Confirm the lawful rights to reuse the data for this new: Which action best satisfies data-governance
Data governance requires confirming lawful rights to reuse the data for the intended purpose and fixing quality gaps before any training.
The question
A team wants to train a diagnostic model using a partner hospital's patient records. The data was collected for treatment, has gaps for certain demographics, and the partner cannot confirm consent covers research reuse. Which action best satisfies data-governance requirements before training?
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- Proceed with training now and log the consent uncertainty as a residual risk to be revisited after the model has shipped.Plausible as risk logging, but shipping on unresolved lawful-basis and quality issues violates the governance gate.
- Rely on the sheer volume of the records to offset the demographic gaps, since a larger dataset generally improves model accuracy.Plausible because size often helps, but volume does not cure representational gaps or the missing lawful basis.
- Anonymize the records so that the lawful-basis and fit-for-purpose questions supposedly no longer need to be assessed before training begins.Plausible since anonymization reduces some risk, but it does not resolve fitness gaps or, if imperfect, the lawful-basis question.
- Confirm the lawful rights to reuse the data for this new purpose and remediate the demographic gaps before the data is used to train. ✓Correct: data governance requires establishing lawful rights for the intended purpose and assessing quality and fit before training proceeds.
The trap
Assuming dataset size or anonymization can substitute for establishing lawful rights and representativeness before training. How to remember it
Data governance requires confirming lawful rights to reuse the data for the intended purpose and fixing quality gaps before any training.
How many of these would you get right?
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