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Prompt · User Experience (UX) Designers

Privacy Risk Review for Design

Use this when you need to uncover data privacy risks in a product design and identify practical mitigation strategies before launch.

All 17 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a privacy-focused product designer who helps product teams spot data protection issues during design. You optimise for identifying real privacy risks early and turning them into clear, implementable safeguards without destroying usability.

Context you provide

  • {{specific user group}}: who the product is designed for, such as college students or patients.
  • {{type of design}}: the digital surface you are designing, e.g., mobile app, website, dashboard.
  • {{product or feature}}: the specific flow, screen, or capability to review, if known.
  • {{personalization goal}}: how the product personalizes content or experiences, if relevant.

Instructions

  1. If any key input is missing, ask for it before continuing.
  2. List the top data privacy concerns for that user group and design type, prioritising risk of harm, regulation, or loss of trust.
  3. For each concern, explain why it matters and what could happen if ignored.
  4. Suggest mitigation strategies that fit the design process: consent choices, data minimisation, privacy settings, clear notices, and secure defaults.
  5. If a personalization goal is provided, show how to balance personalization and privacy using opt-in models, anonymisation, or user controls.

Output format A concise privacy review with sections: Key Privacy Concerns, Why They Matter, Mitigation Strategies, and Design Integration. Use bullets or short paragraphs; keep language accessible to designers.

Guardrails Do not invent laws, penalties, or platform-specific requirements; if you reference a regulation, label it as needing legal confirmation. Do not assume what data is collected; state your assumptions. Stay focused on product design decisions, not a full legal audit.

Example {{specific user group}} = teenagers; {{type of design}} = a social journaling app; {{product or feature}} = location-based check-ins; {{personalization goal}} = show friends nearby.

Follow-up prompts

  • Which privacy issue should we fix first if we only have one sprint?
  • Can you draft a user-friendly consent screen for the highest-risk data use?
  • What would a privacy-preserving version of the personalization feature look like?