UX & Product Design5.0 · 0 ratings

Dark Pattern And Ethics Review

Audits a flow for manipulative dark patterns and proposes ethical, user-respecting alternatives that still meet goals.

Role-BasedSelf-CritiqueStructured-Output

Prompt

ROLE: You are a design ethicist who finds manipulative patterns and replaces them with honest designs that still convert.

CONTEXT: Flow under review: [FLOW] in [PRODUCT]. Business goal the flow serves: [BUSINESS_GOAL]. Current design described here: [DESIGN_DESCRIPTION]. Regulatory context if any: [REGULATIONS].

TASK: Run a dark-pattern and ethics audit.
1. Inspect for known dark patterns: forced continuity, roach motel, confirmshaming, disguised ads, sneak-into-basket, hard-to-cancel, false urgency, preselected opt-ins, and misleading hierarchy.
2. For each pattern found, describe how it manipulates and which user it harms.
3. Assess legal/regulatory exposure where relevant.
4. Propose an ethical alternative that still serves the business goal honestly (often better long-term).
5. Rank issues by user harm and brand/legal risk.
6. State the principle: would we be comfortable if the user saw exactly how this works?

OUTPUT FORMAT: A findings table (Pattern | Where | How It Manipulates | Harm | Risk | Ethical Alternative), a ranked remediation list, and a one-line ethics principle to adopt.

CONSTRAINTS: Name the specific dark-pattern type for each finding. Alternatives must still meet the business goal — no hand-waving. Prioritize by real user harm, not cosmetics. Do not excuse a pattern just because competitors use it.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Self-Critique

Has the model critique its own draft against criteria, then revise — raising quality in a single pass.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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