An organization is evaluating a number of Machine Learning (ML) solutions to help automate a customer-facing part of its business From a privacy perspective, the organization should first?
A.
Define their goals for fairness
B.
Document the distribution of bias scores
C.
Document the False Positive Rates (FPR).
D.
Define how data subjects may object to the processing
When evaluating Machine Learning (ML) solutions, the first step from a privacy perspective is to define how data subjects may object to the processing. This aligns with the principles of transparency and individual rights under data protection laws such as GDPR, which stipulates that data subjects should have the ability to object to the processing of their personal data. This ensures that individuals maintain control over their personal information and that the organization respects their privacy rights. (Reference: IAPP CIPT Study Guide, Chapter on Privacy in Technology and GDPR)
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