Name a common data privacy regulation CPMAI teams must consider and its impact on AI projects.

Name a common data privacy regulation CPMAI teams must consider and its impact on AI projects.

• A. HIPAA is the regulation.
• B. GDPR or CCPA, affecting data handling, consent, and rights management.
• C. FERPA only.
• D. PCI DSS controls.

Answer: (B)

Handling personal data responsibly is a must in AI work. A common regulation to consider is GDPR or CCPA, which set rules about how data can be collected, stored, used, and shared, plus what kind of consent and transparency is required and what rights individuals have over their data. In AI projects, this drives privacy-by-design: you should minimize data you collect, anonymize or pseudonymize where possible, and document why and how data is used. You must have a lawful basis for processing, obtain appropriate consent when needed, provide clear notices, and honor data subject rights such as access, deletion, and data portability. It also affects how you handle cross-border data transfers and how you assess and mitigate risks with data protection impact assessments. All of this shapes data sourcing, model training, evaluation, deployment, and ongoing governance to ensure compliance and trust. The other options refer to more specific domains—health information, education records, or payment data—relevant in particular contexts, but GDPR or CCPA have the broad scope that most AI projects encounter.

Handling personal data responsibly is a must in AI work. A common regulation to consider is GDPR or CCPA, which set rules about how data can be collected, stored, used, and shared, plus what kind of consent and transparency is required and what rights individuals have over their data. In AI projects, this drives privacy-by-design: you should minimize data you collect, anonymize or pseudonymize where possible, and document why and how data is used. You must have a lawful basis for processing, obtain appropriate consent when needed, provide clear notices, and honor data subject rights such as access, deletion, and data portability. It also affects how you handle cross-border data transfers and how you assess and mitigate risks with data protection impact assessments. All of this shapes data sourcing, model training, evaluation, deployment, and ongoing governance to ensure compliance and trust. The other options refer to more specific domains—health information, education records, or payment data—relevant in particular contexts, but GDPR or CCPA have the broad scope that most AI projects encounter.