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🎙 Ambient AI Listening Consent & Privacy Simulator

This simulation allows users to explore the process of obtaining patient consent and maintaining privacy when using an 'listening' AI during a medical consultation.

AI Medical Scribe & Documentation2DModerate60 FPS
ambient-ai-consent-privacy-simulator ↗ Open standalone

Disclosing the Ambient AI Scribe

Placeholder lead: patient is told an AI scribe will listen and how it works.

  • Always: Disclosure required (before any recording)
  • Purpose: Explains (what the AI scribe does)
  • Pre-visit: Timing (before conversation starts)
  • Verbal + sign: Format (spoken and posted notice)

What disclosure covers

Placeholder: staff state that audio will be captured and processed by AI.

Placeholder: explains transcription, note drafting, and physician review.

Placeholder: clarifies that participation is optional at this stage.

Why disclosure matters

Placeholder: transparency builds trust before any recording occurs.

Placeholder: sets up the explicit consent decision that follows.

Explicit Consent Before Recording Begins

Placeholder lead: patient chooses to allow or decline ambient recording.

  • Verbal/written: Consent type (explicit, documented)
  • Always offered: Decline option (no penalty for declining)
  • Manual notes: Alternate path (used if declined)
  • Logged: Documentation (consent recorded in chart)

The consent decision

Placeholder: patient affirmatively opts in or opts out of recording.

Placeholder: decision is timestamped and stored with the visit record.

If consent is declined

Placeholder: physician reverts to manual documentation, no audio captured.

Placeholder: care quality is unaffected by declining the AI scribe.

Audio Capture, Transcription, Note Generation

Placeholder lead: consented audio flows through transcription into a draft note.

  • 3: Pipeline steps (capture, transcribe, draft)
  • Required: Human review (physician signs off)
  • Automated: Processing mode (AI-assisted drafting)
  • Skipped: Declined path (manual notes instead)

Processing the conversation

Placeholder: audio is transcribed and summarized into a structured note.

Placeholder: the physician reviews and edits before finalizing.

Keeping the manual alternative live

Placeholder: manual documentation remains fully available at every visit.

Retention, De-Identification, and PHI Protections

Placeholder lead: audio is typically deleted after processing; the note is retained.

  • Deleted: Audio default (after transcription completes)
  • Kept: Note retention (part of medical record)
  • Applied: De-identification (before any secondary use)
  • End-to-end: Encryption (in transit and at rest)

What is deleted vs. retained

Placeholder: raw audio is processed then deleted under minimal retention.

Placeholder: extended retention stores audio longer, raising exposure risk.

Safeguards applied throughout

Placeholder: encryption, de-identification, and access control gate each step.

Consent Plus Transparent Handling Resolves the Core Concern

Placeholder lead: informed consent and clear retention policy protect patient privacy.

  • Documented: Consent obtained (before recording)
  • Disclosed: Retention policy (minimal by default)
  • 3 active: Safeguards (encryption, de-ID, access control)
  • Preserved: Patient trust (transparent workflow)

Why this resolves the privacy concern

Placeholder: explicit consent removes the core objection to ambient listening.

Placeholder: transparent retention policy limits unnecessary data exposure.

What good practice looks like

Placeholder: disclose, obtain consent, process minimally, protect PHI always.

Placeholder highlight: consent plus minimal retention is the privacy-safe default.
⚙ Under the hood

This simulation allows users to explore the process of obtaining patient consent and maintaining privacy when using an 'listening' AI during a medical consultation.

CanvasBiomedicine

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install

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