De-identification is a technique that removes or modifies direct and indirect identifiers in a data set to prevent or limit the identification of the data subjects. De-identification reduces the risk of re-identification and thus limits the organization's potential exposure in the event of consumer data loss. De-identification also maintains the traceability of the data by preserving some characteristics or patterns of the original data that can be used for analysis or research purposes. The other options are not effective ways to limit exposure and maintain traceability1, p. 75-76 Reference: 1: CDPSE Review Manual (Digital Version)

Synthetic data is generated artificially to mimic patterns without containing real personal data, making it the strongest method to embed privacy by design in AI training. De-identification (A) reduces but does not eliminate reidentification risk; consent (B) addresses lawfulness, not privacy-preserving training; privacy notices (D) provide transparency but not technical risk reduction.
"Synthetic data allows AI model training without exposing real personal information."

Requirements definition is a phase of the software development life cycle (SDLC) that involves gathering, analyzing and documenting the functional and non-functional requirements of the software system or application, such as features, performance, security and usability. It is most important to consider privacy by design principles during this phase, as it would help to ensure that privacy is embedded and integrated into the software system or application from the outset, rather than as an afterthought or an add-on. Considering privacy by design principles during requirements definition would also help to avoid costly rework or delays later in the SDLC, as well as to enhance customer trust and satisfaction, and comply with privacy laws and regulations. The other options are not as important as requirements definition in considering privacy by design principles. Application design is a phase of the SDLC that involves creating and specifying the architecture, components, interfaces and data models of the software system or application, based on the requirements defined in the previous phase. Implementation is a phase of the SDLC that involves coding, testing and debugging the software system or application, based on the design specifications created in the previous phase. Testing is a phase of the SDLC that involves verifying and validating that the software system or application meets the requirements and expectations of the users and stakeholders, as well as identifying and fixing any defects or errors1, p. 88-89 Reference: 1: CDPSE Review Manual (Digital Version)

According to the General Data Protection Regulation (GDPR), data subjects have the right to withdraw their consent for processing their personal data at any time. However, this right does not apply when the processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes, in accordance with Article 89(1) of the GDPR1.