What is privacy by design in the TELUS CX and AI framework?

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Multiple Choice

What is privacy by design in the TELUS CX and AI framework?

Explanation:
Privacy by design means you bake privacy into every layer of the product and data architecture from the very beginning, not as an afterthought. In the TELUS CX and AI framework, this means you define data types, purposes, and retention early, implement data minimization and purpose limitation by default, and build in controls such as strong access governance, encryption, and privacy-preserving processing from the outset. It also involves conducting privacy assessments during design, choosing default settings that protect user data, and ensuring accountability and transparency in how data is collected, used, and stored. This approach keeps privacy embedded in how features are imagined, designed, and deployed, so privacy risks are mitigated before they can occur. Adding privacy controls after launch or relying only on regulatory compliance misses the preventive value of design-time protections and can leave gaps in data handling. Outsourcing privacy concerns to third parties often reduces your visibility and control over data practices, weakening your ability to uphold privacy promises.

Privacy by design means you bake privacy into every layer of the product and data architecture from the very beginning, not as an afterthought. In the TELUS CX and AI framework, this means you define data types, purposes, and retention early, implement data minimization and purpose limitation by default, and build in controls such as strong access governance, encryption, and privacy-preserving processing from the outset. It also involves conducting privacy assessments during design, choosing default settings that protect user data, and ensuring accountability and transparency in how data is collected, used, and stored.

This approach keeps privacy embedded in how features are imagined, designed, and deployed, so privacy risks are mitigated before they can occur. Adding privacy controls after launch or relying only on regulatory compliance misses the preventive value of design-time protections and can leave gaps in data handling. Outsourcing privacy concerns to third parties often reduces your visibility and control over data practices, weakening your ability to uphold privacy promises.

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