Pattern 35
Private before shared
Let users inspect audience, content and AI suggestions before committing.
Concrete takeaway
Keep personal work private until a deliberate share action.
Choose an approach
These are editorial decision conditions to validate. Some alternatives are successive states or can be combined; they are not always exclusive choices.
| Alternative | Use when | Tradeoff or requirement |
|---|---|---|
| A · Share preview | The person chooses to share | Preview must expose recipient and visibility |
| B · Review suggestions | AI proposes wording for shared content | A suggestion is not a saved statement by the user |
| C · No hidden profiling | Private activity could be profiled | A hidden inference is not consent to collect or share |
The problem
A private reflection can leak through a share flow or be transformed into a psychological or religious profile.
The pattern
Keep personal work private until a deliberate share action. Preview the exact content and recipients. Review AI-proposed tags and changes before saving. Do not infer health or spiritual standing from highlights.
Compare the alternatives
Let users inspect audience, content and AI suggestions before committing.
A · Share preview
The content and audience are visible together.
B · Review suggestions
An AI suggestion is not a saved user statement.
C · No hidden profiling
A personal mark does not authorise a derived profile.
Original wireframe proposals · No live controls · Grey rows represent schematic text, not loading states · Labelled placeholders are not Scripture quotations
Download this wireframe as SVGFailure modes
Sharing notes by default; an ambiguous “send” action; storing AI interpretations as user beliefs; hidden audience expansion.
What to validate
Test sharing a verse alone versus a verse with private notes. Can users recognise recipients and reject an AI suggestion without side effects?
Research-informed design proposal. These visual alternatives have not been tested with users in this atlas. Source findings, documented behaviour and this proposed adaptation are different kinds of evidence.
Sources and adaptation
This card is an original design synthesis. The following sources inform its content distinctions, interaction approach or review requirements; they do not validate the whole pattern.
- Design Patterns CatalogueCatalogue and relevant automation entry reviewed · Broader than AI; data-control interfaces must be backed by corresponding storage and permission behaviour.
- The Shape of AICatalogue and named entries reviewed · The site states CC BY NC SA. This atlas uses original text and original wireframes; it does not reproduce the source illustrations.
- Process personal data lawfullyOfficial guidance reviewed · Specific lawful basis, retention and DPIA decisions require the actual data flows.
- AI UX PatternsPublic sample and catalogue framing reviewed · The pattern-composition example is a design reference, not a validation of the proposed faith-specific variants.
Common scenarios and flows
- Receive prayer support without hidden profiling — Choose useful words or silence while retaining ownership of intentions.
Design principles in this decision
Editorial application of Missional by Design. These values frame review questions; they do not validate a pattern’s effectiveness.
- Reverence — What does this interaction ask of the person, and can they understand, decline, correct or leave it without penalty?
Compare alternatives using the task and evidence above. Record competing needs instead of treating a principle as an automatic verdict.
Regional applicability
Design review questions · 5 October 2026. These prompts identify possible triggers; they do not classify this pattern or every faith app as a regulated service.
Where do prayer, religious, health and audio data actually go? Review memory, model-provider access, logs, analytics, training and exports as separate data flows; a private-looking screen is not a data policy.
Start with EU and Germany, then review the relevant market:
- US · Utah: mental-health chatbots — Enacted AI-specific law
- US · Federal health software and data — Existing law; regulator implementation guidance
- United Kingdom — Existing law + regulator guidance; policy statement
- Australia — Existing law + regulator guidance; national policy
- Canada — Existing privacy law + joint regulator principles
Use the jurisdiction decision guide to record the trigger, source version and resulting product requirement.