Dataset provenance matters for security and governance
Where training data came from decides both what the model learned and what you are permitted to do with it.
Scraped material carries licensing and personal data questions. Data of unknown origin cannot be assessed for poisoning or bias. Neither question can be answered retrospectively with any confidence, which is why provenance has to be recorded at the point of collection.
More on AI supply chain
- A model file is executable trust in another formIt looks like data until you open it
- Model version changes can be security changesOne plate swapped inside
- Third-party AI APIs extend the data boundaryThe fence moves with the call
- Evaluation data can leak into trainingIt has already seen the exam
- Fine-tuning credentials are production credentialsThe bench feeds the floor
- Open models shift responsibility toward the operatorThe engine comes with the engine room