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

Question

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

• A
  18% (8)
• B
  71% (32)
• C
  7% (3)
• D
  4% (2)

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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