLMs like GPT) is "Model Collapse." As models are trained on the internet, they begin to ingest AI-generated content (their own vomit). This causes the system to degenerate into nonsense. Archaeobytologists track these "inbred datasets" as markers of the "Synthetic Era."

Stratigraphy (Related Concepts)
Generative Tethered Cultural Seed Frictional Data Algorithm Bias