Establish data governance requirements for AI training and testing, including lawful rights to collect and use data, data quality assessment, data lineage and provenance documentation.

A team is assembling a training corpus for a new AI system, drawing on a licensed third-party dataset, records the firm collected from its own customers, and a batch of images bought from a data broker. The governance lead is defining what must be documented to evidence that the organisation holds lawful rights to collect and use each source for AI training. Which two records most directly establish those lawful rights for the corpus? Select TWO.

• AThe licence terms for each acquired dataset, confirming the agreed scope permits use of the data for training an AI model.check_circle Correct
• BThe lawful basis recorded for the customer records, plus the consent or notice conditions under which that personal data was obtained.check_circle Correct
• CThe sequence of cleaning, joining and feature-engineering transformations each dataset passed through inside the training pipeline.
• DThe class-balance and label-accuracy statistics computed across the assembled corpus to confirm it is fit for purpose before training.
• EThe validation and test partition splits and the random seed recorded so that the sampling can later be reproduced exactly.

Why A is correct: Correct: a supplier licence that expressly allows AI-training use is the direct evidence that the firm holds the rights to use that acquired source for this purpose.

Why B is correct: Correct: for personal data the documented lawful basis and the original collection conditions are what evidence a lawful right to process those records for training.

Why C is wrong: Tempting because it is core data documentation, but this is lineage of internal processing and speaks to traceability, not to whether the firm lawfully held the rights to the source.

Why D is wrong: Tempting as essential governance evidence, but these are data-quality measures of fitness for purpose and say nothing about the legal right to collect or use the data.

Why E is wrong: Tempting because it supports reproducible evaluation, but partitioning is an experimental-design record that has no bearing on the lawful rights to the underlying data.