Evidence for App Store Privacy Disclosures in Local AI

Direct answer

A store privacy disclosure should be prepared from the exact release and observed data flows, not copied from a marketing page or older answer. Google Play defines collection around information transmitted off-device and includes SDK transmissions in an app’s Data safety form. Apple asks for the app’s and third-party partners’ practices through App Store Connect, using platform-specific definitions for data collection, linkage, and tracking. Those definitions are not interchangeable. PRIVACY-01 and ANDROID-PRIVACY-01 support evidence-led disclosure review; neither card determines a legal classification for a specific app. Pin the artifact, store listing, region, and submission date. Inventory user-provided content, generated results, device diagnostics, identifiers, backups, exports, SDK traffic, and optional network features. Trace each data class from source through processing, storage, destination, retention, deletion, and user control. Distinguish information that remains on-device from information that is transmitted. Record which platform treats an on-device app-to-app transfer as a share or data-use event. Do not rely on an app description to establish what an SDK actually sends. Prepare a separate worksheet for each store. Use Google Play’s form definitions and Apple’s App Privacy terms as written, and note which app version and build each answer covers. Some terms appear similar, but the forms have their own categories, exemptions, workflows, and definitions. An answer for one store cannot automatically be copied to another. If a library behaves differently by platform, preserve the difference in evidence rather than forcing one generic statement across all builds. Gather evidence from code and artifacts: permissions, SDK versions, privacy manifests where applicable, network clients, backup rules, analytics schemas, file pickers, exports, settings, and deletion paths. Test optional features, declined consent, signed-out states, offline operation, and reconnect behavior. Tools have blind spots, so note what could not be observed. A static dependency list, a privacy manifest, or an empty traffic capture cannot independently prove there was no collection or sharing. Map every disclosure answer to a concise evidence chain: statement, data class, purpose, path, control, retention, artifact version, and test. If an answer is uncertain, assign it for qualified owner review rather than guessing. Record whether a flow is initiated by the user, optional, collected by the first party, or transmitted by a third party. Avoid words such as anonymous, not shared, or never leaves the device unless the precise route and data class support them. Use change control. A new SDK, endpoint, feedback action, model download, support bundle, backup rule, or consent setting can make a prior disclosure stale. Tie store submission to a review of the exact release dependency graph and observed behavior. If a feature is removed, test whether its transmission route and retained data were actually removed before deleting a disclosure entry. Store declarations should describe a particular release, not the app’s aspirations. This article is an evidence workflow, not legal advice or a substitute for store review. A qualified owner must decide how platform definitions and applicable regional requirements apply. The technical team’s job is to connect each answer to a build, flow, source, and test, while keeping disagreements visible. Maintain reviewer and date, store the evidence link, and retain open questions. One platform’s terminology must not be used to make claims about another platform.

A release adds optional feedback and updates an SDK

A release candidate adds an optional feedback action and upgrades a third-party library. The team has store privacy answers from the previous release but needs to confirm whether those disclosures still match the new package, user control, data destinations, and retention behavior.

Decision

Review the exact build separately for each store, trace new and existing data paths, and send uncertain classifications to the assigned policy owner.

Expected outcome

The submission record ties each declaration to implementation evidence without asserting legal compliance or relying on old marketing copy.

Evidence to collect

The claim becomes reviewable only when the following evidence is attached to the same artifact and test run:

• Data and endpoint inventory
• Payload and control evidence
• Disclosure review record

A privacy claim needs a data inventory and traffic evidence. A local-model label by itself is not proof.

Implementation workflow

1. Pin release and store scope. Record app artifact, build variant, store platform, region, submission date, enabled modules, exact privacy form, release identifier, and assigned reviewer.
2. Inventory data sources and destinations. Map first-party fields, SDK flows, optional features, backup, export, deletion, purpose, retention, and user choices for the exact release being reviewed.
3. Apply each platform’s own definitions. Create separate worksheets for Google Play and Apple; preserve differences in collection, sharing, linkage, tracking, optionality, and form workflow by release.
4. Attach evidence and mark uncertainties. Link each answer to code, artifact, SDK documentation, privacy manifest, or runtime test, and assign ambiguous classifications to a named reviewer for decision.
5. Review changes before submission. Compare with the prior version, retest added and removed routes, and obtain policy-owner review before submitting disclosures for release with a dated record.

Keep each transition observable. A failure should identify the stage, artifact, runtime, and recovery action without logging private user content.

Acceptance criteria

• Every disclosure is tied to a named release, store platform, and date; answers are not copied between stores without definition checks.
• The evidence map covers first-party and third-party flows, optional features, retention, deletion, and user controls.
• Unknown classifications remain open for qualified review, and technical checks are not represented as a legal-compliance decision.

Decision table

Failure patterns to prevent

• Copying marketing language
• Omitting optional cloud paths

Also prevent silent fallback, unpinned artifacts, missing cancellation, and conclusions that combine unlike configurations. Store unsuccessful runs alongside successful ones.

Minimum reproducibility record

Release checklist

• ☐ The primary query is answered without an unsupported number.
• ☐ Every artifact and runtime is pinned.
• ☐ The representative task and failure policy are explicit.
• ☐ Lifecycle, cancellation, cleanup, and fallback are tested.
• ☐ User-content and network boundaries are documented.
• ☐ Result wording applies only to the recorded configuration.
• ☐ The page links to raw method or evidence when results are added.

Sources and related evidence

• Android privacy and security
• Google Play Data safety section
• Apple App Privacy details
• Google Play SDK requirements

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Frequently asked questions