Earlier this year, scientists discovered a peculiar term appearing in published papers: "vegetative electron microscopy".
This phrase, which sounds technical but is actually nonsense, has become a "digital fossil" – an error preserved and reinforced in artificial intelligence (AI) systems that is nearly impossible to remove from our knowledge repositories.
Like biological fossils trapped in rock, these digital artefacts may become permanent fixtures in our information ecosystem.
The case of vegetative electron microscopy offers a troubling glimpse into how AI systems can perpetuate and amplify errors throughout our collective knowledge.
To test whether a model "knew" about vegetative electron microscopy, we input snippets of the original papers to find out if the model would complete them with the nonsense term or more sensible alternatives.
The results were revealing. OpenAI's GPT-3 consistently completed phrases with "vegetative electron microscopy". Earlier models such as GPT-2 and BERT did not. This pattern helped us isolate when and where the contamination occurred.
We also found the error persists in later models including GPT-4o and Anthropic's Claude 3.5. This suggests the nonsense term may now be permanently embedded in AI knowledge bases.