This is the forensic case file for Fauzia Chaudhry v OpenAI Inc.
Network captures, browser cache extractions, and OpenAI's own data export confirm that special-category health data
was processed by Scale AI annotators for RLHF training — without explicit consent, without disclosure, and
with the opt-out flag set to false after stated withdrawal.
label = "MICROSOFT/AZURE", "AWS", and "reviewed" ×7 extracted from Chrome IndexedDB binary 000034.ldb. Seven human annotation reviews confirmed.oai-client-auth-info records "isOptedOut": false after stated withdrawal of consent. All messages carry weight: 1.0 RLHF eligibility.weight: 1.0. Only hidden system messages carry weight: 0.0. 132 RLHF-eligible messages confirmed including memoir content./backend-api/conversation/implicit_message_feedback sent automatically during the captured session — no thumbs up, no rating click, no user action whatsoever.is_kaur1br5: false appears in every turn_exchange_started event in the HAR. An undisclosed Statsig experiment assigned to control group — never disclosed, no opt-out provided."remove_memory": true. The classifier strips memory context before running — disabling a paid Plus feature without disclosure.gpt-4o. The official conversations.json export confirms model_slug: gpt-5-2. An undisclosed internal GPT-5 variant processed the psychotherapy and memoir conversations.68af7dfe) triggered the RLHF rating event. Mental health content confirmed in active annotation pipeline.snc-pg-sw-3cls-ev3: prefix "snc" consistent with Anthropic model naming. If Anthropic co-determined purposes of this classifier, they are a joint controller under Art. 26 GDPR. No joint controllership agreement published.