CT-AI Question #146: Real Exam Question with Answer & Explanation

The correct answer is B. During the review of the preprocessing, the auditor can uncover whether the data has been. Bias detection at thedata levelis performed by reviewing data acquisition and preprocessing steps, as explained in Section2.3 - Data Quality and Biasof the ISTQB CT-AI syllabus. Sample bias arises when data is distorted or when preprocessing introduces unintended shifts--for exam

Question

How can a tester check the system for bias as part of a review of data sources, acquisition, and preprocessing?

Options

ADuring the review, it can uncover algorithmic bias by analysing the procedures used to obtain the
BDuring the review of the preprocessing, the auditor can uncover whether the data has been
CIt may use the LIME method as part of its data collection review to detect inappropriate bias.
DAs part of the review of preprocessing, it can reveal whether the data has been influenced in a

Explanation

Bias detection at thedata levelis performed by reviewing data acquisition and preprocessing steps, as explained in Section2.3 - Data Quality and Biasof the ISTQB CT-AI syllabus. Sample bias arises when data is distorted or when preprocessing introduces unintended shifts--for example, by filtering, normalization, or labeling steps that disproportionately affect subsets of the data. Option B correctly reflects this: reviewers can identify whether preprocessing steps have altered the dataset in a way that introduces sample distortions. This aligns perfectly with syllabus guidance on reviewing data pipelines for bias sources.

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