Biometric categorisation of sensitive traits

Remove any model, prompt, or label set that infers race, political opinion, union membership, religion or beliefs, sex life, or sexual orientation from biometric data.

In biometric pipelines (face, voice, gait, iris), the code computes only the attributes the feature needs and never a sensitive-trait category: no classifier heads or labels for race or ethnicity, political opinion, trade-union membership, religious or philosophical belief, sex life, or sexual orientation, and no attribute API used for those traits (for example DeepFace.analyze with the 'race' action). Prompts that send a person's photo or voice to a multimodal model instruct it not to guess these traits, and an output check strips any such inference. The data model has no columns for these traits derived from biometric input.

Where it goes: 1 application source code, 2 data models, 7 prompt construction, 9 AI output handling.

What reviewers look for: no predict_ethnicity, infer_religion, classify_sexual_orientation, political_affinity, or similar function or label set fed by a face_embedding, voiceprint, gait, or iris input; no DeepFace 'race' action or equivalent vendor attribute; vision-model prompts that forbid inferring these traits; schemas without sensitive-trait fields sourced from biometrics.

result = DeepFace.analyze(img_path=photo, actions=['age', 'gender', 'race'])
profile.update(age=result[0]['age'], ethnicity=result[0]['dominant_race'])

result = DeepFace.analyze(img_path=photo, actions=['age'])   # no 'race' action
profile.update(age=result[0]['age'])

Engineering guidance, not legal advice. Each provision below may add its own details (a cadence, a deadline, a required notice element): open it for those.